School of Health and
Related Research
(ScHARR)
The University of Sheffield
Regent Court
30 Regent Street
Sheffield, S1 4DA...
Health Economics and
Decision Science (HEDS)
The purpose of HEDS section within ScHARR is to
promote excellence in nationa...
Portfolio of specialities of HEDS
1. Research
2. Post-graduate taught programmes
3. Short-term courses
14/05/2014 © The Un...
RESEARCH
Information
resources
Bayesian
Statistics in
Health
Economics
Evidence
review and
synthesis
Health
Economics and
Outcomes
...
14/05/2014 © The University of Sheffield
Consultancy
within HEDS
Modelling
alongside
clinical trials
Health
related
qualit...
Disease Areas
• Acute coronary syndrome
• Age-related macular degeneration
• Alcohol
• Alzheimer’s
• Ankylosing spondyliti...
Innovation & Knowledge
Transfer Contact details
Further information about consultancy projects and
research areas is avail...
Cost-effectiveness
modelling to support
Healthcare Decision
Making
14/05/2014 © The University of Sheffield
The Decision Analytic Modelling team is a
leading healthcare modelling group
internationally, with a wide ranging, high
im...
In particular:
• Cost-effectiveness modelling to
support HTA submissions
• Budget impact modelling
• Systematic reviews & ...
Examples of cost-
effectiveness studies
conducted in HEDS
14/05/2014 © The University of Sheffield
Evaluating the cost-
effectiveness of
diagnostic tests
Dr Matt Stevenson
Reader in Health Technology Assessment;
NICE Appr...
Overview
• A brief description of how (and why) cost-
effectiveness analyses are applied
• A brief overview of the analyse...
Cost-effectiveness
analyses
In the last 10 years there has a been a
considerable increase in the importance of cost-
effec...
Does a diagnostic test
represent value for money?
Diagnostic tests with high prices may be cost-
effective (i.e. a worthwh...
Cost-effectiveness
analyses
The goal of funding agencies is to provide the
greatest amount of health for society within th...
Previous Diagnostic
evaluations
Whilst the majority of evaluations undertaken relate
to pharmaceuticals, evaluations of di...
Methods for evaluating
diagnostic tests
There have been, for some time, clear methods
guide for undertaking evaluation of
...
Simplified Overview of the
modelling required
The following slides discuss the steps that would
be required to generate an...
Estimating Test Accuracy
The sensitivity and specificity of a diagnostic test
must be estimated.
These values would be com...
Modelling the patient
experience
For each of the four groups defined, an
estimation of the events that would occur to the
...
Modelling the patient
experience
Ultimately, an estimation of the life years, quality
adjusted life years (QALYs*) and cos...
Calculating an ICER*
Assume that post diagnosis, an average patient
was expected to gain 10 QALYs at a cost of
£20,000 und...
Calculating an ICER
In this example, the ICER would be £2,000 per
QALY gained (£2,000 / 1)
This would be compared with an ...
Implications for diagnostic
pricing
Where a new diagnostic test has a large impact
on mortality or on the utility of a pat...
Sequences and subgroups
Note that sequences of tests and only
incorporating tests on a subgroup of the
population are poss...
Example of diagnostic
algorithm
Taken from Goodacre et al. QJM 2006; 99:377–388
Returning to the example of
sepsis
Current gold standard is blood culture, but this
has poor sensitivity.
A new test is av...
Estimating the cost-
effectiveness of a Treat© and
SeptiFast© diagnostic strategy
For each Treat© category, the patient ex...
Estimating the cost-
effectiveness of a Treat© and
SeptiFast© diagnostic strategy
Thus there will be a QALY gain (and cost...
Additional complications with
evaluating diagnostic tests
There are reasons why evaluating diagnostic
tests are more diffi...
Complicating Issues
1) The need to understand the patient pathway
2) Data reporting
3) Missing and unobtainable data
4) Me...
NICE Decision Support Unit
Dr Paul Tappenden
Senior Research Fellow
Acting DSU Director
http://www.nicedsu.org.uk/
14/05/2...
Background to DSU
• Established in 2002.
• Formal collaboration between the Universities of
Sheffield (lead), York and Lei...
Main strands of work
1. Appraisal-specific work
• Rapid evaluation of technical issues/analysis
around health economic eva...
Appraisal-specific work
• ~7 appraisals per year
• Analysis of additional evidence submitted as part
of the appraisal proc...
The NICE Methods Guide for
Technology Appraisal
• Setting the agenda for, organising and
facilitating the NICE methods gui...
DSU Technical Support Documents
(TSDs)
• Series of independent, non-prescriptive reports commissioned to
support NICE Meth...
Other DSU methods research
• Report and related publications demonstrating the
feasibility of applying Value of Informatio...
Methods training
• Bridge between NICE and the pharmaceutical industry in
providing methods training
• “Masterclasses” hel...
Future updates
• Join our mailing list at :
http://www.nicedsu.org.uk
Health economic modelling in
bowel cancer
Dr Paul Tappenden
Senior Research Fellow
ScHARR, University of Sheffield
p.tappe...
Health economics and cancer
• Key area of methodological expertise in
ScHARR for >15 years
• Key areas include
breast, bow...
Key areas of application
1. Modelling interventions for the early detection /
prevention of cancer
2. Modelling interventi...
1. Modelling interventions for the
early detection / prevention of
cancer
• Methodological development in modelling natura...
An example – screening for CRC
14/05/2014 © The University of Sheffield
2. Modelling interventions for the
treatment of diagnosed cancer
• Curative / palliative treatments for diagnosed cancer
•...
An example – bevacizumab for
MCRC
14/05/2014 © The University of Sheffield
3. Whole Disease Modelling
• Usefulness of models is in part determined by the scope
of the decision it is intended to inf...
A lot of effort so why bother?
• Consistent basis for economic evaluation across the pathway
• Structurally capable of eva...
An example – Colorectal Cancer
Whole Disease Model
From piecewise CPQ to
constrained maximisation
14/05/2014 © The University of Sheffield
Colorectal cancer screening :
using mathematical modelling
to inform policy decisions
Dr Sophie Whyte
Research Fellow
ScHA...
Contents
Background
• The current NHS Bowel Cancer Screening Programme
• The flexible sigmoidoscopy screening trial
• Shou...
The current NHS Bowel Cancer Screening
Programme
• Roll out commenced in 2006 and now screening covers
the whole of Englan...
Flexible sigmoidoscopy(FS)
screening trial*
• Trial reported in 2010
• 170,432 persons aged 55-64 were randomised to FS
sc...
Should the screening programme be
changed in light of new evidence?
• Project for NHS cancer screening “Reappraisal of
opt...
Methods: Possible screening
scenarios
• Biennial screening with guaiac or
immunochemical FOBT for ages 60-74
• One-off FS ...
Methods: Advantages of
modelling
The number of possible screening strategies is
very large
To demonstrate a significant im...
Methods: Modelling challenges
Considerable uncertainty surrounding values of some
parameters essential for colorectal canc...
Methods: Modelling challenges
• Uncertainty in screening test characteristics
Sensitivity to CRC of the Haemoccult gFOBT :...
CRC natural history model
structure
14/05/2014 © The University of Sheffield
Normal Epithelium
Lowrisk adenomas
High risk ...
Methods: Modelling solutions
14/05/2014 © The University of Sheffield
0%
10%
20%
30%
40%
50%
60%
70%
80%
30 50 70 90
Polyp...
Methods: Modelling solutions
14/05/2014 © The University of Sheffield
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
30
35
40...
Methods: Modelling
solutions
14/05/2014 © The University of Sheffield
Parameter values are estimated by using a Bayesian a...
Results and conclusions
CRC screening is generally cost-effective: Tappenden et al found FS
screening to be cost saving an...
Potential impact on policy
decisions
Results of work will allow us to advise NHS cancer
screening on various aspects of FS...
Calibration method
The Metropolis-Hastings algorithm explores the multi-
dimensional parameter space to generate multiple ...
Cost utility analysis of interventions to
return employees to work following
long term sickness absence
Hazel Squires
Rese...
Introduction
• Background
• Project process
• Modelling methodology
• Results
• Conclusions
• Limitations/ further research
Background
• People can apply for Incapacity Benefit after
they have been on sick leave for >6 months.
• Sickness absence ...
Process
• Effectiveness literature review
• Very limited evidence identified – only 3 UK papers
• Cost-effectiveness liter...
Model scope
Population:
• A cohort of employed men & women that have been on
between 1 week and 6 months of sick leave due...
Modelling
methodology (1)
At work
On sick leave for
1 week -6 months
On sick leave for
6-12 months
On sick leave for
12-18...
Modelling methodology (2)
• Costs and QALYs have been calculated for both cohorts
starting at age 41 (average age of sickn...
Quality of life
Utility at
work
Utility on
sick leave
Age<35 0.83 0.66
Age 35-45 0.8 0.59
Age 45-55 0.76 0.61
Age>55 0.76 ...
Costs
State in
the model
Perspective
NHS & PSS Societal Employer
At work £0 £0 £0
1 wk to 6
months
sick leave
Cost of usua...
Key model assumptions (1)
• If an employee has not returned to work within 6 months
given the intervention they are subseq...
Key model assumptions (2)
• The employee is assumed to receive 15 weeks on full
pay and 16.4 weeks on half pay
• Wages and...
Results: NHS/ Societal perspective (1)
Workplace
Intervention
Physical activity
& Education
Physical activity,
Education &...
Results: NHS/ Societal perspective (2)
-£5,000
£0
£5,000
£10,000
£15,000
£20,000
£25,000
£30,000
£0 £1,000 £2,000 £3,000 £...
Results: Employer perspective
Workplace
Intervention
Physical activity
& Education
Physical activity,
Education &
Workplac...
One way sensitivity analysis
• If the difference in health utility between being at work
and being on LTS is ≤0.02 then co...
Conclusions
• The model suggests that interventions to return
employees to work do not have to be very effective
to be con...
Model limitations
• Effectiveness data based on generally poor evidence
carried out in non-UK countries
• Costs of interve...
Further research
Further research is required that:
• Is within the UK setting;
• Provides follow up data beyond 12 months...
Public health modelling:
lessons learned from a
contraception case study
Hazel Squires, Jim Chilcott, Nick Payne, Lindsay
...
Introduction
• Outline methods & results of contraception
case study
• Discuss key issues in public health
modelling based...
Aim of NICE contraceptive
services project
• To assess the effectiveness and cost-
effectiveness of interventions to
encou...
14/05/2014 © The University of Sheffield
Model scope
• Population:
Young people aged between 14 & 16 years within secondar...
14/05/2014 © The University of Sheffield
Conceptual model
Impact on
„unintended‟
pregnancies
Intervention to encourage
con...
Methods
• Markov model developed within Excel.
• Cohort of 100,000 14-year olds who have not
had a baby followed over life...
14/05/2014 © The University of Sheffield
Family, societal and individual characteristics
Long term
outcomes of child
Immed...
Literature review: long term outcomes
• Econometric literature review assessing long
term consequences of a teenage birth ...
14/05/2014 © The University of Sheffield
Model schematic
t
t+1
t+1
t
Concept
ion
(may be
mistime
d or
unwante
d)
No
concep...
14/05/2014 © The University of Sheffield
Key model assumptions
• The negative impacts of a teenage birth include:
• 4% mor...
Health outcomes
• Usually increasing life years is considered to be
a good thing. In this case, contraceptives aim to
prev...
14/05/2014 © The University of Sheffield
Cost-effectiveness decision rules
More
expensive
Less
effective
More
expensive
Mo...
14/05/2014 © The University of Sheffield
Results (excl. Benefits)
Cohort of 100,000 14-year olds followed over a lifetime
...
14/05/2014 © The University of Sheffield
Results (incl. Benefits)
Cohort of 100,000 14-year olds followed over a lifetime
...
Key issues in public health modelling
• Model scoping & granularity
• Extrapolating outcomes over the long term
• Valuing ...
Model scoping & granularity (1)
• Public health interventions & their settings are
complex.
• Often need to capture potent...
Model scoping & granularity (2)
• Formal OR problem structuring methods such
as cognitive mapping could be used:
1. To det...
Extrapolating outcomes
over the long term
• Trials generally collect intermediate outcomes.
• The relationship between the...
Valuing outcomes
• Within health economics, benefits are generally
measured in terms of QALYs gained
• Within public healt...
Handling uncertainty
• Within health economics, uncertainty within
model parameters is formally assessed using
probabilist...
Conclusions
• Dispensing contraceptives within schools to 14 –
16 yr olds is likely to be cost-effective
• Key areas for m...
High dose lipid-lowering
therapy
Is this strategy cost-
effective?
Roberta Ara
Senior Research Fellow
ScHARR, University o...
Background
Statin therapy for secondary CVD should
“usually be initiated with a drug with a low
acquisition cost (taking i...
The decision problem
To evaluate the cost-effectiveness of high
dose statins (atorvastatin 80mg/d,
rosuvastatin 40mg/d & s...
