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Activity Number: 331
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #312023 View Presentation
Title: Valid Inference with Dependent Samples
Author(s): Suzanne Swann*+
Companies: GlaxoSmithKline
Keywords: retrospective clinical assay validation ; correlation ; dependent samples ; bootstrap
Abstract:

As targeted therapies based on biomarker status become more common in oncology and other therapeutic areas, development of biomarker assays in parallel with targeted anti-cancer therapy will also be more common. In some cases, patients enrol in a trial based on assay results from one assay and a commercial assay is validated after the fact. Retrospective clinical assay validation compares clinical endpoints for the same patients with the same biomarker status on both assays and therefore employs dependent samples, one of which is a subset of the other. Clinical efficacy endpoints in oncology trials include response, which is dichotomous, or time-to-event endpoints such as overall survival (OS) or progression-free survival (PFS). Valid inference for these two different types of endpoints requires estimation of correlation. For response, a closed form derivation for the covariance relies that uses a binomial distribution for the number of responses is available. For time-to-event endpoints, a confidence interval for the difference of the log(hazard ratio) from each sample can use a bootstrapped correlation estimate.


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