Point success rate for patient therapeutic response prediction by continuous biomarker scores. (August 2016)

• Record Type: Journal Article
• Authors: Ma, Zhenjun; Kim, Youngchul; Hu, Feifang; Lee, Jae K
• Other Names: Lawson Andrew B guest-editor.; Lee Duncan guest-editor.; MacNab Ying guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 25:Number 4(2016:Aug.)
• Page Start: 1638
• Page End: 1647
• Publication Date: 2016-08
• Subjects: biomarker -- COXEN -- personalized chemotherapy -- point success rate; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280213493161
• Languages: English
• ISSNs: 0962-2802

Abstract

Various predictive diagnostic tests are highly demanded to guide optimal treatments for individual patients, as individual patients with the same disease such as cancer frequently exhibit dramatically different therapeutic responses to multiple available treatment options. A large number of clinical trials have thus been performed to test the predictive ability and utility of various therapeutic biomarker tests. However, in these trial designs the conventional optimization criteria such as positive predictive value or negative predictive value cannot reflect each patient's true chance of success associated with continuous predictive biomarker scores. We have developed a novel statistical concept, point success rate (PSR), to overcome deficiencies in these conventional methods for optimizing biomarker-based clinical trials. We demonstrate statistical superiority as well as clinical improvement by a PSR-based treatment selection both with simulated and breast cancer patient data.