Markov health states
Post HS
Post HS Post HS
Post HS
Post HS
Post HS
QE: Hospitalisation unstable
angina
QE: New non-fatal...
Clinical Data
Literature review: 28 RCTs > 12 week
duration
Benefit: LDL-c
Synthesis: MTC
Relationship: LDL-c & CV events
Mean Relative Risks (95% CI)
Atorvastatin
80mg/d
Rosuvastatin
40mg/d
Simvastatin
40mg/d
Simvastatin
80mg/d
Non-fatal MI 0....
Adherence to therapies
Scenario A Scenario B
Yr 1 Yr 5 Yr 1 Yr 5
S40 ITT ITT ITT ITT
A80 ITT ITT 95% 85%
R40 ITT ITT 95% 8...
Treatment costs
Annual
cost Sensitivity analyses
Atorvastatin 80mg/d £368 £92
Rosuvastatin 40mg/d £387
Simvastatin 40mg/d ...
Results
Comparing with simvastatin 40mg/d:
Atorvastatin
80mg/d
Rosuvastatin
40mg/d
Simvastatin
80mg/d
Scenario A £17,469 £...
Results – reduced cost for
Atorvastatin
simvastatin 40mg/d
simvastatin 80mg/d
atorvastatin 80mg/d
rosuvastatin 40mg/d
0.00...
Summary & Conclusion
• Rosuvastatin 40mg/d is currently the most cost-
effective alternative
• Atorvastatin 80mg/d is the ...
A cost-effectiveness
model of prostate
cancer screening
Matthew Mildred, Jim Chilcott, Silvia Hummel
ScHARR, University of...
05/04/2011 © The University of Sheffield
Contents
• Introduction to the project and topic
• Disease natural history model
...
05/04/2011 © The University of Sheffield
The project
• Client:
UK National Screening Committee
• Purpose:
Help determine I...
05/04/2011 © The University of Sheffield
Introduction to prostate cancer
The prostate is a small gland in men behind the
b...
05/04/2011 © The University of Sheffield
Aim of screening:
Reduce cancer mortality, morbidity and treatment
costs through ...
05/04/2011 © The University of Sheffield
Challenges:
• Effectiveness of different screening programmes
unknown.
• Scarce d...
05/04/2011 © The University of Sheffield
Solution:
• Develop loosely parameterised cancer
screening simulation model.
• Ca...
05/04/2011 © The University of Sheffield
About the model:
• Disease natural history model (Simul8)
• Calibration module (E...
05/04/2011 © The University of Sheffield
Screening strategies
investigated
No. Screens Screening Age (years) Screening Int...
05/04/2011 © The University of Sheffield
Outputs:
• Age-specific incidence
• Age-specific mortality
• Prostate cancer stag...
05/04/2011 © The University of Sheffield
PCa
Onset
Screen
Detection
PCa
Mortality
Clinical
Diagnosis
Other
Cause
Mortality...
05/04/2011 © The University of Sheffield
Disease natural history model
05/04/2011 © The University of Sheffield
Data
Data Source
Age specific cancer incidence Office of National Statistics
Canc...
05/04/2011 © The University of Sheffield
Calibration process
05/04/2011 © The University of Sheffield
Total SSE during calibration
05/04/2011 © The University of Sheffield
Validation: Incidence
05/04/2011 © The University of Sheffield
Validation: PCa mortality
05/04/2011 © The University of Sheffield
Validation: BAUS
05/04/2011 © The University of Sheffield
Results: Incidence
0
2
4
6
8
10
12
14
16
45-49 50-54 55-59 60-64 65-69 70-74 75-7...
05/04/2011 © The University of Sheffield
Results: Mortality
0
1
2
3
4
5
6
7
8
45-49 50-54 55-59 60-64 65-69 70-74 75-79 80...
05/04/2011 © The University of Sheffield
Over-detection & Lead time:
Once at 50
50-74 every
4 years
50-74 every
2 years
50...
05/04/2011 © The University of Sheffield
Conclusions:
A minimal life gain is offset by the high levels of disease
manageme...
05/04/2011 © The University of Sheffield
Have you heard our findings?
BBC News 06/12/2010 http://www.bbc.co.uk/news/health...
05/04/2011 © The University of Sheffield
Acknowledgements:
• Dr Anne Mackie and Prof Julietta Patnick at the UK
National S...
Healthcare costs alone do not
describe the total costs directly
attributable to Ankylosing
Spondylitis
R. Ara1, R. Rafia1,...
Introduction
Ankylosing Spondylitis (AS) is a chronic,
progressive disease and prognosis is often
poor. In addition to dir...
Objectives
• To explore the total costs directly attributable to
AS patients attending rheumatological centres in
the UK.
...
Methods
Health care costs included: medications, inpatient, GP/ outpatient,
physiotherapy, hydrotherapy
Non medical indire...
Results (1)
Healthcare Utilisation:
41% reported no health care resources
45% reported no NHS funded healthcare resources
...
Results (2)
Total Costs:
The distribution of costs is heavily skewed with small number incurring
high costs and substantia...
Results (3)
Absenteeism/ presenteeism
25% of working age reported not working or early
retirement due to AS
25% (85/339) o...
Results (4)
Using BASDAI & BASFI to predict AS disease costs
Model 1:
Probability of incurring costs = 3.26106 +0.13308*BA...
Conclusion
This study shows that direct healthcare costs
alone do not describe the total costs associated
with AS and that...
The direct healthcare resource
costs associated with
Ankylosing Spondylitis patients
attending a UK secondary care
rheumat...
Introduction
• Anti-TNF inhibitors such as etanercept (ETN),
are now licensed for treating patients with
severe Ankylosing...
Objectives
• To explore the direct healthcare resources utilised by AS
patients attending a UK secondary care rheumatology...
Methods
Costs:
• Costs were assessed using a micro-costing approach
starting with a detailed inventory and measurement of
...
Results (1)
Mean Annual Disease Costs
• The mean total annual costs is estimated to be £1,837 (s.d. = £2,764; median =
£77...
Results (2)
Using BASDAI & BASFI to predict AS disease
costs
• Both the BASDAI and BASFI measurements were moderately
corr...
Discussion/Future Research
• The results of this costing study give an indication of the range of
direct healthcare costs ...
A treatment option for patients
with severe active Ankylosing
Spondylitis:
the costs and benefits associated
with etanerce...
Introduction
• Ankylosing Spondylitis (AS) is a progressive
inflammatory disease that can cause irreversible skeletal
dama...
Objective
To explore the costs and benefits associated
with etanercept (ETN) in patients with
severe AS in the UK under th...
Methods
• The model (written in Excel 2003) estimates the costs and benefits associated with ETN (2x
25mg/week) plus NSAID...
Assumptions
• Natural disease progression: BASFI increases at 0.7 units per
annum
• For responders to ETN: BASDAI & BASFI ...
Base case results
14/05/2014 © The University of Sheffield
Time horizon (years)
2 5 15 25
ETN 1,185 2,646 5,739 7,285
Comp...
Univariate sensitivity analyses
The tornado diagram shows that the three variables that have the
largest impact of the 25 ...
Monte Carlo results
• Using a 25 year horizon and a £30k per QALY threshold, ETN would be
considered a cost-effective trea...
Areas for future research
• Potential impact of radiological progression on long term
disability
• Efficacy of ETN in indi...
An economic evaluation of
etanercept in the treatment of
patients with psoriatic
arthritis
RM Ara and R Rafia
ScHARR, Univ...
Introduction
• Psoriatic Arthritis (PsA) is a chronic, progressive
disease and prognosis is often poor.
• Anti_TNF agents ...
Objective
• To explore the costs and benefits
associated with etanercept in the
treatment for patients with psoriatic
arth...
Methods
• The model compares ciclosporin to anti-TNF agents (etanercept, adalimumab,
infliximab) and it is assumed that pa...
Relationship between HAQ and HrQoL
Relationship estimated from PRESTA trial for the
base case:
Utility (EQ-5D) = 0.8996 – ...
Relationship between HAQ
and Direct health care Costs
• Health care costs include both primary and secondary care
resource...
Base case results
MEAN QALY MEAN COST (£) ICER
RESULTS AT 50YEARS (LIFETIME)
ETN 6.90 £65,650 £12,480
ADALIMUMAB 6.54 £61,...
Uncertainty in results
• The model results were sensitive to both the magnitude of the
rebound of HAQ after withdrawal fro...
Conclusion
While this evaluation provides evidence on the
potential cost-effectiveness of etanercept
compared to other ant...
Evidence Review and
Synthesis
14/05/2014 © The University of Sheffield
Extensive experience of systematic review
and evidence synthesis work for
• National Institute for Health and Clinical Exc...
Systematic review of clinical
evidence
High quality systematic reviews for submissions to key
reimbursement bodies or for ...
Generalised evidence synthesis
Classical and Bayesian meta analysis, including network
meta analysis
• RCTs
• Observationa...
Examples of Systematic
reviews conducted in
HEDS
14/05/2014 © The University of Sheffield
PET and MRI for the assessment
of axillary lymph node
metastases in early stage breast
cancer
A Systematic review
Susan Ha...
Background
• Axillary staging is important for breast cancer staging
and treatment planning
• Current techniques include
•...
Diagnostic pathway
• NICE diagnostic pathway
*Either fine needle aspiration cytology (FNAC) or core
biopsy.
• Positron emi...
HTA report
• National Institute for Health Research Health Technology
Assessment (HTA) programme commissioned research
to ...
Methods
• Searched eleven databases
• Inclusion criteria:
• Assessed diagnostic accuracy of PET or MRI
for assessment of a...
Diagnostic accuracy studies
• Patients are classified against a reference standard (eg
ALND or SLNB) as true positive, tru...
Results
14/05/2014 © The University of Sheffield
PET results
• Quality generally acceptable, though some problems
with patient spectrum, blinding, availability of relevant...
PET results – forest
plots
PET/CT
Study
Chae 2009
Heusner 2009
Kim 2009
Taira 2009
Fuster 2008
Ueda 2008
Veronesi 2007
TP
...
PET sensitivity analyses
MRI results
• Quality generally good. Some problems with patient
spectrum, availability of relevant clinical information a...
MRI results – forest plot
14/05/2014 © The University of Sheffield
USPIO-enhanced MRI
Study
Kimura 2009
Harada 2007
Memars...
MRI results
• Criteria for positivity varied across studies, including
variables of size, morphology and uptake. Uptake
pa...
Adverse effects
• No adverse effects were reported for PET
• Mild to moderate adverse effects reported
for MRI include mil...
Discussion
• PET, PET-CT and MRI have lower sensitivity and
specificity than ALND, SLNB and 4-NS
• PET and PET-CT are simi...
Discussion (2)
• Based on these estimates, if PET or MRI are used to
replace SLNB/4-NS in the diagnostic pathway, more
wom...
PET results – ROC plot
14/05/2014 © The University of Sheffield
All PET studies,
showing ROC curve
(solid line), mean
sens...
MRI results – ROC plot
14/05/2014 © The University of Sheffield
All MRI studies, showing ROC
curve (solid line), mean
sens...
Systematic reviews of relevant
data
Myfanwy Lloyd Jones
Senior Research Fellow
ScHARR, University of Sheffield
Email: m.ll...
More specifically
• Drawing on the experience of the pilot
diagnostics project, how do systematic
reviews of diagnostic in...
The review question
• Is there a bigger difference between the
overall project question and the question
that forms the fo...
Therapeutic intervention
Research question defined in the protocol:
• To establish the clinical and cost effectiveness of
...
In PICOS terms
• Population: postmenopausal women with
osteoporosis, with or without prior fracture
• Intervention: stront...
Diagnostic intervention
Decision problem defined in the protocol:
• Will using non-invasive liver assessment tools in
pati...
In PICOS terms:
population & intervention
• Population: patients suspected of having
liver fibrosis related to alcohol
con...
In PICOS terms: the
comparator
• The current UK decision-making process?
• What the NICE team wanted:
- A relevant compara...
In PICOS terms:
outcomes
• Test accuracy compared with the reference standard
• Number of test failures or other withdrawa...
In PICOS terms: study design
• Protocol: “The best available level of
evidence will be included, with priority
given to co...
Population (1)
• Therapeutic intervention:
• reasonable match between review question
and study populations (main exclusio...
Population (2)
In diagnostic studies, if the reference standard
is invasive (eg liver biopsy) or particularly
expensive, t...
Intervention
Therapeutic intervention:
• Description and other useful data from
EMEA and BNF
Diagnostic intervention:
• No...
Comparator: what is it?
Therapeutic intervention:
• No active intervention (placebo or no
treatment)
• Active intervention...
Comparator: issues
• Studies of diagnostic test accuracy assume that
the reference standard has 100% sensitivity and
speci...
Outcomes: therapeutic
intervention
• Primary outcome: fracture
• Clinical relevance clear
14/05/2014 © The University of S...
