1. Know Your Patients:
Why a registry alongside your observational
claims and Electronic Health Records
research may be crucial
Billy Franks, PhD
Director HECOR Statistics
Astellas Scientific and Medical Affairs, Inc.
September 18, 2014
2. Disclaimer
The presenter is a paid employee of Astellas.
The opinions and positions presented today are
my own and do not necessarily reflect those of
Astellas or any of its affiliate companies or
entities.
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3. Outline
• Apples-to-Apples (sequences & combinations)
• Impact of sequencing or combinations on
claims/EHR comparisons
• Illustrative Example
• Registries should complement your Big Data
strategy
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4. Comparative Effectiveness Research
AHRQ – “[CER] is designed to inform health-care decisions by
providing evidence on the effectiveness, benefits, and harms of
different treatment options.”
Two named sources:
…all of the available evidence about the benefits and harms of
each choice for different groups of people from existing
clinical trials, clinical studies, and other research. These are
called research reviews, because they are systematic reviews
of existing evidence.
…conduct studies that generate new evidence of
effectiveness or comparative effectiveness of a test,
treatment, procedure, or health-care service.
http://effectivehealthcare.ahrq.gov/index.cfm/what-is-comparative-effectiveness-research1/ 4
5. Apples-to-Apples
AHRQ – “The magnitude of potential confounding generally is expected to be
smaller when the comparator (1) has the same indication, (2) has similar
contraindications, (3) shares the same treatment modality (e.g., tablet or
capsule), and (4) has similar adverse effects.”
This guidance fails to warn the user of the implications of bias due to:
• Sequencing of therapies
– Guidelines
– Insurance Step Therapy Programs/Bundles
– Standard of Care
• Combination Therapy vs. Monotherapy Comparisons
(Brief mention on pg. 54 with regards to complexity of inference)
AHRQ - Developing a Protocol for Observational Comparative Effectiveness Research 5
6. Sequencing and Combination Therapy
• What may inform the sequence of therapies?
– Cost – least expensive option first, more expensive alternatives later
– Tolerability – perceived tolerability profile and/or patient characteristics, try alternatives
for lack of tolerability
– Efficacy – perceived efficacy profile and/or patient characteristics, try alternatives for
lack of response
• What may inform the use of combination therapy?
– Lack of efficacy of initial monotherapy regimen
– Severity of disease upon diagnosis or suspected condition
– Uncertainty of diagnosis
Given the above possible rationales for sequencing of therapies/combination
therapies, which would you be able to account for in CER when using data
commonly available in a claims data source? In a robust EHR data source?
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7. Type 2 Diabetes Guidelines (2014)
Pharmacological Therapy for Hyperglycemia in Type 2 Diabetes
• Metformin, if not contraindicated and if tolerated, is the preferred initial
pharmacological agent for type 2 diabetes.
• In newly diagnosed type 2 diabetic patients with markedly symptomatic and/or
elevated blood glucose levels or A1C, consider insulin therapy, with or without
additional agents, from the outset.
• If noninsulin monotherapy at maximum tolerated dose does not achieve or
maintain the A1C target over 3 months, add a second oral agent, a glucagon-like
peptide 1 (GLP-1) receptor agonist, or insulin.
• Patient-centered approach should be used to guide choice of pharmacological
agents. Consider efficacy, cost, side effects, effects on weight, comorbidities,
hypoglycemia risk, and patient preferences.
• Due to the progressive nature of type 2 diabetes, insulin therapy is eventually
indicated for many patients with type 2 diabetes.
http://care.diabetesjournals.org/content/37/Supplement_1/S5.full.pdf+html 7
8. Type 2 Diabetes Guidelines (2014)
Pharmacological Therapy for Hyperglycemia in Type 2 Diabetes
• Metformin, if not contraindicated and if tolerated, is the preferred initial
pharmacological agent for type 2 diabetes. (Efficacy – Sequence)
• In newly diagnosed type 2 diabetic patients with markedly symptomatic and/or
elevated blood glucose levels or A1C, consider insulin therapy, with or without
additional agents, from the outset. (Efficacy – Combination)
• If noninsulin monotherapy at maximum tolerated dose does not achieve or
maintain the A1C target over 3 months, add a second oral agent, a glucagon-like
peptide 1 (GLP-1) receptor agonist, or insulin. (Efficacy – Sequence to Combination)
• Patient-centered approach should be used to guide choice of pharmacological
agents. Consider efficacy, cost, side effects, effects on weight, comorbidities,
hypoglycemia risk, and patient preferences. (Tolerability + Efficacy + Cost)
• Due to the progressive nature of type 2 diabetes, insulin therapy is eventually
indicated for many patients with type 2 diabetes. (Efficacy – Combination)
http://care.diabetesjournals.org/content/37/Supplement_1/S5.full.pdf+html 8
9. Sample FDA Labeled Indications
• Metformin – “as monotherapy are indicated as an adjunct to diet and
exercise to improve glycemic control in patients with type 2 diabetes…
…Metformin may be used concomitantly with a sulfonylurea to improve
glycemic control in adults”
• Glipizide (sulfonylurea class) – “as an adjunct to diet and exercise to
improve glycemic control in adults with type 2 diabetes mellitus”
• Repaglinide (Meglitinide class)– “as an adjunct to diet and exercise to
improve glycemic control in adults with type 2 diabetes mellitus”
• Rosiglitazone Maleate (Thiazolidinediones class) – “as an adjunct to diet
and exercise to improve glycemic control in patients with type 2 diabetes
mellitus… …monotherapy… …combination with sulfonylurea, metformin,
or insulin [due to failure on maximum dose monotherapy with
sulfonylurea or metformin]… …combination with a sulfonylurea plus
metformin”
• Pioglitazone Hydrochloride (Thiazolidinediones class) – “as an adjunct to
diet and exercise to improve glycemic control in adults with type 2
diabetes mellitus in multiple clinical settings”
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10. Big Data Example – Type 2 Diabetes
• DARTNet – “advance observational comparative effectiveness research
(OCER) methods… …by providing a way to account for important clinical
information that is missing from claims databases [LABS and EHR].”
