Evidence map›Paper›PMID 41543565›Full record

ArticleEuropean radiology2026

Variation in prostate cancer growth rates in an MRI-based active surveillance cohort.

Hayley Smith, Vasilis Stavrinides, Francesco Giganti, Caroline M Moore, Bharath Narayanan, Mark Emberton, Paul D P Pharoah, Nora Pashayan

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Article in European radiology, 2026. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Hayley SmithDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, UK. hs898@cam.ac.uk.ORCID http://orcid.org/0000-0003-3636-9857
Vasilis StavrinidesUCL Cancer Institute, University College London, London, UK.
Francesco GigantiDivision of Surgery and Interventional Science, University College London, London, UK.
Caroline M MooreDepartment of Urology, University College London Hospitals NHS Trust, London, UK.
Bharath NarayananDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Mark EmbertonDivision of Surgery and Interventional Science, University College London, London, UK.
Paul D P PharoahCedars-Sinai Medical Center, Los Angeles, CA, USA.
Nora PashayanDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Funding

International Alliance for Cancer Early Detection EICEDAAP\100005
6 · The paper itself

Abstract

backgroundUnderstanding tumour growth rates helps optimise screening and active surveillance (AS) schedules. We estimated prostate cancer growth rate accounting for individual variation in a longitudinal AS cohort. MATERIALS AND

methodsWe modelled tumour growth in 145 biopsy-confirmed prostate cancer patients undergoing MRI-based AS. Primary lesion volumes were measured longitudinally using planimetry. We compared three mixed-effects models (exponential, Gompertz, and logistic) and investigated relationships between growth rate and clinical characteristics. We estimated the natural trajectory of prostate cancer lesions starting at a single cell to clinical detectability (diameter ≈ 1 cm), with diameters estimated based on spherical volume.

resultsAll three models fit observed data well; however, only the Gompertz model provided reasonable estimates from a single cell to an MRI-detectable size (diameter ≈ 3 mm). The Gompertz growth parameter (mean = 0.07, range = 0.02-0.15), describing exponential growth deceleration, was positively correlated with: patient age; lesion volume at AS onset; prostate-specific antigen (PSA) level; and PSA density. Lesions with Gleason 3 + 4 had faster volume doubling times than Gleason 3 + 3 lesions (mean = 3.5 and 5.2 years, respectively). On average, it would take 17 years (95% CI [15, 19]) for a lesion to grow from a single cell to an MRI-detectable size and an additional 12 years to reach a clinically detectable size (95% CI [10, 13]). At age 50, 75% of lesions would remain undetectable by MRI.

conclusionsProstate cancer shows slow growth with large variation between patients, posing a challenge for early detection. KEY POINTS: Question What is the population distribution of growth rates and the natural history of prostate cancer? Findings Prostate cancer typically grows slowly, with considerable variation between individuals. On average, lesions take 17 years to grow from initiation to an MRI-detectable size. Clinical relevance Small lesions undetectable on MRI may take many years to reach a clinically significant size, posing a challenge for early detection, as it increases the risk of detecting indolent lesions that may never cause harm.

Indexed as

Magnetic Resonance ImagingProstatic NeoplasmsWatchful WaitingAgedBiopsyCohort StudiesDisease ProgressionHumansMaleMiddle AgedNeoplasm GradingProstate-Specific AntigenProstate-Specific AntigenActive surveillanceEarly detection of cancerMagnetic resonance imagingProstate cancerTumour growth modelling

Identifiers

PMID41543565
PMCPMC13212372

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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.