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Generalizing Randomized Clinical Trial Results: Implementation and Challenges Related to Missing Data in the Target Population
Author(s) -
JinLiern Hong,
Michele Jönsson Funk,
Robert LoCasale,
Sara E. Dempster,
Stephen R. Cole,
Michael WebsterClark,
Jessie K. Edwards,
Til Stürmer‎
Publication year - 2017
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwx287
Subject(s) - rosuvastatin , missing data , population , medicine , confidence interval , randomized controlled trial , generalizability theory , clinical trial , statistics , mathematics , environmental health
Statins are indicated in patients with elevated levels of high-sensitivity C-reactive protein and normal low-density lipoprotein cholesterol based on results of the multicountry trial, Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) (2003-2008), but the benefit in real-world populations remains unknown. We sought to generalize JUPITER results to trial-eligible population using data from the UK Clinical Practice Research Datalink (CPRD), 2001-2014. We multiply imputed missing baseline characteristics for the CPRD population and selected the trial-eligible participants as the target population based on observed and imputed values. Trial participants were weighted to be representative of the CPRD population (n = 383,418) based on individual predicted probability of selection into the trial. Trial participants were also standardized to the CPRD population without missing values (n = 2,677). In JUPITER, rosuvastatin reduced cardiovascular risk with a 3-year risk difference of -2.0% (95% confidence interval (CI): -2.9, -1.1). The rosuvastatin effect was muted in the first 2 years but remained strong at 3 years after standardizing to the imputed CPRD population (3-year risk difference = -2.7%; 95% CI: -5.8, 0.4) and the CPRD population without missing data (3-year risk difference = -1.7%; 95% CI: -3.5, 0.1). The study serves as an illustration of possible approaches to understanding generalizability of trials using real-world databases given limitations due to missing data on inclusion/exclusion criteria.

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