ReviewEuropean urology2018
Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators.
Review in European urology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 846 papers, 1 of them a synthesis that pooled 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.
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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
846 citing papers in PubMed, 1 synthesis or guideline pooled it, 1,241 citations in OpenAlex.
- Development and validation of a novel prediction model for new-onset atrial fibrillation after lung resection.Annals of medicine · 2025Pooled it
- Development and validation of a machine learning-based prediction model for prolonged length of stay after laparoscopic gastrointestinal surgery: a secondary analysis of the FDP-PONV trial.BMC gastroenterology · 2025Trial
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- A four-gene signature for diagnosis of acute kidney injury following kidney transplantation.Renal failure · 2026Article
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- CT radiomics and topology-based intratumoral heterogeneity for preoperative prediction of nuclear β-catenin expression in hepatocellular carcinoma.Abdominal radiology (New York) · 2026Article
- Interpreting ocular age estimates: source, output, evidence, and clinical meaning.Biogerontology · 2026Review
- Site-Specific Characterization and Quantification of Facial Corticosteroid Addiction Dermatitis: A Multimodal Nomogram Integrating High-Frequency Ultrasonography and Transepidermal Water Loss.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2026Article
- Development and Validation of a Dynamic Nomogram for Predicting Postdischarge Nausea and Vomiting in Adults Undergoing Ambulatory Surgery: A Retrospective Cohort Study.International journal of nursing practice · 2026Article
- Physiological Emergency Surgery Acuity Score Predicts Mortality and Anastomotic Leak in Emergency Laparotomy: An External Validation Study.World journal of surgery · 2026Article
- Refining the Multivariable Predictive-Prognostic PREDICTR-OPC Model for Survival in Surgical Escalation for Oropharyngeal Squamous Cell Carcinoma.The Laryngoscope · 2026Observational
- New insights into diagnostic values and mechanisms of ferroptosis associated with immune infiltration in diabetic kidney disease.Experimental and therapeutic medicine · 2026Article
- Early prediction of anastomotic leakage within 24 h after minimally invasive colorectal cancer surgery using postoperative inflammatory markers: development and temporal validation of a machine learning model.Surgical endoscopy · 2026Article
- A Mitochondrial-Related Gene Signature for Diagnosis and Immune Microenvironment Modulation in Lung Cancer and Venous Thromboembolism.World journal of oncology · 2026Article
- Independent model evaluation and decision thresholds in machine-learning prediction of delayed graft function.International urology and nephrology · 2026Article
- CORE-PH: A 3-Component Score for Long-Term Mortality Risk in a Pulmonary Arterial Hypertension Cohort.Diagnostics (Basel, Switzerland) · 2026Article
- Evaluation of the Diagnostic Performance of Prenatal Screening Markers for Down Syndrome in the Turkistan Region.Healthcare (Basel, Switzerland) · 2026Article
- Methodological and clinical considerations of MRI-based prostate cancer risk calculators.Prostate cancer and prostatic diseases · 2026Article
- Development of an Explainable Machine Learning Model to Predict Mortality Risk in Sepsis Patients: Insights From a Real-World Clinical Data.Shock (Augusta, Ga.) · 2026Article
- Response to de Riese et al. regarding "methodological and clinical considerations of MRI-based prostate cancer risk calculators".Prostate cancer and prostatic diseases · 2026Article
786 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 5 countries.
Funding
Abstract
contextUrologists regularly develop clinical risk prediction models to support clinical decisions. In contrast to traditional performance measures, decision curve analysis (DCA) can assess the utility of models for decision making. DCA plots net benefit (NB) at a range of clinically reasonable risk thresholds.
objectiveTo provide recommendations on interpreting and reporting DCA when evaluating prediction models. EVIDENCE ACQUISITION: We informally reviewed the urological literature to determine investigators' understanding of DCA. To illustrate, we use data from 3616 patients to develop risk models for high-grade prostate cancer (n=313, 9%) to decide who should undergo a biopsy. The baseline model includes prostate-specific antigen and digital rectal examination; the extended model adds two predictors based on transrectal ultrasound (TRUS). EVIDENCE SYNTHESIS: We explain risk thresholds, NB, default strategies (treat all, treat no one), and test tradeoff. To use DCA, first determine whether a model is superior to all other strategies across the range of reasonable risk thresholds. If so, that model appears to improve decisions irrespective of threshold. Second, consider if there are important extra costs to using the model. If so, obtain the test tradeoff to check whether the increase in NB versus the best other strategy is worth the additional cost. In our case study, addition of TRUS improved NB by 0.0114, equivalent to 1.1 more detected high-grade prostate cancers per 100 patients. Hence, adding TRUS would be worthwhile if we accept subjecting 88 patients to TRUS to find one additional high-grade prostate cancer or, alternatively, subjecting 10 patients to TRUS to avoid one unnecessary biopsy.
conclusionsThe proposed guidelines can help researchers understand DCA and improve application and reporting. PATIENT SUMMARY: Decision curve analysis can identify risk models that can help us make better clinical decisions. We illustrate appropriate reporting and interpretation of decision curve analysis.
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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.