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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Propensity score-integrated composite likelihood approach for augmenting the control arm of a randomized controlled
Wei-Chen Chen1, Chenguang Wang2, Heng Li1
1Division of Biostatistics, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Abstract:
In this paper, a propensity score-integrated composite likelihood (PSCL) approach is developed for cases in which the control arm of a two-arm randomized controlled trial (RCT) (treated vs control) is augmented with patients from real-world data (RWD) containing both clinical outcomes and covariates at the patient-level. RWD patients who were treated with the same therapy as the control arm of the RCT are considered for the augmentation. The PSCL approach first estimates the propensity score for every patient as the probability of the patient being in the RCT rather than the RWD, and then stratifies all patients into strata based on the estimated propensity scores. Within each propensity score stratum, a composite likelihood function is specified and utilized to down-weight the information contributed by the RWD source. Estimates of the stratum-specific parameters are obtained by maximizing the composite likelihood function. These stratum-specific estimates are then combined to obtain an overall population-level estimate of the parameter of interest. The performance of the proposed approach is evaluated via a simulation study. A hypothetical two-arm RCT and a hypothetical RWD source are used to illustrate the implementation of the proposed approach.
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