Back to Search Start Over

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

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
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
Source :
Lawlor , A , Lin , C , Gómez Rivas , J , Ibáñez , L , Abad López , P , Willemse , P P , Imran Omar , M , Remmers , S , Cornford , P , Rajwa , P , Nicoletti , R , Gandaglia , G , Yuen-Chun Teoh , J , Moreno Sierra , J , Golozar , A , Bjartell , A , Evans-Axelsson , S , N'Dow , J , Zong , J , Ribal , M J , Roobol , M J , Van Hemelrijck , M & Beyer , K 2024 , ' Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer : A Systematic Review ' , European Urology Open Science , vol. 63 , pp. 126-135 .
Publication Year :
2024

Abstract

Background and objective: 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. Methods: 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. Key findings and limitations: 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. Conclusions and clinical implications: 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. Patient summary: 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.

Details

Database :
OAIster
Journal :
Lawlor , A , Lin , C , Gómez Rivas , J , Ibáñez , L , Abad López , P , Willemse , P P , Imran Omar , M , Remmers , S , Cornford , P , Rajwa , P , Nicoletti , R , Gandaglia , G , Yuen-Chun Teoh , J , Moreno Sierra , J , Golozar , A , Bjartell , A , Evans-Axelsson , S , N'Dow , J , Zong , J , Ribal , M J , Roobol , M J , Van Hemelrijck , M & Beyer , K 2024 , ' Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer : A Systematic Review ' , European Urology Open Science , vol. 63 , pp. 126-135 .
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1430692867
Document Type :
Electronic Resource