Outcomes: diagnostic
intervention
• Primary outcome: subject of debate
• Test accuracy?
• Fundamental: if the new test is ...
Reporting of outcomes:
therapeutic intervention (1)
• The Consort statement says that “for each
outcome, study results sho...
Reporting of outcomes:
therapeutic intervention (2)
• 1
14/05/2014 © The University of Sheffield
Number (%) Relative risk
...
Reporting of outcomes:
therapeutic intervention (3)
• Vertebral fracture:
• SOTI trial reported %ages plus RR; numbers of
...
Reporting of outcomes:
diagnostic intervention (1)
• The STARD (Standards for Reporting of
Diagnostic Accuracy) guidelines...
Reporting of outcomes:
diagnostic intervention (2)
Reference standard
positive
Reference standard
negative
Index test posi...
Reporting of outcomes:
diagnostic intervention (3)
14/05/2014 © The University of Sheffield
Reporting of outcomes:
diagnostic intervention (4)
• NILTs produce results on a continuous scale, but liver
biopsy results...
Study design
Therapeutic intervention:
• Only RCTs included
Diagnostic intervention:
• No relevant RCTs identified:
• Wher...
Meta-analysis (1)
Therapeutic intervention:
• Generally straightforward using Review
Manager
• In the strontium ranelate e...
Meta-analysis (2)
• Not appropriate if studies have heterogeneous
populations, and in diagnostic studies that
heterogeneit...
Systematic reviews of relevant
data
Myfanwy Lloyd Jones
Senior Research Fellow
ScHARR, University of Sheffield
Email: m.ll...
The aim of the assessment
To answer the research question: Will
using the specified non-invasive liver
assessment tools in...
The specified tests
 Three patented blood tests:
• The Enhanced Liver Fibrosis (ELF) test
• FibroTest
• FibroMAX
 Transi...
Outcomes of interest:
 Diagnostic test accuracy (including numbers of test
failures)
 Number of patients tested in prima...
Reference standard
tests
 Liver biopsy
 Also used in some studies
• Hepatic venous pressure gradient (HVPG)
measurement ...
Systematic review of
clinical effectiveness
 Population: patients with suspected alcohol-
related liver fibrosis
 Interv...
Included studies: ELF
test
 Rosenberg 2004: patients with
chronic liver disease (subgroup
with ALD); test accuracy vs liv...
Included studies:
FibroTest (1)
 2 studies specifically in patients with
known or suspected alcohol-related
liver disease...
Included studies:
FibroTest (2)
 3 studies in mixed aetiology liver disease:
• 1 study in patients with chronic liver dis...
Included studies:
FibroMAX
 No relevant studies identified
Included studies:
FibroScan (1)
 6 studies specifically in patients with known or
suspected alcohol–related liver disease...
Included studies:
FibroScan (2)
 3 studies in mixed aetiology liver disease:
• 1 study in patients undergoing transjugula...
AUROCs from key
studies: test vs liver biopsy
Test Degree of fibrosis Study AUROC (95% CI)
ELF „Moderate/severe‟ Rosenberg...
Sensitivity and
specificity: ELF Test
(subgroup with ALD)
Degree of fibrosis Study Threshold
score
Sensitivity Specificity...
Sensitivity and
specificity: FibroTest (all
patients ALD)
Degree of
fibrosis
Study Threshold
score
Sensitivity Specificity...
Sensitivity and specificity:
FibroScan (all patients ALD, all
biopsied)
Degree of fibrosis Study Threshold
score
Sensitivi...
Sensitivity and specificity:
FibroScan (all patients ALD, only
subset biopsied)
Degree of
fibrosis
Study Threshold
score
S...
FibroScan: exclusion of
patients with laboratory
signs of ASH
Degree of
fibrosis
No of
patients
AUROC Threshold
score
Sens...
Evidence re outcomes
of interest (1)
 Diagnostic test accuracy: NILTs appear to have
reasonable accuracy, but the evidenc...
Evidence re outcomes
of interest (2)
 Numbers of patients giving up or significantly
reducing alcohol consumption followi...
Liver biopsy: an imperfect
reference standard
 Diagnostic studies assume that the reference
standard has 100% sensitivity...
Liver biopsy: ethical
aspects affect study
design
 Adverse events:
• Minor adverse events: 9.39%
• Severe adverse events ...
How much homogeneity
is required for meta-
analysis?
 The studies of FibroTest and FibroScan
included in this review are ...
Health Economics and
Outcomes Research
14/05/2014 © The University of Sheffield
Areas of Particular Strength
• Quality of life and outcomes
measurement, wellbeing and equity
• Primary economic evaluatio...
Research centre
Centre for Well-being in Public Policy
(CWiPP)
• The goals of the centre are to consider as to how
people‟...
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
Cost utility analysis of interventions to return employees to work following long term sickness absence
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Cost utility analysis of interventions to return employees to work following long term sickness absence

  1. 1. School of Health and Related Research (ScHARR) The University of Sheffield Regent Court 30 Regent Street Sheffield, S1 4DA Website: www.sheffield.ac.uk/scharr
  2. 2. Health Economics and Decision Science (HEDS) The purpose of HEDS section within ScHARR is to promote excellence in national and international healthcare resource allocation decisions, through applied and theoretical research funded by the public and private sector; and supporting the effective implementation of the results of such research through education, training and management interventions 14/05/2014 © The University of Sheffield
  3. 3. Portfolio of specialities of HEDS 1. Research 2. Post-graduate taught programmes 3. Short-term courses 14/05/2014 © The University of Sheffield
  4. 4. RESEARCH
  5. 5. Information resources Bayesian Statistics in Health Economics Evidence review and synthesis Health Economics and Outcomes Research Cost-effectiveness modelling to support Healthcare Decision Making Main Focus of Research Areas
  6. 6. 14/05/2014 © The University of Sheffield Consultancy within HEDS Modelling alongside clinical trials Health related quality of life Clinical Trial Simulation Health Economics Modelling Evidence Synthesis Costing studies Systematic reviewing
  7. 7. Disease Areas • Acute coronary syndrome • Age-related macular degeneration • Alcohol • Alzheimer’s • Ankylosing spondylitis • Asthma • Back pain • Breast cancer • Cardiovascular conditions • Colon cancer • Colorectal cancer • Dementia • Depression • Dyskaryosis • Epilepsy • Flushing • Foot ulcers • Immune thrombocytopenic purpura • Influenza • Irritable bowel syndrome • Leg ulcers • Lymph node metastases • Menopause • Mental health problems • Multiple sclerosis • Overactive bladder • Prostate cancer • Psoriatic arthritis • Pulmonary hypertension • Renal disease • Rheumatoid arthritis • Schizophrenia • Sexual health • Surgical procedures in sex reassignment • Type 1 and Type 2 diabetes • Vaccination scheduling • Venous ulcers
  8. 8. Innovation & Knowledge Transfer Contact details Further information about consultancy projects and research areas is available at: http://www.sheffield.ac.uk/scharr/consultancy For an informal chat, contact the HEDS programme director, Roberta Ara: Email:r.m.ara@sheffield.ac.uk
  9. 9. Cost-effectiveness modelling to support Healthcare Decision Making 14/05/2014 © The University of Sheffield
  10. 10. The Decision Analytic Modelling team is a leading healthcare modelling group internationally, with a wide ranging, high impact programme of methodological and applied research. Research focuses on Operational Research modelling including both health technology assessment modelling and supporting service organisation and delivery.
  11. 11. In particular: • Cost-effectiveness modelling to support HTA submissions • Budget impact modelling • Systematic reviews & critique of cost- effectiveness literature • Critique / validate existing model • Country adaptations • Model adaptations
  12. 12. Examples of cost- effectiveness studies conducted in HEDS 14/05/2014 © The University of Sheffield
  13. 13. Evaluating the cost- effectiveness of diagnostic tests Dr Matt Stevenson Reader in Health Technology Assessment; NICE Appraisal Committee Member; Contributor to the NICE Diagnostic Assessment Programme manual
  14. 14. Overview • A brief description of how (and why) cost- effectiveness analyses are applied • A brief overview of the analyses required to model diagnostic tests in sepsis • A very brief description of the reasons why diagnostic evaluations are more difficult than pharmaceutical evaluations
  15. 15. Cost-effectiveness analyses In the last 10 years there has a been a considerable increase in the importance of cost- effectiveness analyses. This was due to the relatively fixed budget and a combination of ageing populations and emerging expensive interventions. This has led to the formation of funding agencies in England and Wales, Scotland, Australia and Canada.
  16. 16. Does a diagnostic test represent value for money? Diagnostic tests with high prices may be cost- effective (i.e. a worthwhile use of a limited budget). Conversely, diagnostic tests with low prices may not be cost-effective. The „gold standard‟ approach for determining whether the price of a diagnostic test is justified is through an economic evaluation, or cost- effectiveness analysis.
  17. 17. Cost-effectiveness analyses The goal of funding agencies is to provide the greatest amount of health for society within the budget, and thus opportunity cost is a key principle. That is, what health would be lost if money was diverted from one intervention in order to fund another. The process is typically to estimate the cost- effectiveness of an intervention through modelling, and comparing this result with a value assumed to represent opportunity cost.
  18. 18. Previous Diagnostic evaluations Whilst the majority of evaluations undertaken relate to pharmaceuticals, evaluations of diagnostic tests have been conducted: •Carotid Artery Imaging - Wardlow et al. HTA •Thrombophilia Testing - Simpson et al. HTA • BMD Scanning (Strontium Ranelate) – Stevenson et al HTA •Diagnostic strategies for DVT – Goodacre et al HTA • Diagnostic pathways for minor head injuries – Pandor et al. HTA • Non-Invasive Liver Testing – Stevenson et al HTA (in press)
  19. 19. Methods for evaluating diagnostic tests There have been, for some time, clear methods guide for undertaking evaluation of pharmaceutical interventions. Recently NICE has set up a Diagnostic Assessment Programme which has issues an interim statement of the methods it expects to be followed in evaluating diagnostics. http://www.nice.org.uk/media/164/3C/DAPInterim MethodsStatementProgramme.pdf
  20. 20. Simplified Overview of the modelling required The following slides discuss the steps that would be required to generate an estimate of the cost- effectiveness of a diagnostic test (or series of diagnostic tests). The overview is a simplification. More detailed discussion is provided in the previously listed HTA reports (all free to download) and the Diagnostic Methods statement
  21. 21. Estimating Test Accuracy The sensitivity and specificity of a diagnostic test must be estimated. These values would be combined with the estimated prevalence of the condition being tested for, to form an expectation of the number of true positives, true negatives, false positives and false negatives generated by the diagnostic test.
  22. 22. Modelling the patient experience For each of the four groups defined, an estimation of the events that would occur to the patient must be modelled. These may differ due to underlying risks and the chosen medical management. The modelling would include factors such as the risks of mortality, risk of morbidity, length of stay within hospital, costs for initial and subsequent care, treatment-related adverse-events and the quality of life for patients in each potential health state.
  23. 23. Modelling the patient experience Ultimately, an estimation of the life years, quality adjusted life years (QALYs*) and costs can be attributed to each of the four groups. These can be weighted by the proportions in each group to form a total cost and total QALY for patients post diagnosis. The costs of the diagnostic tests performed are then added. * The QALY is a combination of life years and patient utility. A person living for 10 years at a utility of 0.5 would gain 5 QALYs; a person living for 4 years at a utility of 0.75 would gain 3 QALYs
  24. 24. Calculating an ICER* Assume that post diagnosis, an average patient was expected to gain 10 QALYs at a cost of £20,000 under current best practice. These values became 11 QALYs at a cost of £18,000 following a new diagnostic test, which costs £4,000 per patient. In this instance the increase in cost is £2,000 (£18,000 - £20,000 + £4,000) The increase in QALYs is 1. (11 – 10) * An Incremental Cost Effectiveness Ratio.
  25. 25. Calculating an ICER In this example, the ICER would be £2,000 per QALY gained (£2,000 / 1) This would be compared with an estimation of the cost of gaining a QALY in interventions that are likely to be replaced.* Thus if this were the result from a real technology appraisal the diagnostic test would be likely to be recommended for use. * NICE has estimated this to be in the region of £20,000-£30,000
  26. 26. Implications for diagnostic pricing Where a new diagnostic test has a large impact on mortality or on the utility of a patient, then the QALY gained over the current diagnostic will be greater. ICER = Δ Cost / Δ QALY Thus, for a constant ICER, such a test would be able to command a higher price than a test with a smaller QALY gain.
  27. 27. Sequences and subgroups Note that sequences of tests and only incorporating tests on a subgroup of the population are possible. The following slide shows the predicted optimal strategy for diagnosing whether a patient has deep vein thrombosis. The costs of diagnostic tests, the risks of death, morbidity, recurrence, treatment-related adverse-events and the costs of treating future events were all considered in the model.
