Finding the intended use population for a new treatment. Issue 4 (4th July 2019)

• Record Type: Journal Article
• Authors: Simon, Richard; Simon, Noah
• Is Part Of: Journal of biopharmaceutical statistics. Volume 29:Issue 4(2019)
• Page Start: 675
• Page End: 684
• Publication Date: 2019-07-04
• Subjects: Intended use population -- predictive classification -- subset analysis -- bootstrap de-biasing -- cross-validation; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2019.1636812
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Genomic tools are demonstrating that many human diseases are molecularly heterogeneous and likely to respond differently to molecularly targeted therapeutics. For many widely used treatments, the number of patients needed to treat (NNT) for each patient who benefits is large indicating that many patients are being exposed to the risks of serious adverse effects although they do not benefit from the drug. Consequently, more accurately determining the intended use population for new therapeutics is of increased importance. In this paper, we describe a new paradigm for identifying and internally validating an estimate of the intended use population in randomized phase III clinical trials. The approach preserves the type I error of the trial and approaches determination of the intended use population as a classification problem, not a multiple hypothesis testing problems.