Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology

Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy. Diff...

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Veröffentlicht in:Journal of clinical epidemiology 2023-03, Vol.155, p.31-38
Hauptverfasser: Thurin, Nicolas H., Jové, Jérémy, Lassalle, Régis, Rouyer, Magali, Lamarque, Stéphanie, Bosco-Levy, Pauline, Segalas, Corentin, Schneeweiss, Sebastian, Blin, Patrick, Droz-Perroteau, Cécile
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Sprache:eng
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Zusammenfassung:Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy. Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Sytème National des Données de Santé-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed. Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c = 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c = 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month −1. In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias.
ISSN:0895-4356
1878-5921
DOI:10.1016/j.jclinepi.2023.01.002