  28. 28. Example of diagnostic algorithm Taken from Goodacre et al. QJM 2006; 99:377–388
  29. 29. Returning to the example of sepsis Current gold standard is blood culture, but this has poor sensitivity. A new test is available (SeptiFast©) which has higher accuracy than blood culture tests, but is relatively expensive. The price may preclude use in all patients with suspected sepsis. A decision support system is also available, (Treat ©) which can categorise patients into high, medium and low risk. This may allow SeptiFast© to be used more efficiently.
  30. 30. Estimating the cost- effectiveness of a Treat© and SeptiFast© diagnostic strategy For each Treat© category, the patient experience must be modelled taking into account true positives, false positives, true negatives and false negatives. This will incorporate (amongst others) •Risks of mortality •Risks of post-infection sequalae •Length of stay in hospital These variables are expected to be lower where there is appropriate management of a patient with sepsis.
  31. 31. Estimating the cost- effectiveness of a Treat© and SeptiFast© diagnostic strategy Thus there will be a QALY gain (and cost reduction) associated with the new diagnostic tests. It is expected that these will be greatest in those patients denoted high risk. Factoring in the costs of the diagnostic (Treat© for all patients, SeptiFast© for the groups being evalauted) will allow the cost-effectiveness of diagnostic strategies to be evaluated.
  32. 32. Additional complications with evaluating diagnostic tests There are reasons why evaluating diagnostic tests are more difficult than evaluating pharmaceuticals. Due to time restrictions these will be mentioned very briefly under broad headings.
  33. 33. Complicating Issues 1) The need to understand the patient pathway 2) Data reporting 3) Missing and unobtainable data 4) Meta-analyses 5) Correlation between tests 6) Imperfect gold standards 7) Required operator skill 8) Spectrum bias 9) Incidental findings 10) Estimating the costs of diagnostic tests
  34. 34. NICE Decision Support Unit Dr Paul Tappenden Senior Research Fellow Acting DSU Director http://www.nicedsu.org.uk/ 14/05/2014 © The University of Sheffield
  35. 35. Background to DSU • Established in 2002. • Formal collaboration between the Universities of Sheffield (lead), York and Leicester. • Peripheral members at LSHTM, Brunel and Bristol. • May also involve highly specialist expertise from elsewhere. • Expertise covers all key areas of HTA. • Commissioned by NICE to provide a research and training resource to support the Institute's Technology Appraisal Programme.
  36. 36. Main strands of work 1. Appraisal-specific work • Rapid evaluation of technical issues/analysis around health economic evaluation/modelling problems within specific technology appraisals • An independent yet highly qualified voice 2. Methods development • Ongoing role in developing Methods guidance for NICE • DSU Technical Support Documents • Training for industry and NICE Appraisal Committee members • Other methods work
  37. 37. Appraisal-specific work • ~7 appraisals per year • Analysis of additional evidence submitted as part of the appraisal process • Cetuximab for 1st line metastatic colorectal cancer • Lapatinib for metastatic breast cancer • Provision of modelling expertise unavailable elsewhere (software) • Donepezil for Alzheimer‟s Disease • Evaluating Patient access schemes (PAS) • Tocilizumab for Rheumatoid Arthritis
  38. 38. The NICE Methods Guide for Technology Appraisal • Setting the agenda for, organising and facilitating the NICE methods guide for technology appraisal • Recent work includes managing the update to the 2008 NICE methods guide – 6 workshops covering issues around evidence synthesis, utilities, uncertainty analysis, subgroups etc. • Update due in 2011/2012 • Conduit for leading academic centres in HTA
  39. 39. DSU Technical Support Documents (TSDs) • Series of independent, non-prescriptive reports commissioned to support NICE Methods Guide • 14 TSDs completed or near completion • Main areas: • Health utilities (x5) • Evidence synthesis (x7) • Model development and reviewing evidence for informing model parameters • Survival modelling using individual patient data • Use of regression methods in HTA models
  40. 40. Other DSU methods research • Report and related publications demonstrating the feasibility of applying Value of Information methods. • Feasibility projects relating to computerised decision support systems and orphan drugs • Equity arguments applied to orphan drugs • Discounting of costs and benefits • The role of patient valuations of health states • The incorporation of uncertainty into cost-effectiveness models • The incorporation of equity weights into cost effectiveness models and decision making
  41. 41. Methods training • Bridge between NICE and the pharmaceutical industry in providing methods training • “Masterclasses” held: • Measurement and valuation of health-related quality of life • Network meta-analysis & indirect comparisons • NICE Appraisal Process, modelling, what makes a good submission, uncertainty analysis
  42. 42. Future updates • Join our mailing list at : http://www.nicedsu.org.uk
  43. 43. Health economic modelling in bowel cancer Dr Paul Tappenden Senior Research Fellow ScHARR, University of Sheffield p.tappenden@sheffield.ac.uk 14/05/2014 © The University of Sheffield
  44. 44. Health economics and cancer • Key area of methodological expertise in ScHARR for >15 years • Key areas include breast, bowel, cervical, CML, kidney, prostate, lu ng • Range of decision-makers/clients including: – NICE – NETSCC / NHS R&D Programme – NHS Cancer Screening Programmes – Department of Health – Local decision-makers
  45. 45. Key areas of application 1. Modelling interventions for the early detection / prevention of cancer 2. Modelling interventions for the treatment of diagnosed cancer 3. Modelling whole disease and treatment pathways (Whole Disease Modelling)
  46. 46. 1. Modelling interventions for the early detection / prevention of cancer • Methodological development in modelling natural history disease progression – Handling competing risks – Length / lead-time biases – Consideration of full trade-off between costs and benefits – Calibration of unobservable parameters (disease progression, presentation behaviours etc) • Evaluation of screening programmes in breast, bowel, cervical and prostate cancer • Evaluation of early awareness campaigns
  47. 47. An example – screening for CRC 14/05/2014 © The University of Sheffield
  48. 48. 2. Modelling interventions for the treatment of diagnosed cancer • Curative / palliative treatments for diagnosed cancer • Numerous appraisals for NICE - main areas covered include bowel and breast • Key issues around methods for handling • Extrapolation beyond trial duration • Handling treatment crossover • Treatment sequences • Evidence networks across multiple trials
  49. 49. An example – bevacizumab for MCRC 14/05/2014 © The University of Sheffield
  50. 50. 3. Whole Disease Modelling • Usefulness of models is in part determined by the scope of the decision it is intended to inform. • Single isolated point versus whole pathway model. • “Modelling the bigger picture” – development of models which can represent whole disease and treatment pathways
  51. 51. A lot of effort so why bother? • Consistent basis for economic evaluation across the pathway • Structurally capable of evaluating any intervention at any point in the pathway • Capturing upstream and downstream knock-on impacts • Shift to potentially more useful economic decision rules • Methodological challenges • Obtaining agreement regarding pathways • Handling geographical variability • Programming / model run time • Calibration of unobservable parameters • Non-trivial investment of time at outset but payoff may be considerable
  52. 52. An example – Colorectal Cancer Whole Disease Model
  53. 53. From piecewise CPQ to constrained maximisation 14/05/2014 © The University of Sheffield
  54. 54. Colorectal cancer screening : using mathematical modelling to inform policy decisions Dr Sophie Whyte Research Fellow ScHARR, University of Sheffield Email: s.whyte@sheffield.ac.uk 14/05/2014 © The University of Sheffield
  55. 55. Contents Background • The current NHS Bowel Cancer Screening Programme • The flexible sigmoidoscopy screening trial • Should the screening programme be changed? Methods • Possible screening strategies to consider • The value of modelling in this context • Modelling challenges • Modelling solutions Results and conclusions • Results • Policy implications 14/05/2014 © The University of Sheffield
  56. 56. The current NHS Bowel Cancer Screening Programme • Roll out commenced in 2006 and now screening covers the whole of England. • Persons aged 60-69 (being increased to age 74) are offered biennial screening. • The guaiac faecal occult blood (gFOB) test is used for screening and positives(≈2%) receive follow up with colonoscopy. • Uptake is 52% 14/05/2014 © The University of Sheffield
  57. 57. Flexible sigmoidoscopy(FS) screening trial* • Trial reported in 2010 • 170,432 persons aged 55-64 were randomised to FS screening or to a control group (no screening). • 40,674 persons underwent FS screening • After 10 years of follow-up the incidence of CRC was reduced by 33% and mortality was reduced by 43% in the FS group. *Atkin et al 2010, Once-only flexible sigmoidoscopy screening in prevention of colorectal cancer: a multicentre randomised controlled trial, The Lancet 14/05/2014 © The University of Sheffield
  58. 58. Should the screening programme be changed in light of new evidence? • Project for NHS cancer screening “Reappraisal of options for CRC screening” • Update to “Appraisal of options for CRC screening” completed by Tappenden et al in 2004. • The reappraisal uses: (1) Data from existing screening programme, (2) Data from FS trial, (3) Data on newer immunochemical FOBTs 14/05/2014 © The University of Sheffield
  59. 59. Methods: Possible screening scenarios • Biennial screening with guaiac or immunochemical FOBT for ages 60-74 • One-off FS screening (for different ages) • Combination screening strategies e.g. FS at age 55 then biennial FOBT at ages 60-74 14/05/2014 © The University of Sheffield
  60. 60. Methods: Advantages of modelling The number of possible screening strategies is very large To demonstrate a significant impact on incidence and mortality rates screening trials require: • very large numbers of participants • a long follow-up period Hence modelling is very useful for the evaluation of screening strategies 14/05/2014 © The University of Sheffield
  61. 61. Methods: Modelling challenges Considerable uncertainty surrounding values of some parameters essential for colorectal cancer screening modelling. • Uncertainty in underlying prevalence of precancerous conditions: 14/05/2014 © The University of Sheffield 0% 10% 20% 30% 40% 50% 60% 70% 80% 30 50 70 90 Polypprevalence Age Polyp prevalence from autopsy studies
  62. 62. Methods: Modelling challenges • Uncertainty in screening test characteristics Sensitivity to CRC of the Haemoccult gFOBT : range 0.25-0.96* • Uncertainty(very little data) on growth rates of colorectal cancer and precancerous conditions as: (1) difficult to observe and (2) cancers are removed if found. 14/05/2014 © The University of Sheffield * Burch JA, Soares-Weiser K, St John DJ, et al. Diagnostic accuracy of faecal occult blood tests used in screening for colorectal cancer: a systematic review. J Med Screen 2007;14(3):132-7.
  63. 63. CRC natural history model structure 14/05/2014 © The University of Sheffield Normal Epithelium Lowrisk adenomas High risk adenomas Dukes’A CRC Dukes’B CRC Dukes’C CRC Stage D CRC Dead (CRC) Dukes’A CRC clinical Dukes’C CRC clinical Stage D CRC clinical Dukes’B CRC clinical Dead (non-CRC) Transition estimated within model calibration Transition estimated directly from mortality data
  64. 64. Methods: Modelling solutions 14/05/2014 © The University of Sheffield 0% 10% 20% 30% 40% 50% 60% 70% 80% 30 50 70 90 Polypprevalence Age Polyp prevalence from autopsy studies 0% 10% 20% 30% 40% 50% 60% 70% 30 40 50 60 70 80Age Polyp detection rate at FS screeningPolyp prevalence Sensitivity of screening test to polyps
  65. 65. Methods: Modelling solutions 14/05/2014 © The University of Sheffield 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Age Statedistribution Normal epithelium CRC High risk polyp Lowrisk polyp 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 30 40 50 60 70 80 90 Incidence Age Probability of diagnosis of CRC (due to symptoms or chance detection) State allocation diagram CRC incidence in absence of screening
  66. 66. Methods: Modelling solutions 14/05/2014 © The University of Sheffield Parameter values are estimated by using a Bayesian approach in which sets of parameter values for which the model predictions have a good fit to observed data are generated.*
  67. 67. Results and conclusions CRC screening is generally cost-effective: Tappenden et al found FS screening to be cost saving and FOBT screening the have an ICER<£3K. “Reappraisal Project” results will be available by the end of October. DOH Press Release 2nd October 2010 “New Action on Cancer to Save Thousands More Lives Every Year Increase detection through a revolutionary new bowel cancer screening technology flexible sigmoidoscopy – a £60 million investment over the next four years to incorporate the latest breakthrough in bowel cancer screening into our existing national programme – saving 3,000 lives a year.” 14/05/2014 © The University of Sheffield
  68. 68. Potential impact on policy decisions Results of work will allow us to advise NHS cancer screening on various aspects of FS screening implementation. • At what age will a one-off FS screen provide the greatest health benefits? • How cost effective are combined screening strategies? • Would it be cost effective to create a national polyp centre to process all pathology generated through screening? • What level of FS uptake is required to achieve the same health benefits as the current screening programme? 14/05/2014 © The University of Sheffield
  69. 69. Calibration method The Metropolis-Hastings algorithm explores the multi- dimensional parameter space to generate multiple sets of parameters for which the model predictions have a good fit to observed data. 14/05/2014 © The University of Sheffield Parameter1 Parameter2 Difference between model predictions and observed data
  70. 70. Cost utility analysis of interventions to return employees to work following long term sickness absence Hazel Squires Research Fellow ScHARR, University of Sheffield Email: h.pilgrim@sheffield.ac.uk 14/05/2014 © The University of Sheffield
  71. 71. Introduction • Background • Project process • Modelling methodology • Results • Conclusions • Limitations/ further research
  72. 72. Background • People can apply for Incapacity Benefit after they have been on sick leave for >6 months. • Sickness absence in the UK costs the country around 1% of the annual GDP. • There is a need to prevent people from going onto Incapacity Benefit.
