ArticleDiagnostic and prognostic research2019
A simple, step-by-step guide to interpreting decision curve analysis.
Article in Diagnostic and prognostic research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 702 papers, 5 of them syntheses that pooled 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.
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.
Who cites it
702 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Development and validation of a multiancestry and multitrait polygenic risk score for lung cancer.Nature communications · 2026Pooled it
- Electronic health record-based prediction models for dementia detection: a systematic review of model performance and quality.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- Prediction models for caesarean section following induction of labour: a systematic review of methodology and reporting quality.BMC medical research methodology · 2026Pooled it
- Second-generation capsule endoscopy for the detection of colorectal polyps: An updated systematic review and comparative meta-analysis of prospective studies.Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland · 2026Pooled it
- Prediction models for infection after kidney transplantation: a systematic review.Frontiers in medicine · 2026Pooled it
- Why decision curves cross treat-all and treat-none: A PPV and calibration perspective.Global epidemiology · 2026Article
- Clinician-accessible automated machine learning in oral healthcare: A systematic review.The Japanese dental science review · 2026Review
- Development and Validation of a Clinical Prediction Rule to Identify Preoperatively Patients With Acute Refractory Pain After Lumbar Spine Surgery.Pain practice : the official journal of World Institute of Pain · 2026Article
- From Molecular Signal to Clinical Action in Cardiovascular-Kidney-Metabolic Disease.Kidney international reports · 2026Article
- Admission serum mitochondrial DNA relative abundance is associated with angiographic no-reflow or slow-flow after primary percutaneous coronary intervention in STEMI.Journal of thrombosis and thrombolysis · 2026Article
- Article
- Predicting Retinopathy of Prematurity in Thailand: A Practical Model for Risk-Based Screening.Diagnostics (Basel, Switzerland) · 2026Article
- A Parsimonious Machine Learning Model for Predicting Invasive Coronary Angiography Referral After Coronary Computed Tomography Angiography: Development and Multicentre External Validation.Journal of clinical medicine · 2026Article
- Clinical Relevance of Donor-Derived Cell-Free DNA in Monitoring Kidney Transplant Rejection.Journal of the American Society of Nephrology : JASN · 2026Observational
- Predicting High-Risk CKD in Japanese People: Model Development and Validation.Kidney international reports · 2026Article
- A novel nomogram incorporating LASSO and Cox regression analyses for predicting survival in early-stage non-small cell lung cancer patients following sublobectomy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Pretreatment prediction of early severe treatment-related toxicity in older patients with lung adenocarcinoma: same-center temporal validation of a risk model.Journal of thoracic disease · 2026Article
- Development and Validation of a Machine Learning Model for Predicting One-year Anemia After Bariatric Surgery: A Multicenter Study.Obesity surgery · 2026Article
- Article
- A Clinician-Configurable FAHP-Based Ensemble Framework for Multi-Label Chest X-Ray Classification.Diagnostics (Basel, Switzerland) · 2026Article
642 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDecision curve analysis is a method to evaluate prediction models and diagnostic tests that was introduced in a 2006 publication. Decision curves are now commonly reported in the literature, but there remains widespread misunderstanding of and confusion about what they mean. SUMMARY OF COMMENTARY: In this paper, we present a didactic, step-by-step introduction to interpreting a decision curve analysis and answer some common questions about the method. We argue that many of the difficulties with interpreting decision curves can be solved by relabeling the
conclusionDecision curves are readily interpretable if readers and authors follow a few simple guidelines.
Indexed as
Identifiers
What OpenQuestion holds
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.