Open AccessPropensity score matching and inverse probability of treatment weighting to address confounding by indication in comparative effectiveness research of oral anticoagulants
Author(s) -
Victoria Allan,
Sreeram Ramagopalan,
Jack Mardekian,
Aaron Jenkins,
Xiaoyan Li,
Xiangbin Pan,
Xuemei Luo
Publication year - 2020
Publication title -
journal of comparative effectiveness research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.567
H-Index - 23
eISSN - 2042-6313
pISSN - 2042-6305
DOI - 10.2217/cer-2020-0013
Subject(s) - medicine , dabigatran , propensity score matching , apixaban , rivaroxaban , inverse probability weighting , edoxaban , atrial fibrillation , warfarin , comparative effectiveness research , randomized controlled trial , matching (statistics) , confounding , randomization , alternative medicine , pathology
After decades of warfarin being the only oral anticoagulant (OAC) widely available for stroke prevention in atrial fibrillation, four direct OACs (apixaban, dabigatran, edoxaban and rivaroxaban) were approved after demonstrating noninferior efficacy and safety versus warfarin in randomized controlled trials. Comparative effectiveness research of OACs based on real-world data provides complementary information to randomized controlled trials. Propensity score matching and inverse probability of treatment weighting are increasingly popular methods used to address confounding by indication potentially arising in comparative effectiveness research due to a lack of randomization in treatment assignment. This review describes the fundamentals of propensity score matching and inverse probability of treatment weighting, appraises differences between them and presents applied examples to elevate understanding of these methods within the atrial fibrillation field.