ArticleJournal of biomedical informatics2015
Improving patient prostate cancer risk assessment: Moving from static, globally-applied to dynamic, practice-specific risk calculators.
Article in Journal of biomedical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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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.
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.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.Applied clinical informatics · 2021Pooled it
- Pooled it
- Comparison of Methods for Incorporating Related Data When Developing Clinical Prediction Models: A Simulation Study.Biometrical journal. Biometrische Zeitschrift · 2026Article
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- Concerns regarding prostate cancer screening guidelines in minority populations.Prostate cancer and prostatic diseases · 2024Article
- External validation of the barcelona magnetic resonance imaging predictive model for detecting significant prostate cancer including men receiving 5-alpha reductase inhibitors.World journal of urology · 2024Article
- Identification of risk factors for the onset of delirium associated with COVID-19 by mining nursing records.PloS one · 2024Article
- Risk score model to automatically detect prostate cancer patients by integrating diagnostic parameters.Frontiers in oncology · 2024Article
- Comparison of Rotterdam and Barcelona Magnetic Resonance Imaging Risk Calculators for Predicting Clinically Significant Prostate Cancer.European urology open science · 2023Article
- EHR foundation models improve robustness in the presence of temporal distribution shift.Scientific reports · 2023Article
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- External Validation of the Prostate Biopsy Collaborative Group Risk Calculator and the Rotterdam Prostate Cancer Risk Calculator in a Swedish Population-based Screening Cohort.European urology open science · 2022Article
- Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare.NPJ digital medicine · 2022Review
- Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Advanced cardiovascular risk prediction in the emergency department: updating a clinical prediction model - a large database study protocol.Diagnostic and prognostic research · 2021Article
- Developing risk models for multicenter data using standard logistic regression produced suboptimal predictions: A simulation study.Biometrical journal. Biometrische Zeitschrift · 2020Article
- Temporal Pattern Detection to Predict Adverse Events in Critical Care: Case Study With Acute Kidney Injury.JMIR medical informatics · 2020Article
- Liquid Biopsy Potential Biomarkers in Prostate Cancer.Diagnostics (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 4 countries.
Funding
Abstract
Clinical risk calculators are now widely available but have generally been implemented in a static and one-size-fits-all fashion. The objective of this study was to challenge these notions and show via a case study concerning risk-based screening for prostate cancer how calculators can be dynamically and locally tailored to improve on-site patient accuracy. Yearly data from five international prostate biopsy cohorts (3 in the US, 1 in Austria, 1 in England) were used to compare 6 methods for annual risk prediction: static use of the online US-developed Prostate Cancer Prevention Trial Risk Calculator (PCPTRC); recalibration of the PCPTRC; revision of the PCPTRC; building a new model each year using logistic regression, Bayesian prior-to-posterior updating, or random forests. All methods performed similarly with respect to discrimination, except for random forests, which were worse. All methods except for random forests greatly improved calibration over the static PCPTRC in all cohorts except for Austria, where the PCPTRC had the best calibration followed closely by recalibration. The case study shows that a simple annual recalibration of a general online risk tool for prostate cancer can improve its accuracy with respect to the local patient practice at hand.
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Registered trials
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.