Demystifying Clone-Censor-Weighting to Studying Treatment Initiation Windows: An Example Using Publicly Available Synthetic Medicare Claims Data

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Abstract

Background: Clone-censor-weighting (CCW) can compare treatment regimens that are initially indistinguishable (such as starting treatment within specific time windows) without using landmarks or creating immortal time. The causal contrasts estimated in these cases and the analyses themselves can become quite complex; however. Objective: Provide a tutorial on CCW for comparing initiation windows and illustrate the causal contrasts underlying such comparisons. Methods: We identified patients with myocardial infarctions without past aspirin or clopidogrel use in Medicare's synthetic public data files. We assigned “clones” to three regimens: (1) initiation within 30 days; (2) initiation within 90 days; or 3) initiation from 30 to 90 days. Clones were censored when deviating from their assigned regimen by failing to initiate treatment in time or by initiating treatment too early. We addressed informative censoring using inverse probability of censoring weights (IPCW), calculated weighted 180-day risks of re-hospitalization or death using Kaplan–Meier methods, and visualized the portion of the population exposed during the first 90 days to compare exposure distributions underlying regimens. Results: We identified 1589 patients experiencing myocardial infarction with no past medication use. 15% initiated within 30 days and 26% initiated between 30 and 90 days. After IPCW, the 180-day outcome risk was 40.2% in the 30-day regimen, 35.7% in the 90-day regimen, and 35.2% in the 30-to-90 day regimen. Conclusions: Though CCW can be complex to implement and the effects it estimates can vary substantially across study populations that initiate treatments at different times, it is a useful tool for contrasting initiation windows.

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Webster-Clark, M., Li, Y., Dell’Aniello, S., & Platt, R. W. (2025). Demystifying Clone-Censor-Weighting to Studying Treatment Initiation Windows: An Example Using Publicly Available Synthetic Medicare Claims Data. Pharmacoepidemiology and Drug Safety, 34(10). https://doi.org/10.1002/pds.70223

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