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

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, observ...

Descripción completa

Detalles Bibliográficos
Autores principales: Kazama, Hirotaka, Kawaguchi, Osamu, Seto, Takeshi, Suzuki, Kazuhiro, Matsuyama, Hideyasu, Matsubara, Nobuaki, Tajima, Yuki, Fukao, Taro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052565/
https://www.ncbi.nlm.nih.gov/pubmed/35484517
http://dx.doi.org/10.1186/s12885-022-09509-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052565/
https://www.ncbi.nlm.nih.gov/pubmed/35484517
http://dx.doi.org/10.1186/s12885-022-09509-0

Ejemplares similares