  73. 73. Process • Effectiveness literature review • Very limited evidence identified – only 3 UK papers • Cost-effectiveness literature review • No studies identified which consider the implications of RTW within the UK setting over a sufficient time frame to capture all impacts on costs and benefits of the interventions • Health economic model
  74. 74. Model scope Population: • A cohort of employed men & women that have been on between 1 week and 6 months of sick leave due to musculoskeletal disorders. Interventions: • Workplace intervention • Physical activity and education intervention • Physical activity, education and workplace visit Comparator: • Usual care for musculoskeletal disorders Outcomes: • Cost per quality-adjusted life year (QALY) gained • Cost per day on sick leave avoided Perspective: • NHS and PSS • Societal • Employer
  75. 75. Modelling methodology (1) At work On sick leave for 1 week -6 months On sick leave for 6-12 months On sick leave for 12-18 months On sick leave for 18+ months Retirement or death • Markov model which simulates the experience of a hypothetical cohort of employees who are currently on long term sick leave over a working lifetime.
  76. 76. Modelling methodology (2) • Costs and QALYs have been calculated for both cohorts starting at age 41 (average age of sickness absence from evidence) through to retirement at age 66. • Discount rate of 3.5% for both costs and utilities. • One-way sensitivity analysis and threshold analysis carried out.
  77. 77. Quality of life Utility at work Utility on sick leave Age<35 0.83 0.66 Age 35-45 0.8 0.59 Age 45-55 0.76 0.61 Age>55 0.76 0.61 • Utility scores estimated based on data from the British Household Survey Panel (BHSP) • Based on whether the individual is at work or on sick leave •Sf-36 SF-6D Transformed using SPSS • Impact of potential confounding variables assessed using regression
  78. 78. Costs State in the model Perspective NHS & PSS Societal Employer At work £0 £0 £0 1 wk to 6 months sick leave Cost of usual care and intervention incurred by NHS NHS & PSS costs + Employer costs - Transfer costs Cost of intervention incurred by employer + Cost of replacing employee + Production loss over friction period + Salary of replacement employee after friction period + Occupational sick pay + Employer‟s NI contribution 6-12 months sick leave Cost of usual care Cost of usual care Occupational sick pay + Employer‟s NI contribution 12 months+ sick leave Cost of usual care Cost of usual care
  79. 79. Key model assumptions (1) • If an employee has not returned to work within 6 months given the intervention they are subsequently no more likely to RTW than an employee who is given usual care • The intervention is only given the first time that the person goes onto LTS • The probability of going onto further episodes of LTS is the same for the intervention cohort and the usual care cohort
  80. 80. Key model assumptions (2) • The employee is assumed to receive 15 weeks on full pay and 16.4 weeks on half pay • Wages and productivity of a replacement worker are assumed to be the same as the employee on LTS • The probability of dying is assumed to be no different for people on LTS to people who are at work
  81. 81. Results: NHS/ Societal perspective (1) Workplace Intervention Physical activity & Education Physical activity, Education & Workplace visit -£500 -£400 -£300 -£200 -£100 £0 £100 £200 £300 £400 £500 -0.50 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50 Difference in QALYs Differenceincosts Cost per QALY gained = £2,758
  82. 82. Results: NHS/ Societal perspective (2) -£5,000 £0 £5,000 £10,000 £15,000 £20,000 £25,000 £30,000 £0 £1,000 £2,000 £3,000 £4,000 £5,000 Additional cost of intervention per employee CostperQALYgained relative risk of RTW of 1.05 (32/1000 additional employees RTW) relative risk of RTW of 1.1 (65/1000 additional employees RTW) relative risk of RTW of 1.2 (130/1000 additional employees RTW) relative risk of RTW of 1.3 (194/1000 additional employees RTW) relative risk of RTW of 1.4 (259/1000 additional employees RTW)
  83. 83. Results: Employer perspective Workplace Intervention Physical activity & Education Physical activity, Education & Workplace visit -£200 -£150 -£100 -£50 £0 £50 £100 £150 £200 -1,500 -1,000 -500 0 500 1,000 1,500 Days on sick leave avoided Differenceincosts Cost per day on sick leave avoided = £0.34
  84. 84. One way sensitivity analysis • If the difference in health utility between being at work and being on LTS is ≤0.02 then cost per QALY >£20,000. • If the person is aged 55 when going onto LTS then cost per QALY >£8,000. • All other assumptions tested within the model had a limited impact on model results
  85. 85. Conclusions • The model suggests that interventions to return employees to work do not have to be very effective to be considered cost-effective in comparison to other technologies routinely funded by the NHS. • This can be explained by the high costs of productivity loss and Incapacity Benefit in comparison to the relatively low cost of the intervention.
  86. 86. Model limitations • Effectiveness data based on generally poor evidence carried out in non-UK countries • Costs of interventions are uncertain • Lack of long term follow up data • Only able to consider interventions for musculoskeletal disorders due to limited data on interventions for other sickness absence • Does not take into account different employee/ employer characteristics (although some tested in sensitivity analyses)
  87. 87. Further research Further research is required that: • Is within the UK setting; • Provides follow up data beyond 12 months; • Reports comparable return to work outcomes between studies; • Reports quality of life data of the employees who are both at work and on sick leave.
  88. 88. Public health modelling: lessons learned from a contraception case study Hazel Squires, Jim Chilcott, Nick Payne, Lindsay Blank, Monica Hernandez, Louise Guillaume ScHARR, University of Sheffield
  89. 89. Introduction • Outline methods & results of contraception case study • Discuss key issues in public health modelling based upon this work
  90. 90. Aim of NICE contraceptive services project • To assess the effectiveness and cost- effectiveness of interventions to encourage young people to use contraceptives and contraceptive services 14/05/2014 © The University of Sheffield
  91. 91. 14/05/2014 © The University of Sheffield Model scope • Population: Young people aged between 14 & 16 years within secondary school who have not previously been a parent. • Interventions: • School-based dispensing of hormonal contraceptives to 14-16 year olds • School-based „dispensing‟ of condoms to 14-16 year olds • Comparator: School nurse only • Outcomes: • Cost per age 14 – 16 Pregnancy Averted • Cost per Abortion Averted • Perspective: Public sector perspective (incl. & excl. Benefit payments)
  92. 92. 14/05/2014 © The University of Sheffield Conceptual model Impact on „unintended‟ pregnancies Intervention to encourage contraceptive use Sexually transmitted infection (STI) rate Treatment of STIs Impact upon contraceptive services Abortion Miscarriage/ ectopic Pregnancy/ stilbirth Birth Mistimed UnwantedLow birth weight baby Maternity care Social care Mental health problems (eg. depression) Child health problems Crime Government- funded Benefits Education/ employment impacts
  93. 93. Methods • Markov model developed within Excel. • Cohort of 100,000 14-year olds who have not had a baby followed over lifetime. • Each year there is a probability of becoming pregnant. • Following conception, dependent upon age, there is a probability of birth, abortion, miscarriage, ectopic pregnancy or stillbirth. • Costs are associated with each of these outcomes. 14/05/2014 © The University of Sheffield
  94. 94. 14/05/2014 © The University of Sheffield Family, societal and individual characteristics Long term outcomes of child Immediate birth outcomes Long term outcomes of parent(s) Low social class Teenage birth Poor education Poor employment More claims for Means- tested Benefits Teenage pregnancy Crime Low birth weight Foetal death Poorly educated mother Poor behaviour/ education as child Other observable or unobservable characteristics A B C Outcomes of teenage birth
  95. 95. Literature review: long term outcomes • Econometric literature review assessing long term consequences of a teenage birth in the UK • Controlling for observable & unobservable characteristics (eg. personality) which might predispose a young woman to teenage motherhood • Eg. Comparing those who‟ve had a teenage miscarriage with those that have had a baby as a teenager 14/05/2014 © The University of Sheffield
  96. 96. 14/05/2014 © The University of Sheffield Model schematic t t+1 t+1 t Concept ion (may be mistime d or unwante d) No conceptio n (may Aborti on Birth Miscarriage/ ectopic pregnancy/ stillbirth Additional proportion of low birth weight babies Additional Benefit claims of teenage parents Cohort of young people ST I No STI t+ 1 t t t+ 1
  97. 97. 14/05/2014 © The University of Sheffield Key model assumptions • The negative impacts of a teenage birth include: • 4% more likely to receive Income Support & associated Benefits until age 35 years; • 90% will receive Income Support immediately, hence the earlier the birth, the more years it is received for; • <1% more babies will be low birth weight. • 50% of averted teenage births are mistimed & 50% are unwanted. • STIs are assumed to be transmitted to 1 person only.
  98. 98. Health outcomes • Usually increasing life years is considered to be a good thing. In this case, contraceptives aim to prevent life. • There is no long term quality of life evidence associated with motherhood by age, adjusted for socioeconomic status • Similarly, there is no quality of life evidence associated with the child by age of motherhood 14/05/2014 © The University of Sheffield
  99. 99. 14/05/2014 © The University of Sheffield Cost-effectiveness decision rules More expensive Less effective More expensive More effective Less expensive Less effective Less expensive More effective Difference in effectivenessDifferenceincosts NO YES
  100. 100. 14/05/2014 © The University of Sheffield Results (excl. Benefits) Cohort of 100,000 14-year olds followed over a lifetime -£1,000 -£800 -£600 -£400 -£200 £0 £200 £400 £600 £800 £1,000 0 200 400 600 800 1000 1200 Thousands Age 14 - 16 pregnancies averted Differenceincosts Dispensing condoms within schools Dispensing hormonal contraceptives within schools Expected cost per age 14 – 16 pregnancy averted = £37 (condoms) & £110 (hormonal) compared with no intervention Approx. 50% probability that cost-saving
  101. 101. 14/05/2014 © The University of Sheffield Results (incl. Benefits) Cohort of 100,000 14-year olds followed over a lifetime -£30 -£25 -£20 -£15 -£10 -£5 £0 0 100 200 300 400 500 600 700 800 900 1000 Millions Age 14 - 16 pregnancies averted Differenceincosts Dispensing condoms within schools Dispensing hormonal contraceptives within schools Dominates no intervention
  102. 102. Key issues in public health modelling • Model scoping & granularity • Extrapolating outcomes over the long term • Valuing outcomes • Handling uncertainty 14/05/2014 © The University of Sheffield
  103. 103. Model scoping & granularity (1) • Public health interventions & their settings are complex. • Often need to capture potentially adaptive behaviour (eg. sexual behaviour). • Often several health areas to be modelled (in this case, pregnancies & STIs). • Intersectoral impacts (not just health) 14/05/2014 © The University of Sheffield
  104. 104. Model scoping & granularity (2) • Formal OR problem structuring methods such as cognitive mapping could be used: 1. To determine the model scope 2. To make sure that all important costs & outcomes associated with the intervention are captured • Further research around the use of these methods applied to public health modelling is required 14/05/2014 © The University of Sheffield
  105. 105. Extrapolating outcomes over the long term • Trials generally collect intermediate outcomes. • The relationship between these outcomes & final outcomes needs to be understood. • Long term outcomes (eg. employment) are dependent upon many factors; hence econometric techniques will generally be required to disentangle the impacts of the intervention. 14/05/2014 © The University of Sheffield
  106. 106. Valuing outcomes • Within health economics, benefits are generally measured in terms of QALYs gained • Within public health economic modelling, the QALY measure may not be sufficiently broad eg. intersectoral costs/ consequences • There is also generally limited evidence around utilities • Further research is required around alternative outcome measures 14/05/2014 © The University of Sheffield
  107. 107. Handling uncertainty • Within health economics, uncertainty within model parameters is formally assessed using probabilistic sensitivity analysis (PSA) • The structure of public health models is also often highly uncertain eg. modelling mistimed pregnancies • It is important to parameterise structural uncertainties & include these within the PSA as outlined by Bojke et al. (2006). 14/05/2014 © The University of Sheffield
  108. 108. Conclusions • Dispensing contraceptives within schools to 14 – 16 yr olds is likely to be cost-effective • Key areas for methodological development within public health modelling: • Model scoping & level of granularity • Extrapolating outcomes over the long term • Valuing outcomes • Handling uncertainty
  109. 109. High dose lipid-lowering therapy Is this strategy cost- effective? Roberta Ara Senior Research Fellow ScHARR, University of Sheffield Email: r.m.ara@sheffield.ac.uk
  110. 110. Background Statin therapy for secondary CVD should “usually be initiated with a drug with a low acquisition cost (taking into account required daily dose and product price per dose)” (www.nice.org.uk/TA094, 2006) Savings: £1 billion over 5 years {Moon BMJ, 2006} 69% PCT switch to generic statins → NHS savings ≥ £85m/year (www.institute.nhs.uk, 2007)
  111. 111. The decision problem To evaluate the cost-effectiveness of high dose statins (atorvastatin 80mg/d, rosuvastatin 40mg/d & simvastatin 80mg/d) versus simvastatin 40mg/d in individuals with acute coronary syndrome.
