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.
journal_name
J Biopharm Statjournal_title
Journal of biopharmaceutical statisticsauthors
Chen WC,Wang C,Li H,Lu N,Tiwari R,Xu Y,Yue LQdoi
10.1080/10543406.2020.1730877subject
Has Abstractpub_date
2020-05-03 00:00:00pages
508-520issue
3eissn
1054-3406issn
1520-5711journal_volume
30pub_type
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