When a new drug enters the market, comparative effectiveness evidence is often comprised solely of evidence from the randomized clinical trials (RCTs) which led to regulatory agency approval. Older adults are major consumers of drugs and other therapeutics and underrepresented in randomized clinical trials. During the critical early period after a new drug enters the market, evidence from RCTs may not reflect the average experience for the types of patients actually treated and there is insufficient accrual of ?real world? experience in longitudinal healthcare databases for robust evidence generation. At this critical juncture, combining evidence can enhance understanding of net benefit of new drugs in the older, sicker populations who are actually treated in practice. However, appropriate methods for integrating pre-market RCT and early post-market comparative effectiveness evidence to guide clinical practice have not yet been identified. We will explore these issues in three case studies. For each case study, we will obtain individual level data from pre-market RCTs and create observational cohorts comprised of initiators of the new drug and comparator using Medicare data. We will evaluate different methods which combine evidence generated from RCT with ?real world? evidence from data observed in routine care of older adults in Medicare during early as well as later post-market experience with the new drugs. These methods include complex weighting as well as cross-design synthesis methods that combine information from RCT and ?real world? data. Specifically we will research: (1) How can innovative application of methods to combine individual-level data from pre-market RCTs and early post-market observational data accelerate understanding of effectiveness and safety of new to market medications in older patients who are typically underrepresented in RCTs? (2) How can we evaluate and understand reasons for differences in treatment effect estimates from pre-market RCTs and observational data in the early post-market time period? This project will produce a framework for combining pre-market RCT and early post-market evidence as a means to accelerate understanding of treatment effectiveness in older adults with multiple comorbidities. Use of this framework will provide early insights and clinical guidance to geriatricians on use of new drugs in their patients shortly after market entry. Because the methods used in this project are designed to provide early evidence that reflect average effectiveness in the types (and subtypes) of patients actually treated as part of routine care as opposed to average effectiveness in participants of a trial, the impact of this project will be particularly profound for new medications that target older, sicker patients typically underrepresented in trials.

Public Health Relevance

This project will produce a framework for combining pre-market RCT and early post-market evidence as a means to accelerate understanding of treatment effectiveness in older adults with multiple comorbidities. Use of this framework will provide early insights and clinical guidance to geriatricians on use of new drugs in their patients shortly after market entry. The impact of this project will be particularly profound for new medications that target older, sicker patients typically underrepresented in trials.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG053302-03
Application #
9908033
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Salive, Marcel
Project Start
2018-08-01
Project End
2022-04-30
Budget Start
2020-05-01
Budget End
2021-04-30
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Wang, Shirley V; Gagne, Joshua J; Glynn, Robert J et al. (2013) Case-crossover studies of therapeutics: design approaches to addressing time-varying prognosis in elderly populations. Epidemiology 24:375-8