Your browser doesn't support javascript.
loading
Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review.
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.
Afiliação
  • Lawlor A; Translational Oncology and Urology Research (TOUR), King's College London, London, UK.
  • Lin C; Department of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands.
  • Gómez Rivas J; Department of Urology, Health Research Institute, Hospital Clinico San Carlos, Madrid, Spain.
  • Ibáñez L; Department of Urology, Health Research Institute, Hospital Clinico San Carlos, Madrid, Spain.
  • Abad López P; Department of Urology, Hospital Universitario La Paz, Madrid, Spain.
  • Willemse PP; Department of Oncological Urology, University Medical Center, Utrecht Cancer Center, Utrecht, The Netherlands.
  • Imran Omar M; Academic Urology Unit, University of Aberdeen, Aberdeen, UK.
  • Remmers S; Department of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands.
  • Cornford P; Liverpool University Hospitals NHS Trust, Liverpool, UK.
  • Rajwa P; Department of Urology, Medical University of Silesia, Zabrze, Poland.
  • Nicoletti R; Department of Experimental and Clinical Biomedical Science, University of Florence, Florence, Italy.
  • Gandaglia G; S.H. Ho Urology Centre, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China.
  • Yuen-Chun Teoh J; Department of Urology and Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Hospital, Milan, Italy.
  • Moreno Sierra J; OHDSI Center, Northeastern University, Boston, MA, USA.
  • Golozar A; S.H. Ho Urology Centre, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China.
  • Bjartell A; Department of Urology, Health Research Institute, Hospital Clinico San Carlos, Madrid, Spain.
  • Evans-Axelsson S; OHDSI Center, Northeastern University, Boston, MA, USA.
  • N'Dow J; Odysseus Data Services, New York, NY, USA.
  • Zong J; Department of Translational Medicine, Lund University, Malmö, Sweden.
  • Ribal MJ; Bayer AB, Medical Affairs Oncology, Stockholm, Sweden.
  • Roobol MJ; European Association of Urology, Guidelines Office, Arnhem, The Netherlands.
  • Van Hemelrijck M; Bayer Healthcare, Global Medical Affairs Oncology, Whippany, NJ, USA.
  • Beyer K; European Association of Urology, Guidelines Office, Arnhem, The Netherlands.
Eur Urol Open Sci ; 63: 126-135, 2024 May.
Article em En | MEDLINE | ID: mdl-38596781
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.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article