Considerations for pooling real-world data as a comparator cohort to a single arm trial: a simulation study on assessment of heterogeneity.

Autor: Backenroth D; Janssen Research & Development, Titusville, USA., Royce T; Flatiron Health, Inc, 233 Spring Street, New York, NY, 10013, USA., Pinheiro J; Janssen Research & Development, Titusville, USA., Samant M; Flatiron Health, Inc, 233 Spring Street, New York, NY, 10013, USA., Humblet O; Flatiron Health, Inc, 233 Spring Street, New York, NY, 10013, USA. ohumblet@gmail.com.
Jazyk: angličtina
Zdroj: BMC medical research methodology [BMC Med Res Methodol] 2023 Aug 24; Vol. 23 (1), pp. 193. Date of Electronic Publication: 2023 Aug 24.
DOI: 10.1186/s12874-023-02002-7
Abstrakt: Background: Novel precision medicine therapeutics target increasingly granular, genomically-defined populations. Rare sub-groups make it challenging to study within a clinical trial or single real-world data (RWD) source; therefore, pooling from disparate sources of RWD may be required for feasibility. Heterogeneity assessment for pooled data is particularly complex when contrasting a pooled real-world comparator cohort (rwCC) with a single-arm clinical trial (SAT), because the individual comparisons are not independent as all compare a rwCC to the same SAT. Our objective was to develop a methodological framework for pooling RWD focused on the rwCC use case, and simulate novel approaches of heterogeneity assessment, especially for small datasets.
Methods: We present a framework with the following steps: pre-specification, assessment of dataset eligibility, and outcome analyses (including assessment of outcome heterogeneity). We then simulated heterogeneity assessments for a binary response outcome in a SAT compared to two rwCCs, using standard methods for meta-analysis, and an Adjusted Cochran's Q test, and directly comparing the individual participant data (IPD) from the rwCCs.
Results: We found identical power to detect a true difference for the adjusted Cochran's Q test and the IPD method, with both approaches superior to a standard Cochran's Q test. When assessing the impact of heterogeneity in the null scenario of no difference between the SAT and rwCCs, a lack of statistical power led to Type 1 error inflation. Similarly, in the alternative scenario of a true difference between SAT and rwCCs, we found substantial Type 2 error, with underpowered heterogeneity testing leading to underestimation of the treatment effect.
Conclusions: We developed a methodological framework for pooling RWD sources in the context of designing a rwCC for a SAT. When testing for heterogeneity during this process, the adjusted Cochran's Q test matches the statistical power of IPD heterogeneity testing. Limitations of quantitative heterogeneity testing in protecting against Type 1 or Type 2 error indicate these tests are best used descriptively, and after careful selection of datasets based on clinical/data considerations. We hope these findings will facilitate the rigorous pooling of RWD to unlock insights to benefit oncology patients.
(© 2023. BioMed Central Ltd., part of Springer Nature.)
Databáze: MEDLINE
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