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Open Access 01-12-2022 | Prostate Cancer | Research

Comprehensive analysis of the associations between clinical factors and outcomes by machine learning, using post marketing surveillance data of cabazitaxel in patients with castration-resistant prostate cancer

Authors: Hirotaka Kazama, Osamu Kawaguchi, Takeshi Seto, Kazuhiro Suzuki, Hideyasu Matsuyama, Nobuaki Matsubara, Yuki Tajima, Taro Fukao

Published in: BMC Cancer | Issue 1/2022

Abstract

Background

We aimed to evaluate relationships between clinical outcomes and explanatory variables by network clustering analysis using data from a post marketing surveillance (PMS) study of castration-resistant prostate cancer (CRPC) patients.

Methods

The PMS was a prospective, multicenter, observational study of patients with metastatic, docetaxel-refractory CRPC treated with cabazitaxel in Japan after its launch in 2014. Graphical Markov (GM) model-based simulations and network clustering in ‘R’ package were conducted to identify correlations between clinical factors and outcomes. Factors shown to be associated with overall survival (OS) in the machine learning analysis were confirmed according to the clinical outcomes observed in the PMS.

Results

Among the 660 patients analyzed, median patient age was 70.0 years, and median OS and time-to-treatment failure (TTF) were 319 and 116 days, respectively. In GM-based simulations, factors associated with OS were liver metastases, performance status (PS), TTF, and neutropenia (threshold 0.05), and liver metastases, PS, and TTF (threshold 0.01). Factors associated with TTF were OS and relative dose intensity (threshold 0.05), and OS (threshold 0.01). In network clustering in ‘R’ package, factors associated with OS were number of treatment cycles, discontinuation due to disease progression, and TTF (threshold 0.05), and liver and lung metastases, PS, discontinuation due to adverse events, and febrile neutropenia (threshold 0.01). Kaplan–Meier analysis of patient subgroups demonstrated that visceral metastases and poor PS at baseline were associated with worse OS, while neutropenia or febrile neutropenia and higher number of cabazitaxel cycles were associated with better OS.

Conclusions

Neutropenia may be a predictive factor for treatment efficacy in terms of survival. Poor PS and distant metastases to the liver and lungs were shown to be associated with worse outcomes, while factors related to treatment duration were shown to positively correlate with better OS.

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Title: Comprehensive analysis of the associations between clinical factors and outcomes by machine learning, using post marketing surveillance data of cabazitaxel in patients with castration-resistant prostate cancer
Authors: Hirotaka Kazama
Osamu Kawaguchi
Takeshi Seto
Kazuhiro Suzuki
Hideyasu Matsuyama
Nobuaki Matsubara
Yuki Tajima
Taro Fukao
Publication date: 01-12-2022
Publisher: BioMed Central
Keywords: Prostate Cancer
Metastasis
Prostate Cancer
Neutropenia
Published in: BMC Cancer / Issue 1/2022
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-022-09509-0

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Abstract

Background

Methods

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Conclusions

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