Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer: A Systematic Review

• Published in: European urology open science (Online) Vol. 63; pp. 126 - 135
• Main Authors: Lawlor, Ailbhe, Lin, Carol, Gómez Rivas, Juan, Ibáñez, Laura, Abad López, Pablo, Willemse, Peter-Paul, Imran Omar, Muhammad, Remmers, Sebastiaan, Cornford, Philip, Rajwa, Pawel, Nicoletti, Rossella, Gandaglia, Giorgio, Yuen-Chun Teoh, Jeremy, Moreno Sierra, Jesús, Golozar, Asieh, Bjartell, Anders, Evans-Axelsson, Susan, N'Dow, James, Zong, Jihong, Ribal, Maria J., Roobol, Monique J., Van Hemelrijck, Mieke, Beyer, Katharina
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.05.2024; Elsevier
• Subjects: Adverse events; Cancer and Oncology; Cancer och onkologi; Clinical Medicine; Disease progression; Klinisk medicin; Medical and Health Sciences; Medicin och hälsovetenskap; Metastatic prostate cancer; Overall survival; Predictive models; Review – Prostate Cancer; Toxicity; Treatment discontinuation; Treatment selection; Urology; Treatment discontinuation; Adverse events; Treatment selection; Toxicity; Disease progression; Predictive models; Metastatic prostate cancer; Overall survival

Existing predictive models for men diagnosed with metastatic prostate cancer are not suitable for use due to a lack of model performance and external validation. There remains a need for high-quality predictive models to guide treatment selection in clinical practice. The treatment landscape of meta...