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Enhancing Evidence Generation by Linking Randomized Clinical Trials to Real-World Data: The INVESTED-Medicare Linkage
Hanseul Cho1,2, HoJin Shin1,3, Mehdi Najafzadeh4
1Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Abstract:
Real-world evidence (RWE) derived from real-world data (RWD) can complement randomized controlled trials (RCTs), yet the validity of RWD relative to RCT data remains insufficiently characterized. We obtained post hoc consent and linked individual participant data from the US-based INVESTED trial (2016-2019) with Medicare fee-for-service claims (2012-2020) to validate demographic factors, baseline characteristics (using 183-, 365-, and 730-day lookback periods) and outcomes, and to assess post-trial events. Among 5260 trial participants, 126 were enrolled and eligible for linkage. Among 115 participants with demographic information available from Medicare enrollment files, agreement between RCT- and RWD-based demographic factors was high: only one major age discrepancy, 100% agreement for sex, and an overall agreement of 0.89 for race. Participants with Medicare claims data (n = 65) were older and more likely to be White compared with the overall RCT population. For the 365-day lookback period, baseline comorbidities showed high sensitivity (median 0.80) and specificity (0.89), as did medication use (sensitivity 1.00, specificity 0.88). Lengthening the lookback period to 730 days increased sensitivity but decreased specificity, whereas shortening to 183 days decreased sensitivity but increased specificity. Clinical outcomes showed high specificity (0.88-0.94) but low sensitivity (0.18-0.50). Among those with Medicare coverage beyond the trial end date (n = 45), 22% experienced cardiopulmonary, 18% cardiovascular, and 7% heart failure (HF) hospitalizations, highlighting the value of RWD for extending RCT evidence. Proactive planning of future RCT-RWD linkage initiatives can improve the efficiency of linkage studies, leading to more actionable results.
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