Evidence map›Paper›PMID 38596781›Full record

ReviewEuropean urology open science2024

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

Ailbhe Lawlor, Carol Lin, Juan Gómez Rivas, Laura Ibáñez, Pablo Abad López, Peter-Paul Willemse, Muhammad Imran Omar, Sebastiaan Remmers, Philip Cornford, Pawel Rajwa and 14 more

Abstract readReview
In one paragraph

Review in European urology open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Ailbhe LawlorTranslational Oncology and Urology Research (TOUR), King's College London, London, UK.
Carol LinDepartment of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands.
Juan Gómez RivasDepartment of Urology, Health Research Institute, Hospital Clinico San Carlos, Madrid, Spain.
Laura IbáñezDepartment of Urology, Health Research Institute, Hospital Clinico San Carlos, Madrid, Spain.
Pablo Abad LópezDepartment of Urology, Hospital Universitario La Paz, Madrid, Spain.
Peter-Paul WillemseDepartment of Oncological Urology, University Medical Center, Utrecht Cancer Center, Utrecht, The Netherlands.
Muhammad Imran OmarAcademic Urology Unit, University of Aberdeen, Aberdeen, UK.
Sebastiaan RemmersDepartment of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands.
Philip CornfordLiverpool University Hospitals NHS Trust, Liverpool, UK.
Pawel RajwaDepartment of Urology, Medical University of Silesia, Zabrze, Poland.
Rossella NicolettiDepartment of Experimental and Clinical Biomedical Science, University of Florence, Florence, Italy.
Giorgio GandagliaDepartment of Urology and Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Hospital, Milan, Italy.
Jeremy Yuen-Chun TeohS.H. Ho Urology Centre, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China.
Jesús Moreno SierraDepartment of Urology, Health Research Institute, Hospital Clinico San Carlos, Madrid, Spain.
Asieh GolozarOHDSI Center, Northeastern University, Boston, MA, USA.
Anders BjartellDepartment of Translational Medicine, Lund University, Malmö, Sweden.
Susan Evans-AxelssonBayer AB, Medical Affairs Oncology, Stockholm, Sweden.
James N'DowEuropean Association of Urology, Guidelines Office, Arnhem, The Netherlands.
Jihong ZongBayer Healthcare, Global Medical Affairs Oncology, Whippany, NJ, USA.
Maria J RibalEuropean Association of Urology, Guidelines Office, Arnhem, The Netherlands.
Monique J RoobolDepartment of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands.
Mieke Van HemelrijckTranslational Oncology and Urology Research (TOUR), King's College London, London, UK.
Katharina BeyerDepartment of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands.
PIONEER Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Adverse eventsDisease progressionMetastatic prostate cancerOverall survivalPredictive modelsToxicityTreatment discontinuationTreatment selection

Identifiers

PMID38596781
PMCPMC11001619

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.