• Type 2 Diabetes medications - “retrospective cohort study that evaluated
patterns of use, comparative effectiveness, and safety”
• “Phase 1 used a commercially available, integrated medical claims
database to examine the comparative effectiveness and safety of oral
diabetes medications.”
• “Phase 2 used DARTNet data for the same purpose… [with] clinically-
relevant data such as body weight, height, self-reported alcohol intake,
and self-reported hypoglycemic events, which were absent in the claims
database [along with H-A1C].”
http://effectivehealthcare.ahrq.gov/index.cfm/search-for-guides-reviews-and-
reports/?productid=317&pageaction=displayproduct
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11. Results
• 100,000 subjects for utilization and safety and 14,000 subjects for effectiveness
• 80% initiated on monotherapy, 20% initiated on combination therapy
Lack of DM symptoms and glucose
• Persistence differed across specific monotherapy and combination therapy groups.
Biguanides or TZDs had greater persistence than other monotherapies; sulfonylurea
(SU)+biguanides or biguanides+TZDs had greater persistence than other combinations.
No comparisons between monotherapy and combination therapies
• Unadjusted reductions in Hemoglobin A1C (H-A1C) were similar to previous findings: 1%
(single therapy), 2% (two), and 2.6% (three).
Adjusted model showed smaller effect sizes. Was severity really accounted?
• Multivariate modeling showed slight differences across individual ODM drugs or
combinations in comparison to metformin monotherapy
Multivariate models which should account for severity failed to find relevant differences?
• Associated factors with greater H-A1C reduction: propensity score, persistence and
compliance, baseline H-A1C, and number of diabetes-related MD and education visits.
Shouldn’t significant propensity with equal outcomes imply effectiveness?
http://effectivehealthcare.ahrq.gov/ehc/products/53/151/2009_0728DEcIDE_DARTNet.pdf 11
12. Why Registries Can Complement Your
Big Data Strategy
• Registries
– Sponsored/Public
– Assess important questions typically at standardized time
points (PROs, efficacy, safety, exposure, rationale for
treatment choices)
– May collect novel or uncommon data (e.g. labs, genomic
data)
– May allow for prospective queries directly to participants
– Should be designed to capture known confounders
– Possibly improved longitudinality
– Could enrich available data for rare populations/diseases
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14. Public Registry Example:
Diabetes Collaborative Registry
• Announced June 2014
• Seeks to address a multitude of related conditions and
outcomes:
– cardiovascular disease
– kidney disease
– nerve damage
– amputation
– blindness
• Incorporating patients from the PINNACLE Registry®
(American College of Cardiology) ≈ 2.1 million patients
• Will leverage electronic medical records from:
– primary care physicians, endocrinologists, cardiologists and
other diabetes care providers
http://www.cardiosource.org/news-media/publications/cardiology-magazine/2014/06/first-clinical-diabetes-registry-to-
provide-seamless-view-of-diabetes-patients-across-specialties.aspx
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15. Sponsored Example:
Long-Term Non-Interventional Latanoprost
Study (LYNX)
• Dec 2010 – January 2016
• Seeks to collect long-term outcomes in pediatrics treated with Latanoprost
assessed at scheduled time points (baseline, 6, 12, 24, and 36 months):
– Best corrected visual acuity
– Refractive error
– Horizontal corneal diameter
– Intraocular pressure
– Optic nerve changes/structures
– Visual field
– Iris color darkening
– Other
• How many of these endpoints would be found in even the most robust
EHR databases given these would be observed by an optometrist?
Pfizer - http://clinicaltrials.gov/show/NCT01265719 15
16. Conclusion
• Registries should be considered as part of your
RWE strategy to complement Big Data research
• Registries cannot replace claims/EHR due to
limited size, limits on broad applicability, and
frequent lack of economic data
• Consider the implications of sequencing and
combination therapy in defining the scope of or
methodology for therapy comparisons
• Ensure you are ready to address external
research activities which may include your
therapy in a disadvantaged comparison
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