  112. 112. Markov health states Post HS Post HS Post HS Post HS Post HS Post HS QE: Hospitalisation unstable angina QE: New non-fatal MI QE: Revascularisation New non fatal MI New hospitalisation for unstable angina New non fatal stroke CVD Mortality Transitions from all health states Non CVD Mortality
  113. 113. Clinical Data Literature review: 28 RCTs > 12 week duration Benefit: LDL-c Synthesis: MTC Relationship: LDL-c & CV events
  114. 114. Mean Relative Risks (95% CI) Atorvastatin 80mg/d Rosuvastatin 40mg/d Simvastatin 40mg/d Simvastatin 80mg/d Non-fatal MI 0.425 (0.302 - 0.544) 0.378 (0.241 - 0.51) 0.588 (0.500 - 0.675) 0.510 (0.404 - 0.613) Non fatal stroke 0.623 (0.508 - 0.737) 0.593 (0.465 - 0.717) 0.730 (0.647 - 0.813) 0.679 (0.580 - 0.777) Stroke death 0.809 (0.429 - 1.242) 0.794 (0.384 - 1.261) 0.863 (0.593 - 1.173) 0.837 (0.516 - 1.206) CHD death 0.580 (0.445 - 0.715) 0.545 (0.397 - 0.692) 0.699 (0.601 - 0.796) 0.642 (0.527 - 0.758)
  115. 115. Adherence to therapies Scenario A Scenario B Yr 1 Yr 5 Yr 1 Yr 5 S40 ITT ITT ITT ITT A80 ITT ITT 95% 85% R40 ITT ITT 95% 85% S80 ITT ITT 95% 85%
  116. 116. Treatment costs Annual cost Sensitivity analyses Atorvastatin 80mg/d £368 £92 Rosuvastatin 40mg/d £387 Simvastatin 40mg/d £17 Simvastatin 80mg/d £34 Monitoring cost £76
  117. 117. Results Comparing with simvastatin 40mg/d: Atorvastatin 80mg/d Rosuvastatin 40mg/d Simvastatin 80mg/d Scenario A £17,469 £12,484 £5,319 Scenario B £17,217 £12,277 £5,226
  118. 118. Results – reduced cost for Atorvastatin simvastatin 40mg/d simvastatin 80mg/d atorvastatin 80mg/d rosuvastatin 40mg/d 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 £0 £5,000 £10,000 £15,000 £20,000 £25,000 £30,000 Threshold ratio Probabilitycosteffective
  119. 119. Summary & Conclusion • Rosuvastatin 40mg/d is currently the most cost- effective alternative • Atorvastatin 80mg/d is the most cost-effective (@ 25% of current price) • Simvastatin 80mg/d is not recommended Current PCT policies intended to minimise primary care drug acquisition costs result in sub-optimal treatment for patients with ACS
  120. 120. A cost-effectiveness model of prostate cancer screening Matthew Mildred, Jim Chilcott, Silvia Hummel ScHARR, University of Sheffield
  121. 121. 05/04/2011 © The University of Sheffield Contents • Introduction to the project and topic • Disease natural history model • Data and model calibration • Validation • Results • Conclusions
  122. 122. 05/04/2011 © The University of Sheffield The project • Client: UK National Screening Committee • Purpose: Help determine IF a national prostate cancer screening programme should occur AND which screening strategy is best. • Objectives: Estimate costs, benefits and resource implications of alternative screening options.
  123. 123. 05/04/2011 © The University of Sheffield Introduction to prostate cancer The prostate is a small gland in men behind the bladder. The most common cancer in men in UK (excluding non-melanoma skin cancer) In 2008: Over 37,000 men diagnosed Over 10,000 men died from prostate cancer
  124. 124. 05/04/2011 © The University of Sheffield Aim of screening: Reduce cancer mortality, morbidity and treatment costs through early diagnosis and intervention. Current evidence: In 2009 two large RCTs reported apparently inconsistent results in terms of the death rate ratio: • ERSPC – significant reduction in PCa death rate • PLCO – no statistically significant reduction
  125. 125. 05/04/2011 © The University of Sheffield Challenges: • Effectiveness of different screening programmes unknown. • Scarce data around disease process due to its unobservable nature. • Multiple unknown parameters in cancer screening model.
  126. 126. 05/04/2011 © The University of Sheffield Solution: • Develop loosely parameterised cancer screening simulation model. • Calibrate unobservable model parameters to observed data. • Estimate impact of prostate cancer screening using calibrated model.
  127. 127. 05/04/2011 © The University of Sheffield About the model: • Disease natural history model (Simul8) • Calibration module (Excel, Visual Basic) • Simulation model of prostate cancer screening (Simul8) • Resource impact model (Excel)
  128. 128. 05/04/2011 © The University of Sheffield Screening strategies investigated No. Screens Screening Age (years) Screening Interval (years) Single 50 N/A 55 60 65 70 Repeat 50-70 2, 4 50-74 1, 2, 4 55-70 2, 4 55-74 2, 4
  129. 129. 05/04/2011 © The University of Sheffield Outputs: • Age-specific incidence • Age-specific mortality • Prostate cancer stage distributions • Over-detection rate • Lead time • Life years gained, QALYs gained • Probability of developing prostate cancer • Etc...
  130. 130. 05/04/2011 © The University of Sheffield PCa Onset Screen Detection PCa Mortality Clinical Diagnosis Other Cause Mortality PCa Onset Screen Detection PCa Mortality Clinical Diagnosis Other Cause Mortality Lead-time Lead-time Over-detection: Relevant: Definitions & terms used
  131. 131. 05/04/2011 © The University of Sheffield Disease natural history model
  132. 132. 05/04/2011 © The University of Sheffield Data Data Source Age specific cancer incidence Office of National Statistics Cancer stage distributions ProtecT RCT UK Cancer Registry (ERIC) Gleason score distributions ProtecT RCT UK Cancer Registry (ERIC) PSA/biopsy test characteristics ERSPC RCT (Rotterdam section) Progression Free Survival ERSPC RCT (Rotterdam section) Overall Survival ERSPC RCT (Rotterdam section)
  133. 133. 05/04/2011 © The University of Sheffield Calibration process
  134. 134. 05/04/2011 © The University of Sheffield Total SSE during calibration
  135. 135. 05/04/2011 © The University of Sheffield Validation: Incidence
  136. 136. 05/04/2011 © The University of Sheffield Validation: PCa mortality
  137. 137. 05/04/2011 © The University of Sheffield Validation: BAUS
  138. 138. 05/04/2011 © The University of Sheffield Results: Incidence 0 2 4 6 8 10 12 14 16 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ PCaincidence(/1000yrs) Age band Noscreening Once at 50 50-74every 4 years 50-74every 2 years 50-74every year
  139. 139. 05/04/2011 © The University of Sheffield Results: Mortality 0 1 2 3 4 5 6 7 8 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Age band PCamortality(/1000yrs) No screening Once at 50 50-74 every4 years 50-74 every2 years 50-74 everyyear
  140. 140. 05/04/2011 © The University of Sheffield Over-detection & Lead time: Once at 50 50-74 every 4 years 50-74 every 2 years 50-74 every year Over- detection rate 18% 44% 45% 46% Lead time (for over- detected cases) 15.2 yrs 11.6 yrs 12.5 yrs 13.0 yrs
  141. 141. 05/04/2011 © The University of Sheffield Conclusions: A minimal life gain is offset by the high levels of disease management and over-diagnosis: • One off screening: life gain of 0.004 years (1.2 days) with 36 years of additional disease management • Repeat screening: life gain of 0.03 years (10-11 days) with 67-84 years of additional disease management
  142. 142. 05/04/2011 © The University of Sheffield Have you heard our findings? BBC News 06/12/2010 http://www.bbc.co.uk/news/health-11930979
  143. 143. 05/04/2011 © The University of Sheffield Acknowledgements: • Dr Anne Mackie and Prof Julietta Patnick at the UK National Screening Committee • The South West Public Health Observatory • The British Association of Urological Surgeons • The ProtecT team
  144. 144. Healthcare costs alone do not describe the total costs directly attributable to Ankylosing Spondylitis R. Ara1, R. Rafia1, J. C. Packham2,3, K L Haywood4, E.L. Healey2,4 1University of Sheffield, 2Staffordshire Rheum Centre, 3University of Warwick, 4Arthritis Research Campaign, Keele. 14/05/2014 © The University of Sheffield
  145. 145. Introduction Ankylosing Spondylitis (AS) is a chronic, progressive disease and prognosis is often poor. In addition to direct health care costs, AS is associated with substantial indirect costs due to privately funded health care, absenteeism from work and early retirement. 14/05/2014 © The University of Sheffield
  146. 146. Objectives • To explore the total costs directly attributable to AS patients attending rheumatological centres in the UK. • To explore the relationship between total costs and disease severity (classified using the Bath AS Disease Activity Index (BASDAI) and the Bath AS Functional Index (BASFI) variables) 14/05/2014 © The University of Sheffield
  147. 147. Methods Health care costs included: medications, inpatient, GP/ outpatient, physiotherapy, hydrotherapy Non medical indirect costs included: productivity losses (unemployment, early retirement, absenteeism, presenteeism) Productivity losses were assessed using human capital approach Absenteeism = number of days off sick (average 5 working days per week) Presenteeism = relative to age/gender adjusted gross pay & WLQ-16 Two-step model used to explore relationship between disease severity and costs using data collected at baseline 1: logistic regression for probability incurring cost 2: generalised linear model conditional on incurring any cost Performance of the estimated model tested on data collected at 6 months
  148. 148. Results (1) Healthcare Utilisation: 41% reported no health care resources 45% reported no NHS funded healthcare resources 26% reported ≥ 1 medication 71/162 received anti-TNF treatment 10 hospitalisations due to AS (mean duration 11 days) 215 reported ≥ 1 GP consultation Number consultations > for greater disease activity (1.7 vs 2.6) Number consultations > for non workers (2.8 vs 1.9) 19% ≥ 1 physiotherapy session (33% of these self funded) 11% ≥ 1 hydrotherapy session (46% of these self-funded) Number sessions > non workers (7.1 vs 13.1) Number sessions > for greater disease activity (7.0 vs 12.3) 14/05/2014 © The University of Sheffield
  149. 149. Results (2) Total Costs: The distribution of costs is heavily skewed with small number incurring high costs and substantial proportion incurring none. Average 3 month direct health care costs = £420 £988 (median = £27) Average 3 month total costs = £2,837 £3,358 (median = £1,228) £0 £1,000 £2,000 £3,000 £4,000 £5,000 £6,000 Moderate (score <4) Severe (4 = score < 6) Very severe (6 = score = 10) Patients subgroupedby BASDAI(BASFI) bands 3monthtotalcost BASFI mean cost BASDAI mean cost BASFI median cost BASDAI median cost Mean 3 month total costs sub-grouped by disease severity bands
  150. 150. Results (3) Absenteeism/ presenteeism 25% of working age reported not working or early retirement due to AS 25% (85/339) of workers reported time off sick 93% (315/339) of workers reported a reduction in productivity while at work Mean number of days off sick due to AS = 5.7 (range 1 – 62) Mean reduction in productivity at work = 20% (range = 1 – 90%) 14/05/2014 © The University of Sheffield
  151. 151. Results (4) Using BASDAI & BASFI to predict AS disease costs Model 1: Probability of incurring costs = 3.26106 +0.13308*BASFI + 0.27695*BASDAI – 0.01323*BASFI*BASDAI + 0.30472*male – 0.04869*age – 0.01171*disease duration Model 2: 3 month total costs, conditional on costs incurred = 6.89107 + 0.26335*BASFI + 0.12048*BASDAI - 0.01411*BASFI*BASDAI + 0.46456*male – 0.01679*age + 0.00364*disease duration £0 £1,000 £2,000 £3,000 £4,000 £5,000 £6,000 £7,000 - 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 BASDAI Score Indirectcosts Observed mean cost Predicted cost Actual and predicted total 3 month costs
  152. 152. Conclusion This study shows that direct healthcare costs alone do not describe the total costs associated with AS and that productivity losses associated with AS are considerable. Additional research examining interventions and measures that improve both presenteeism and absenteeism will have the largest affect on the cost to society. 14/05/2014 © The University of Sheffield
  153. 153. The direct healthcare resource costs associated with Ankylosing Spondylitis patients attending a UK secondary care rheumatology unit RM Ara1, JC Packham2, KL Haywood3 1University of Sheffield; 2Staffordshire Rheumatology Centre, Stoke on Trent; 3Royal College of Nursing Institute, Oxford, UK 14/05/2014 © The University of Sheffield
  154. 154. Introduction • Anti-TNF inhibitors such as etanercept (ETN), are now licensed for treating patients with severe Ankylosing Spondylitis (AS). • These treatments have larger cost implications than previously available therapies and comprehensive economic evaluations of these novel treatments in individual disease areas are increasingly requested by policy decision makers to inform reimbursement decisions. 14/05/2014 © The University of Sheffield
  155. 155. Objectives • To explore the direct healthcare resources utilised by AS patients attending a UK secondary care rheumatology unit to inform an economic evaluation of ETN in AS patients. • To establish if resources, and thus health care costs, vary by disease severity (as classified using the Bath AS Disease Activity Index (BASDAI) and the Bath AS Functional Index (BASFI) variables).
