Evidence map›Paper›PMID 36615017›Full record

ArticleJournal of clinical medicine2022

Development and External Validation of the STRATified CANcer Surveillance (STRATCANS) Multivariable Model for Predicting Progression in Men with Newly Diagnosed Prostate Cancer Starting Active Surveillance.

Alexander Light, Artitaya Lophatananon, Alexandra Keates, Vineetha Thankappannair, Tristan Barrett, Jose Dominguez-Escrig, Jose Rubio-Briones, Toufik Benheddi, Jonathan Olivier, Arnauld Villers and 3 more

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

13 authors.

Alexander LightDivision of Urology, Department of Surgery, University of Cambridge, Cambridge CB2 0QQ, UK.ORCID 0000-0001-7246-3651
Artitaya LophatananonDivision of Population Health, Health Services Research and Primary Care, University of Manchester, Manchester M13 9PL, UK.
Alexandra KeatesDepartment of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK.
Vineetha ThankappannairDepartment of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK.
Tristan BarrettDepartment of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK.
Jose Dominguez-EscrigDepartment of Urology, Fundación Instituto Valenciano de Oncología, 46009 Valencia, Spain.
Jose Rubio-BrionesDepartment of Urology, Fundación Instituto Valenciano de Oncología, 46009 Valencia, Spain.
Toufik BenheddiDepartment of Urology, Lille University, 59000 Lille, France.
Jonathan OlivierDepartment of Urology, Lille University, 59000 Lille, France.
Arnauld VillersDepartment of Urology, Lille University, 59000 Lille, France.
Kirthana BabureddyDepartment of Urology, University Hospital of Wales, Cardiff and Vale University Health Board, Cardiff CF14 4XW, UK.
Haitham AbdelmotelebDepartment of Urology, University Hospital of Wales, Cardiff and Vale University Health Board, Cardiff CF14 4XW, UK.
Vincent J GnanapragasamDivision of Urology, Department of Surgery, University of Cambridge, Cambridge CB2 0QQ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For men with newly diagnosed prostate cancer, we aimed to develop and validate a model to predict the risk of progression on active surveillance (AS), which could inform more personalised AS strategies. In total, 883 men from 3 European centres were used for model development and internal validation, and 151 men from a fourth European centre were used for external validation. Men with Cambridge Prognostic Group (CPG) 1-2 disease at diagnosis were eligible. The endpoint was progression to the composite endpoint of CPG3 disease or worse (≥CPG3). Model performance at 4 years was evaluated through discrimination (C-index), calibration plots, and decision curve analysis. The final multivariable model incorporated prostate-specific antigen (PSA), Grade Group, magnetic resonance imaging (MRI) score (Prostate Imaging Reporting & Data System (PI-RADS) or Likert), and prostate volume. Calibration and discrimination were good in both internal validation (C-index 0.742, 95% CI 0.694-0.793) and external validation (C-index 0.845, 95% CI 0.712-0.958). In decision curve analysis, the model offered net benefit compared to a 'follow-all' strategy at risk thresholds of ≥0.08 and ≥0.04 in development and external validation, respectively. In conclusion, our model demonstrated good accuracy and clinical utility in predicting the progression on AS at 4 years post-diagnosis. Men with lower risk predictions could subsequently be offered less-intense surveillance. Further external validation in larger cohorts is now required.

Indexed as

active surveillancebiopsyCambridge Prognostic Groups (CPG)MRInon-metastatic diseaseprostate cancerPSArisk modelrisk prediction

Identifiers

PMID36615017
PMCPMC9821695

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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.