Open AccessPoint success rate for patient therapeutic response prediction by continuous biomarker scores
Author(s) -
Zhenjun Ma,
YoungChul Kim,
Feifang Hu,
Duncan Lee
Publication year - 2016
Publication title -
statistical methods in medical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.952
H-Index - 85
eISSN - 1477-0334
pISSN - 0962-2802
DOI - 10.1177/0962280213493161
Subject(s) - biomarker , predictive value , clinical trial , medicine , breast cancer , oncology , cancer , biochemistry , chemistry
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.