ArticleMedical decision making : an international journal of the Society for Medical Decision Making2022
Recalibration Methods for Improved Clinical Utility of Risk Scores.
Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Clinical impact of MRI-based risk calculators for prostate cancer diagnosis: a systematic review and meta-analysis.Prostate cancer and prostatic diseases · 2026Pooled it
- Predictive performance of risk prediction models for lung cancer incidence in Western and Asian countries: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review.Open heart · 2025Pooled it
- Assigning Probable Dementia Status Using Routinely Collected Electronic Health Record Data.Journal of the American Geriatrics Society · 2026Article
- Validation and Recalibration of PCE, China-PAR, and PREVENT Models for Estimating ASCVD Risk in China.JACC. Asia · 2026Article
- Development and validation of risk models for hospital-acquired bleeding in medical inpatients: the Medical Inpatients Thrombosis and Hemostasis (MITH) study.Journal of thrombosis and haemostasis : JTH · 2026Article
- External validation of dementia risk prediction models in the EPIC-Norfolk cohort: a UK-based cohort study.NPJ dementia · 2026Article
- Clinical Utility of Multicancer Detection in Symptomatic Patients: A Decision-Making Perspective.JCO precision oncology · 2025Article
- External validation and comparison of clinical prediction models for cisplatin-associated acute kidney injury: a single-centre retrospective study.Journal of pharmaceutical health care and sciences · 2025Article
- Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive Care IV (MIMIC-IV) Database.Journal of medical Internet research · 2025Article
- Performance of contemporary cardiovascular risk stratification scores in Brazil: an evaluation in the ELSA-Brasil study.Open heart · 2024Article
- Assessing calibration and bias of a deployed machine learning malnutrition prediction model within a large healthcare system.NPJ digital medicine · 2024Article
- Recalibration Methods for Improved Clinical Utility of Risk Scores.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
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4 authors.
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Abstract
backgroundAn established risk model may demonstrate miscalibration, meaning predicted risks do not accurately capture event rates. In some instances, investigators can identify and address the cause of miscalibration. In other circumstances, it may be appropriate to recalibrate the risk model. Existing recalibration methods do not account for settings in which the risk score will be used for risk-based clinical decision making.
methodsWe propose 2 new methods for risk model recalibration when the intended purpose of the risk model is to prescribe an intervention to high-risk individuals. Our measure of risk model clinical utility is standardized net benefit. The first method is a weighted strategy that prioritizes good calibration at or around the critical risk threshold. The second method uses constrained optimization to produce a recalibrated risk model with maximum possible net benefit, thereby prioritizing good calibration around the critical risk threshold. We also propose a graphical tool for assessing the potential for recalibration to improve the net benefit of a risk model. We illustrate these methods by recalibrating the American College of Cardiology (ACC)-American Heart Association (AHA) atherosclerotic cardiovascular disease (ASCVD) risk score within the Multi-Ethnic Study of Atherosclerosis (MESA) cohort.
resultsNew methods are implemented in the R package
conclusionThe proposed methods target good calibration for critical risks and can improve the net benefit of a risk model. We recommend constrained optimization when the risk model net benefit is paramount. The weighted approach can be considered when good calibration over an interval of risks is important.
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