Evidence map›Paper›PMID 40502720›Full record

ArticlePhysics and imaging in radiation oncology2025

The value of post radiotherapy prostate specific antigen dynamics for prostate cancer risk stratification models.

Jane Shortall, Eliana Vasquez Osorio, Andrew Green, Kimberley Reeves, David Wong, Tanuj Puri, Peter Hoskin, Ananya Choudhury, Marcel van Herk, Alan McWilliam

Abstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Jane ShortallDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.
Eliana Vasquez OsorioDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.
Andrew GreenEMBL's European Bioinformatics Institute, UK.
Kimberley ReevesDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.
David WongDivision of Informatics, The University of Manchester, Manchester, UK.
Tanuj PuriDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.
Peter HoskinDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.
Ananya ChoudhuryDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.
Marcel van HerkDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.
Alan McWilliamDepartment of Cancer Sciences, The University of Manchester, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: Risk-stratification at diagnosis of prostate cancer does not always predict risk of biochemical recurrence (BCR). Fully utilizing post-radiotherapy follow-up Prostate Specific Antigen (PSA) data could offer earlier and higher prognostic value than pre-treatment risk-stratification.We investigate whether PSA dynamics in the first three-years of follow-up can re-stratify risk of treatment failure after radical radiotherapy, allowing for targeted intervention. Materials and methods: Retrospective analysis of repeat follow-up PSA measurements from men with mixed-risk prostate cancer treated in two separate radical radiotherapy techniques (n = 446, 2005-2007). PSA trajectories were modelled between zero and three-years follow-up using Gaussian Process regression. Models were sampled and clustered using hierarchical clustering to define characteristic post-radiotherapy PSA trajectories.Kaplan-Meier analysis compared dichotomising by pre-treatment risk-group and characteristic PSA trajectory. Cox proportional-hazard models with and without follow-up PSA information compared using Akaike Information Criterion (AIC). Results: PSA trajectories were characterized as stable, steady-rise, and unstable. Kaplan-Meier analysis showed that pre-treatment risk-group was not prognostic of BCR (p > 0.05), however characteristic PSA trajectory was (p < 0.001). PSA trajectory improved multivariable model performance when added to baseline prognostic variables. Unstable PSA had highest BCR.Results were validated across two cohorts and sensitivity analysis, suggesting results were robust. However, analysis excluded patients with BCR within three-years follow-up due to lack of data. Conclusion: PSA dynamics within the first three-years of post-radiotherapy follow-up for prostate cancer were more prognostic of BCR than pre-treatment risk-groups, suggesting PSA dynamics could be used to re-stratify BCR risk during early follow-up.

Indexed as

Biochemical recurrenceFollow-upProstate cancerProstate specific antigenRadiotherapyRisk-stratification

Identifiers

PMID40502720
PMCPMC12156266

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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.