aceIncremental Propensity Score Interventions: A Primer for Pharmacoepidemiologists
Background In observational pharmacoepidemiology, estimating average treatment effects (ATEs) is often challenging due to a lack of practical positivity. In highly selective clinical settings, certain patients almost always or never receive treatment, causing ATE estimators to rely on unstable extrapolation. Incremental propensity score interventions (IPSIs) offer a stochastic alternative by shifting each patient's probability of treatment, providing a more clinically realistic framework that circumvents positiv…
Using a Super Learner ensemble to estimate propensity scores, shifting each patient's odds of receiving abciximab during PCI reduced 6-month mortality, with a strong pro-treatment incremental policy showing significant benefit.
In highly selective PCI settings, conventional ATE estimation for abciximab suffers from lack of practical positivity, forcing unstable extrapolation and assuming patients with near-certain treatment probability could realistically be assigned to withhold therapy.
Evidence
- Peer-reviewedPharmacoepidemiology and Drug Safety2026-10-01
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Truvace Impact Record TRV-2026-1233, v1: “Incremental Propensity Score Interventions: A Primer for Pharmacoepidemiologists.” Truvace, 2026-10-01. /record/TRV-2026-1233 (accessed at citation time). sha256 9bbf46ade60d2934…
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