CHAIR: Job van Boven
DATE: Saturday 9th September 2017
VENUE: Melia Milano Hotel, Via Masaccio 19,
1) Update on the current project ‘Improve understanding of the bi-
directional causality relationship between asthma outcomes and
2) Ideas for future projects
- Are they still relevant, feasible, valid and a priority
3) New REG projects that include an adherence component
4) Any new project ideas?
1) Update on current project
Improve understanding of the bi-directional causality
relationship between asthma outcomes and adherence
1) To what extent and in what context adherence may be
considered an asthma outcome, or/and a predictor of
i.e. What is the impact of adherence, and change in adherence, on
asthma outcomes, and vice versa?.
2) Clinically meaningful adherence and outcomes thresholds
will be explored by treating them as continuous variables
and estimating linear/nonlinear relationships and
meaningful cut-off points.
Phase I study has been published
Souverein et al. (2017) J Allergy Clin Immunol Pract. 5(2): 448-456
Adherence - outcomes
Gap: 60 days
Interval: 110 days
Gap: 100 days
Interval: 50 days
Interval: 100 days
New approach – per-prescription-interval
Note: possible carry-over not illustrated in this figure
Select homogeneous intervals to be most accurate in
estimating bidirectional relation adherence – asthma control
Focus on variation in implementation:
- exclude gap intervals (0% adherence) (15%)
- exclude intervals with 100% adherence (60%)
(+ sensitivity analyses performed with binary 0/rest & 100/rest)
Include only intervals with range of adherence (4-99.6%)
94,498 intervals (10,472 patients) 24,102 intervals (7,501 patients)
- control: 11,509 (92.7%) of intervals with RDAC=1; 5,882
(56.2%) patients with RDAC=1 during follow-up
- adherence: 65.2% (SD=19.7)
Phase 2. Adherence - outcomes
Interval level SABA overuse within interval (ref=no) 0.98 (0.75-1.27)
SABA overuse lagged (ref=no) 0.96 (0.75-1.22)
Adherence within interval 1.01 (1.00-1.01)**
Adherence lagged 1.00 (1.00-1.00)
Patient level Age 1.00 (0.99-1.00)
Gender (ref=female) 1.58 (1.34-1.87)***
BMI (ref=underweight (<18.5)) normal (18.5-25) 1.08 (0.57-2.07)
overweight (25-30) 1.08 (0.56-2.09)
obese (≥30) 0.90 (0.46-1.77)
Smoking history (ref=current) none 1.47 (1.15-1.89)**
former 1.61 (1.18-2.19)**
Deprivation (ref=Q1 most affluent) Q2 1.21 (0.83-1.77)
Q3 1.26 (0.84-1.88)
Q4 1.27 (0.85-1.90)
Q5 (most deprived) 1.08 (0.70-1.66)
Diagnosed with (ref=no) rhinitis 0.74 (0.45-1.21)
allergic rhinitis 1.02 (0.74-1.39)
hay fever 0.99 (0.69-1.44)
gastroesophageal reflux 0.68 (0.41-1.12)
COPD 0.52 (0.35-0.78)**
other respiratory diseases 0.33 (0.10-1.05)
Asthma duration 1.00 (1.00-1.01)
CCI (ref=low (≤4)) 0.65 (0.50-0.85)**
Type of ICS device (ref=DPI) MDI 0.87 (0.61-1.24)
BAI 1.48 (0.57-3.90)
Doses in the device 1.00 (0.99-1.00)*
Daily dose 1.07 (1.00-1.15)*
Phase 2: adherence - outcomes
Same Occurrence of ≥1: (ref=no) Asthma-related hospitalizations -0.20 (12.0)
Respiratory-related hospitalizations -8.40 (11.2)
Asthma-related hospitalizations &
Prescriptions of acute OCS -5.0 (9.0)
Prescription of antibiotics -1.77 (0.64)**
Asthma-related outpatient visits -2.32 (1.17)*
Moderate to severe exacerbations 3.04 (8.99)
SABA overuse (ref=no) -6.68 (0.42)*** -6.69 (0.42)***
Risk domain asthma control (ref=no) 2.18 (0.46)**
Previous Occurrence of ≥1: (ref=no) Asthma-related hospitalizations 0.41 (10.4)
Respiratory-related hospitalizations -2.80 (9.55)
Asthma-related hospitalizations &
Prescriptions of acute OCS -6.32 (7.77)
Prescription of antibiotics -0.97 (0.64)
Asthma-related outpatient visits -1.34 (1.19)
Moderate to severe exacerbations 6.21 (7.79)
SABA overuse (ref=no) -1.22 (0.44)** -1.21 (0.44)**
Risk domain asthma control (ref=no) -0.25 (0.46)
Phase 2: outcomes – adherence
Phase 2 – preliminary conclusions
• Control is weakly associated with higher adherence
during the same interval between 2 prescriptions
• No lagged effects of adherence on control
• Lower adherence is associated with antibiotic use,
outpatient visits, and reliever overuse in the same
• No lagged effects of control (markers) on adherence.
Reliever overuse in preceding interval is predictive of
lower adherence in the next
Phase 2 – limitations
• The control-related event could have happened at the
beginning, middle or end of the interval – adherence is
assumed stable across the interval
moderator variable time of event within interval?
• 100% and 0% adherence intervals are artificially defined
based on pre-defined permissible treatment gap and by
censoring at the end of the 2-year period.
gap may be too short?
• No separation of variance between- and within-patient levels
person-centering may clarify effects?
Phase 2 – next steps
• Results to share with scientific committee for
• Discussion of possible publication of findings
• Different methodological approaches to test in the future:
o Selection of subsamples (type of ICs, >2000 only)
o Solutions for considering both persistence and implementation
o Testing of different permissible gap values
2) Current ideas for future studies
• Using Pharmacy data to validate adherence measures
calculated using UK Prescribing data
• Technology-based pragmatic trial grant that would provide an
online video inhaler training service.
Are they still relevant, feasible, valid and a priority?
3) New REG projects that include an
1) Device optimisation for improved adherence and outcomes
(Novartis funded study)
2) Child age dependent changes in adherence and associated
outcomes. (Child Health WG)
Device optimization for improved
adherence and outcomes
(Novartis funded study)
Phase 1 - Develop a standard setting piece by means of a Delphi
exercise to identify and detail what all new types of technologies must
do/gather in order to deliver relevant and necessary information.
Phase 2 - Study design that could be used to test all new technologies/
combination of technologies.
Development of a digital algorithm to predict/detect exacerbations.
Possible questions to address include
- How does adherence change with a child’s age?
- What outcomes are associated with different adherence patterns/phenotypes?
- What predicts a change in year-on-year adherence?
Many of these questions will be relevant to adults with asthma and other
chronic respiratory conditions, and a multidisciplinary and pan–REG
approach could be very productive and lead to improved patient care.
Child age dependent changes in
adherence and associated outcomes.
(Child Health WG)
3) Any new project ideas?
REG research needs that involve adherence-
NEED 7. To improve understanding of medication adherence behaviours
(including inhaler device challenges) in respiratory and allergic airways disease,
their implications on clinical and health economic outcomes and optimised
NEED 1. To characterise current routine care disease epidemiology and burden
for respiratory, allergic and obstructive airways disease outcomes
NEED 2. To characterise current routine care prescribing practices (diagnostic
and management) and their implications for respiratory and allergic airways
• Are the previous project ideas still:
o A priority?
• How do we set priorities in adherence?
• How to we ensure these priorities are pursued?
• What are the two most important projects to push forwards?