  156. 156. Methods Costs: • Costs were assessed using a micro-costing approach starting with a detailed inventory and measurement of resources consumed by the patient. • Unit cost multipliers were applied to the quantity of each type of resource consumed. • The mean cost per patient is estimated using the total cost divided by the total number of patients included. Resources included: • NHS physiotherapy, outpatient appointments; inpatient days, laboratory based tests (FBR, ESR, LFT, U&E), X- rays, scans, prescribed medications. 14/05/2014 © The University of Sheffield
  157. 157. Results (1) Mean Annual Disease Costs • The mean total annual costs is estimated to be £1,837 (s.d. = £2,764; median = £772). • The total annual costs range from £101 to £18,012 with an asymmetric distribution (just 11/147 patients have annual costs concentrated beyond £7,000). • The mean annual cost per patient is correlated with both measures of disease activity (BASDAI) and functional disability (BASFI) £0 £500 £1,000 £1,500 £2,000 £2,500 £3,000 £3,500 £4,000 <30 30-39 40-49 50-59 60-69 70+ Disease severity (disease activity (BASDAI)orfunctionaldisability (BASFI)) Meanannualcost £0 £500 £1,000 £1,500 £2,000 £2,500 £3,000 £3,500 £4,000 Medianannualcost BASDAImean annualcost BASFImean annualcost BASDAImedian annualcost BASFImedian annualcost BASDAI < 60 BASDAI > 60 BASFI < 60 BASFI > 60 Physiotherapy £281; 22% £1,575;45 % £123; 13% £1,547; 43% Hospitalisation £303; 23% £785; 23% £243; 26% £779; 22% Medication £315; 24% £479; 14% £225; 24% £615; 17% Outpatient/tests £397; 31% £668; 19% £351; 37% £688; 19% The mean annual costs by levels of disease activity and functional disability Mean (proportion) annual costs by resource type and disease severity
  158. 158. Results (2) Using BASDAI & BASFI to predict AS disease costs • Both the BASDAI and BASFI measurements were moderately correlated with the log transformed annual costs (Pearson correlation = 0.40 and 0.48 respectively; p < 0.001). • The model# with the best predictive ability was Annual direct costs = exp(0.006*BASDAI + 0.016*BASFI + 5.862) #Adj R2=0.24 hence BASDAI and BASFI only partially account for the variability in costs. • A 10 unit increase in both BASDAI and BASFI measurements incurs an increment of approximately £130 for scores of 40 and below; and an increment of approximately £480 for scores of 70 and above.
  159. 159. Discussion/Future Research • The results of this costing study give an indication of the range of direct healthcare costs associated with patients who have AS and are eligible for anti-TNF treatments in the UK. • Due to time constraints only readily accessible data such as clinical visits; inpatient care, technical procedures including radiographic examinations, prescribed medications, and physiotherapy appointments were included. • The study would benefit from inclusion of additional information such as the number of GP visits. • Further research into the most (cost)-effective provision of physiotherapy to patients with AS would be constructive. • As AS is a progressive debilitating disease, it may be appropriate to include non-medical resources such as aids and appliances or formal household care and paid productivity losses such as absence from paid work.
  160. 160. A treatment option for patients with severe active Ankylosing Spondylitis: the costs and benefits associated with etanercept RM Ara1, A Reynolds2, P Conway2 1University of Sheffield; 2Wyeth Pharmaceuticals, UK 14/05/2014 © The University of Sheffield
  161. 161. Introduction • Ankylosing Spondylitis (AS) is a progressive inflammatory disease that can cause irreversible skeletal damage. Typically presenting in young males, the long term prognosis is poor. High levels of pain and severe loss of physical function can have a large effect on health related quality of life (HRQoL). • The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Bath Ankylosing Spondylitis Functional Index (BASFI) are validated and established measures in AS patients.
  162. 162. Objective To explore the costs and benefits associated with etanercept (ETN) in patients with severe AS in the UK under the BSR criteria. 14/05/2014 © The University of Sheffield
  163. 163. Methods • The model (written in Excel 2003) estimates the costs and benefits associated with ETN (2x 25mg/week) plus NSAIDS compared with NSAIDs alone. • Effectiveness of ETN is based on patient level data obtained from two RCTs • Placebo data are used to inform the comparator (88% of patients received NSAIDS) • Effectiveness of treatment are measured by changes in BASDAI and BASFI at weeks 12 and 24 • Initial response is supported by three year open label data [6,7] • Direct healthcare costs associated with AS are obtained from a UK costing study and are estimated using the relationship [8] • Annual direct costs = exp(0.006*BASDAI + 0.016*BASFI + 5.862) • QoL data (EQ-5D) collected during the RCT are used to estimate quality adjusted life years (QALYS) using the relationship • Utility = 0.923 – 0.004*BASFI – 0.004*BASDAI • A 25 year time horizon is used to reflect the chronic progressive nature of AS and results are also presented for shorter horizons • Univariate sensitivity analyses are used to explore the impact of varying individual key parameters • Costs and benefits are discounted at 3.5% per annum
  164. 164. Assumptions • Natural disease progression: BASFI increases at 0.7 units per annum • For responders to ETN: BASDAI & BASFI measurements remain constant at values observed in RCTS • BASDAI & BASFI measurements revert to baseline values and follow natural disease progression after withdrawal from ETN • 10% annual withdrawal from ETN due to lack of efficacy/ adverse effects • Age and sex related life expectancy is adjusted using ratio of 1.5 and assumed equal in both arms 14/05/2014 © The University of Sheffield
  165. 165. Base case results 14/05/2014 © The University of Sheffield Time horizon (years) 2 5 15 25 ETN 1,185 2,646 5,739 7,285 Comp 817 1,831 4,286 5,700 Incremental 368 815 1,453 1,585 ETN £13,042 £26,390 £51,415 £62,517 Comp £2,890 £7,109 £18,596 £26,538 Incremental £10,152 £19,281 £32,819 £35,978 £27,594 £23,649 £22,580 £22,704 Total discounted QALYS Total discounted costs (£,000) Discounted incremental cost per QALY
  166. 166. Univariate sensitivity analyses The tornado diagram shows that the three variables that have the largest impact of the 25 year results are: • the values used to represent HRQoL • the annual withdrawal rates • the health care costs directly attributable to AS 14/05/2014 © The University of Sheffield £10,000 £15,000 £20,000 £25,000 £30,000 £35,000 Discount BASDAI/BASFI capped at 80 BASFI progression rate Disease costs Annual withdrawal Quality of Life CI Cost per QALY Tornado diagram showing the parameters which have the largest impact on the results
  167. 167. Monte Carlo results • Using a 25 year horizon and a £30k per QALY threshold, ETN would be considered a cost-effective treatment when compared to NSAIDs in individuals with severe AS. The corresponding cost effectiveness acceptability curve shows that ETN is 93% likely to be cost effective when using a £25k per QALY threshold. 14/05/2014 © The University of Sheffield £0 £10,000 £20,000 £30,000 £40,000 0.0 0.5 1.0 1.5 2.0 Incrementaleffectiveness Incrementalcosts year 25 yaer 15 yaer 5 year 2 £20,000 per QALYgained £30,000 per QALYgained Cost effectiveness plane ETN plus NSAIDs compared with NSAIDs
  168. 168. Areas for future research • Potential impact of radiological progression on long term disability • Efficacy of ETN in individuals with BASDAI < 40 • Strengthen relationship between BASDAI/BASFI and both costs and utilities • BASDAI & BASFI further explore the relationship to disease costs • Effect of ETN on early retirement • Develop prognostic algorithms to identify patients who would benefit the most from ETN • Quantify natural disease progression and disease progression for individuals responding to ETN
  169. 169. An economic evaluation of etanercept in the treatment of patients with psoriatic arthritis RM Ara and R Rafia ScHARR, University of Sheffield 14/05/2014 © The University of Sheffield
  170. 170. Introduction • Psoriatic Arthritis (PsA) is a chronic, progressive disease and prognosis is often poor. • Anti_TNF agents such as etanercept are effective alternatives for patients whose current treatment is symptomatic.
  171. 171. Objective • To explore the costs and benefits associated with etanercept in the treatment for patients with psoriatic arthritis to inform a NICE submission.
  172. 172. Methods • The model compares ciclosporin to anti-TNF agents (etanercept, adalimumab, infliximab) and it is assumed that patients have failed methotrexate and sulphasalazine prior entering the model. • Relationship between HAQ and costs associated with PsA and HAQ and health related quality of life are then used to estimate the long term costs and benefits accrued. • Treatment effectiveness was derived from a Mixed Treatment Comparison published in a previous STA. • Treatment discontinuation was modelled using PsARC response rate at 12 and/or 24 weeks using results from the MTC. Long term withdrawal rate was derived from data from a recent observational study conducted by the BSRBR. • A set of 27 univariate sensitivity analysis was performed to test the robustness of the model to main assumptions. • The overall uncertainty was examined using a Monte Carlo approach. • Costs and quality of life benefits were discounted at 3.5% per annum as per NICE recommandations for economic evaluation • The model was extended beyond the trial duration to a 50 years time horizon
  173. 173. Relationship between HAQ and HrQoL Relationship estimated from PRESTA trial for the base case: Utility (EQ-5D) = 0.8996 – 0.4559 * HAQ – 0.0010 * Age + 0.0201 * male + 0.0031 *Age * HAQ – 0.0388 * male * HAQ
  174. 174. Relationship between HAQ and Direct health care Costs • Health care costs include both primary and secondary care resources. • The relationship between HAQ and costs was examined using a Generalised Linear Model assuming a poison distribution and a log link: Cost = 3.5367 + 2.0484 * HAQ + 0.0260 * Age – 0.0119 * Age * HAQ £0 £1,000 £2,000 £3,000 £4,000 £5,000 £6,000 £7,000 <=1.2 1.2<=1.4 1.4<=1.6 1.6<=1.8 1.8<=2.0 2.0<=2.2 2.2<=2.4 2.4<=2.6 2.6<=2.8 HAQ band Costs Observed cost Predicted cost Actual and predicted annual cost by HAQ
  175. 175. Base case results MEAN QALY MEAN COST (£) ICER RESULTS AT 50YEARS (LIFETIME) ETN 6.90 £65,650 £12,480 ADALIMUMAB 6.54 £61,381 EXTENDEDLY DOMINATED BY ETN INFLIXIMAB 6.39 £66,867 DOMINATED BY ADL CICLOSPORINE 5.96 £53,860
  176. 176. Uncertainty in results • The model results were sensitive to both the magnitude of the rebound of HAQ after withdrawal from treatment, and annual HAQ progression rates, relationship between HAQ and QoL and discount rates. • Results from the PSA, demonstrate one is 65% confident that etanercept is a cost-effective strategy when using a threshold of £20,000 per QALY. 14/05/2014 © The University of Sheffield 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 20000 40000 60000 80000 100000 120000 Willingness To Pay (£) Probabilitycosteffective Etanercept Cyclosporine Infliximab Adalimumab Cost-Effectiveness- Acceptability Curve
  177. 177. Conclusion While this evaluation provides evidence on the potential cost-effectiveness of etanercept compared to other anti-TNF agents or ciclosporin for adults with PsA, there are limitations with the evidence based used to populate the model. 14/05/2014 © The University of Sheffield
  178. 178. Evidence Review and Synthesis 14/05/2014 © The University of Sheffield
  179. 179. Extensive experience of systematic review and evidence synthesis work for • National Institute for Health and Clinical Excellence (NICE), • NIHR Evaluation, Trials and Studies Coordinating Centre (NETSCC) • NICE Public Health Collaborating Centre (PHCC) • Multiple clients in industry. 14/05/2014 © The University of Sheffield
  180. 180. Systematic review of clinical evidence High quality systematic reviews for submissions to key reimbursement bodies or for publication • Clinical reviews • Critical appraisal of reviews • Review updates Other review methods • Mapping reviews • Reviews of model parameters • Rapid reviews • Research reports 14/05/2014 © The University of Sheffield
  181. 181. Generalised evidence synthesis Classical and Bayesian meta analysis, including network meta analysis • RCTs • Observational studies • Diagnostic studies • Qualitative studies (meta synthesis) • Mixed methods
  182. 182. Examples of Systematic reviews conducted in HEDS 14/05/2014 © The University of Sheffield
  183. 183. PET and MRI for the assessment of axillary lymph node metastases in early stage breast cancer A Systematic review Susan Harnan Research Associate ScHARR, University of Sheffield Email: s.harnan@sheffield.ac.uk 14/05/2014 © The University of Sheffield
  184. 184. Background • Axillary staging is important for breast cancer staging and treatment planning • Current techniques include • Axillary lymph node dissection (ALND) • Sentinel lymph node biopsy (SLNB) • Sampling techniques such as four node sampling (4- NS) • All these procedures (ALND, SLNB and 4-NS) have short and long term adverse effects such as lymphoedema 14/05/2014 © The University of Sheffield
  185. 185. Diagnostic pathway • NICE diagnostic pathway *Either fine needle aspiration cytology (FNAC) or core biopsy. • Positron emission tomography (PET) and magnetic resonance imaging (MRI) may offer alternatives with fewer adverse events • Could replace SLNB/4-NS • Or be added to the pathway 14/05/2014 © The University of Sheffield
  186. 186. HTA report • National Institute for Health Research Health Technology Assessment (HTA) programme commissioned research to evaluate PET and MRI: • Diagnostic accuracy • Cost-effectiveness • Patient outcomes • Work carried out by ScHARR: Katy Cooper, Yang Meng, Sue Harnan, Sue Ward, Patrick Fitzgerald, Diana Papaioannou • With clinical advisers: Lynda Wyld, Christine Ingram, Iain Wilkinson, Eleanor Lorenz 14/05/2014 © The University of Sheffield
  187. 187. Methods • Searched eleven databases • Inclusion criteria: • Assessed diagnostic accuracy of PET or MRI for assessment of axillary metastases in patients newly diagnosed with early-stage invasive primary breast cancer • PET studies only included if ≥ 20 patients • Studies with > 20% non-early stage, non- newly diagnosed or DCIS were excluded. • Quality Assessment of Diagnostic Accuracy Studies (QUADAS) checklist used. 14/05/2014 © The University of Sheffield
  188. 188. Diagnostic accuracy studies • Patients are classified against a reference standard (eg ALND or SLNB) as true positive, true negative, false positive or false negative • Sensitivity is % of positive patients correctly identified • Specificity is % of negative patients correctly identified • Studies only included if TP, TN, FP and FN were reported or could be calculated. • Bivariate random effects model used to meta-analyse data as sensitivity and specificity are linked.
