Lawlor, Ailbhe, Lin, Carol, Gómez Rivas, Juan, Ibáñez, Laura, Abad López, Pablo, Willemse, Peter-Paul, Imran Omar, Muhammad, Remmers, Sebastiaan, Cornford, Philip 
ORCID: 0000-0002-7146-9258, Rajwa, Pawel et al (show 14 more authors)
(2024)
Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review.
European urology open science, 63.
pp. 126-135.
Abstract
<h4>Background and objective</h4>The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients' response to treatment.<h4>Methods</h4>We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria.<h4>Key findings and limitations</h4>The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance.<h4>Conclusions and clinical implications</h4>Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa.<h4>Patient summary</h4>In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | PIONEER Consortium |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences > School of Medicine |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 30 Apr 2024 08:28 |
| Last Modified: | 11 May 2024 02:34 |
| DOI: | 10.1016/j.euros.2024.03.012 |
| Open Access URL: | https://doi.org/10.1016/j.euros.2024.03.012 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3180662 |
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