Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated with Eribulin

J. G.C. Van Hasselt, A. Gupta, Z. Hussein, J. H. Beijnen, J. H.M. Schellens, A. D.R. Huitema

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Frameworks that associate cancer dynamic disease progression models with parametric survival models for clinical outcome have recently been proposed to support decision making in early clinical development. Here we developed such a disease progression clinical outcome model for castration-resistant prostate cancer (CRPC) using historical phase II data of the anticancer agent eribulin. Disease progression was captured using the dynamics of prostate-specific antigen (PSA). For clinical outcome, overall survival (OS) was used. The model for PSA dynamics comprised parameters for baseline PSA (23.2 ng/ml, relative standard error (RSE) 16.5%), growth rate (0.00879 day-1, RSE 12.6%), drug effect (0.241 μg·h·l-1 day-1, RSE 32.6%), and resistance development (0.0113 day-1, RSE 44.3%). OS was modeled according to a Weibull distribution. Predictors for survival included model-predicted PSA time to nadir (TTN), PSA growth rate, Eastern Cooperative Oncology Group (ECOG) score, and baseline PSA. The developed framework can be considered to support informative design and analysis of drugs developed for CRPC.

Original languageEnglish
Pages (from-to)386-395
Number of pages10
JournalCPT: Pharmacometrics and Systems Pharmacology
Volume4
Issue number7
DOIs
Publication statusPublished - 1 Aug 2015
Externally publishedYes

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