Open AccessExposure–Response‐Based Product Profile–Driven Clinical Utility Index for Ipatasertib Dose Selection in Prostate Cancer
Author(s) -
Zhu Rui,
Poland Bill,
Wada Russ,
Liu Qi,
Musib Luna,
Maslyar Daniel,
Cho Eunpi,
Yu Wei,
Ma Han,
Jin Jin Yan,
Budha Nageshwar
Publication year - 2019
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12394
Subject(s) - prostate cancer , logistic regression , medicine , cutoff , proportional hazards model , oncology , index (typography) , cancer , statistics , mathematics , computer science , physics , quantum mechanics , world wide web
The aims of this work were to characterize ipatasertib exposure–response (E‐R) relationships in a phase II study and to quantitatively assess benefit‐risk using a clinical utility index approach to support ipatasertib phase III dose selection in patients with metastatic castration‐resistant prostate cancer. Logistic regression and Cox proportional‐hazards models characterized E‐R relationships for safety and efficacy endpoints, respectively. Exposure metrics with and without considering dose interruptions/reductions (modifications) were tested in the E‐R models. Despite a steeper E‐R relationship when accounting for dose modifications, similar dose‐response projections were generated. The clinical utility index analysis assessed important attributes, weights, and clinically meaningful cutoff/tradeoff values based on predefined minimal, target, and optimistic product profiles. Ipatasertib 400 mg daily, showing the highest probability of achieving the minimal product profiles and better benefit‐risk balance than other doses (200–500 mg daily), was selected for further development in metastatic castration‐resistant prostate cancer .