  189. 189. Results 14/05/2014 © The University of Sheffield
  190. 190. PET results • Quality generally acceptable, though some problems with patient spectrum, blinding, availability of relevant clinical information and reporting of uninterpretable results. • 26 studies of PET or PET/CT 14/05/2014 © The University of Sheffield
  191. 191. PET results – forest plots PET/CT Study Chae 2009 Heusner 2009 Kim 2009 Taira 2009 Fuster 2008 Ueda 2008 Veronesi 2007 TP 16 13 27 13 14 34 38 FP 12 3 0 5 0 6 5 FN 17 9 8 14 6 25 65 TN 63 29 102 60 32 118 128 Sensitivity 0.48 [0.31, 0.66] 0.59 [0.36, 0.79] 0.77 [0.60, 0.90] 0.48 [0.29, 0.68] 0.70 [0.46, 0.88] 0.58 [0.44, 0.70] 0.37 [0.28, 0.47] Specificity 0.84 [0.74, 0.91] 0.91 [0.75, 0.98] 1.00 [0.96, 1.00] 0.92 [0.83, 0.97] 1.00 [0.89, 1.00] 0.95 [0.90, 0.98] 0.96 [0.91, 0.99] Sensitivity 0 0.2 0.4 0.6 0.8 1 Specificity 0 0.2 0.4 0.6 0.8 1 PET only Study Cermik 2008 Gil-Rendo 2006 Weir 2005 Agresti 2004 Fehr 2004 Inoue 2004 Lovrics 2004 Wahl 2004 Barranger 2003 Guller 2002 Nakamoto 2002 Rieber 2002 van der Hoeven 2002 Greco 2001 Noh 1998 Smith 1998 Adler 1997 Avril 1996 Utech 1996 TP 34 120 5 20 2 21 9 66 3 6 6 16 8 68 14 13 16 19 44 FP 11 2 3 3 1 2 2 40 0 1 1 1 1 13 0 1 6 0 20 FN 39 22 13 11 8 14 16 43 12 8 7 4 24 4 1 2 4 5 0 TN 104 131 19 37 13 44 63 159 17 16 16 19 37 82 12 22 26 17 60 Sensitivity 0.47 [0.35, 0.59] 0.85 [0.77, 0.90] 0.28 [0.10, 0.53] 0.65 [0.45, 0.81] 0.20 [0.03, 0.56] 0.60 [0.42, 0.76] 0.36 [0.18, 0.57] 0.61 [0.51, 0.70] 0.20 [0.04, 0.48] 0.43 [0.18, 0.71] 0.46 [0.19, 0.75] 0.80 [0.56, 0.94] 0.25 [0.11, 0.43] 0.94 [0.86, 0.98] 0.93 [0.68, 1.00] 0.87 [0.60, 0.98] 0.80 [0.56, 0.94] 0.79 [0.58, 0.93] 1.00 [0.92, 1.00] Specificity 0.90 [0.84, 0.95] 0.98 [0.95, 1.00] 0.86 [0.65, 0.97] 0.93 [0.80, 0.98] 0.93 [0.66, 1.00] 0.96 [0.85, 0.99] 0.97 [0.89, 1.00] 0.80 [0.74, 0.85] 1.00 [0.80, 1.00] 0.94 [0.71, 1.00] 0.94 [0.71, 1.00] 0.95 [0.75, 1.00] 0.97 [0.86, 1.00] 0.86 [0.78, 0.93] 1.00 [0.74, 1.00] 0.96 [0.78, 1.00] 0.81 [0.64, 0.93] 1.00 [0.80, 1.00] 0.75 [0.64, 0.84] Sensitivity 0 0.2 0.4 0.6 0.8 1 Specificity 0 0.2 0.4 0.6 0.8 1
  192. 192. PET sensitivity analyses
  193. 193. MRI results • Quality generally good. Some problems with patient spectrum, availability of relevant clinical information and uninterpretable results. • Small numbers, different methods • Nine studies of MRI, meta-analysed using highest reported sensitivity and specificity from each study
  194. 194. MRI results – forest plot 14/05/2014 © The University of Sheffield USPIO-enhanced MRI Study Kimura 2009 Harada 2007 Memarsadeghi 2006 Stadnik 2006 Michel 2002 TP 2 23 6 5 9 FP 0 2 0 1 0 FN 0 0 0 0 2 TN 8 8 16 4 7 MRI criteria USPIO uptake USPIO uptake USPIO uptake USPIO uptake USPIO + >10mm + round Sensitivity 1.00 [0.16, 1.00] 1.00 [0.85, 1.00] 1.00 [0.54, 1.00] 1.00 [0.48, 1.00] 0.82 [0.48, 0.98] Specificity 1.00 [0.63, 1.00] 0.80 [0.44, 0.97] 1.00 [0.79, 1.00] 0.80 [0.28, 0.99] 1.00 [0.59, 1.00] Sensitivity 0 0.2 0.4 0.6 0.8 1 Specificity 0 0.2 0.4 0.6 0.8 1 Gadolinium-enhanced MRI Study Mumtaz 1997 TP 36 FP 6 FN 4 TN 29 MRI criteria Gd uptake + >5mm Sensitivity 0.90 [0.76, 0.97] Specificity 0.83 [0.66, 0.93] Sensitivity 0 0.2 0.4 0.6 0.8 1 Specificity 0 0.2 0.4 0.6 0.8 1 Dynamic gadolinium-enhanced MRI Study Murray 2002 Kvistad 2000 TP 10 20 FP 17 4 FN 0 4 TN 20 37 MRI criteria Dynamic Gd + >4sq-mm Dynamic Gd Sensitivity 1.00 [0.69, 1.00] 0.83 [0.63, 0.95] Specificity 0.54 [0.37, 0.71] 0.90 [0.77, 0.97] Sensitivity 0 0.2 0.4 0.6 0.8 1 Specificity 0 0.2 0.4 0.6 0.8 1 MR spectroscopy (in vivo) Study Yeung 2002 TP 11 FP 0 FN 6 TN 10 MRI criteria MR spectroscopy (in vivo) Sensitivity 0.65 [0.38, 0.86] Specificity 1.00 [0.69, 1.00] Sensitivity 0 0.2 0.4 0.6 0.8 1 Specificity 0 0.2 0.4 0.6 0.8 1
  195. 195. MRI results • Criteria for positivity varied across studies, including variables of size, morphology and uptake. Uptake pattern appeared to give better combined sensitivity and specificity. Sensitivity analyses • Sensitivity analyses for size and nodal status not possible as these were not reported • Lower specificity and a trend towards higher sensitivity was seen for studies with only early-stage, newly- diagnosed non-DCIS patients, but wide range. • Study quality did not affect estimates (note small sample, little variation in scores) 14/05/2014 © The University of Sheffield
  196. 196. Adverse effects • No adverse effects were reported for PET • Mild to moderate adverse effects reported for MRI include mild rash following USPIO administration, claustrophobia and back pain. • Cautions and contraindications exist for both including pregnancy (PET), allergy to contrast agents, renal and liver dysfunction, pacemakers, metallic implants (MRI). 14/05/2014 © The University of Sheffield
  197. 197. Discussion • PET, PET-CT and MRI have lower sensitivity and specificity than ALND, SLNB and 4-NS • PET and PET-CT are similar to ultrasound in terms of sensitivity and specificity, MRI is slightly higher. • MRI has higher sensitivity than PET or PET-CT, but similar specificity. • USPIO-enhanced MRI gave highest estimates of sensitivity and specificity, but these are based on a small number of studies • All results vary widely between studies and caution should be taken when interpreting results 14/05/2014 © The University of Sheffield
  198. 198. Discussion (2) • Based on these estimates, if PET or MRI are used to replace SLNB/4-NS in the diagnostic pathway, more women will be at greater risk of recurrence or metastatic spread (false negatives) and more women will undergo ALND unnecessarily (false positives) • However PET and MRI have few adverse effects and much fewer women would undergo SLNB/4-NS and be at risk of the long term problems associated with them. • Decision modeling is needed for overall evaluation of benefits and harms. • Decision modeling will help evaluate the effects if PET or MRI are used in addition to SLNB/4-NS in the diagnostic pathway. 14/05/2014 © The University of Sheffield
  199. 199. PET results – ROC plot 14/05/2014 © The University of Sheffield All PET studies, showing ROC curve (solid line), mean sensitivity/specificity (black spot) and 95% confidence region (dashed ellipse)
  200. 200. MRI results – ROC plot 14/05/2014 © The University of Sheffield All MRI studies, showing ROC curve (solid line), mean sensitivity/specificity (black spot) and 95% confidence region (dashed ellipse)
  201. 201. Systematic reviews of relevant data Myfanwy Lloyd Jones Senior Research Fellow ScHARR, University of Sheffield Email: m.lloydjones@sheffield.ac.uk
  202. 202. More specifically • Drawing on the experience of the pilot diagnostics project, how do systematic reviews of diagnostic interventions differ from systematic reviews of therapeutic interventions, when both are undertaken to inform NICE decision-making? • Review question • PICO(S) components • Meta-analysis 14/05/2014 © The University of Sheffield
  203. 203. The review question • Is there a bigger difference between the overall project question and the question that forms the focus of the systematic review of clinical effectiveness in an assessment of a diagnostic intervention than in an assessment of a therapeutic intervention? • Therapeutic intervention: strontium ranelate TAR (2005) 14/05/2014 © The University of Sheffield
  204. 204. Therapeutic intervention Research question defined in the protocol: • To establish the clinical and cost effectiveness of strontium ranelate for the prevention of osteoporotic fractures in postmenopausal women with osteoporosis Systematic review of clinical effectiveness: • What is the clinical effectiveness of strontium ranelate for the prevention of osteoporotic fractures in postmenopausal women with osteoporosis, with or without prior fracture? 14/05/2014 © The University of Sheffield
  205. 205. In PICOS terms • Population: postmenopausal women with osteoporosis, with or without prior fracture • Intervention: strontium ranelate • Comparator: placebo/no treatment; specified active treatments if evidence available • Outcomes: • Principal: incident fractures (vertebral & nonvert) • Secondary: adverse effects, health-related quality of life etc • Study design: RCTs 14/05/2014 © The University of Sheffield