ReviewMedical decision making : an international journal of the Society for Medical Decision Making2018
A Tutorial on Evaluating the Time-Varying Discrimination Accuracy of Survival Models Used in Dynamic Decision Making.
Review in Medical decision making : an international journal of the Society for Medical Decision Making, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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.
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
34 citing papers in PubMed, 70 citations in OpenAlex.
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- Enhanced dynamic risk stratification of smoldering multiple myeloma.Nature medicine · 2026Article
- Artificial Intelligence driven prediction of multiple outcomes in older adults with coronary heart disease.The Gerontologist · 2026Article
- Immune Ageing Clocks: A Methods-Oriented Review of Tasks, Modalities, Models, and Recalibration.Cells · 2026Review
- Time-Dependent Predictive Accuracy Metrics in the Context of Interval Censoring and Competing Risks.Biometrical journal. Biometrische Zeitschrift · 2026Article
- Integrated circulating tumor DNA-based prognostic algorithm for limited stage small-cell lung cancer under definitive chemoradiotherapy and utility in consolidation immunotherapy benefit prediction.Cell communication and signaling : CCS · 2025Article
- NLRP3-inflammasome Related Genes as Emerging Biomarkers and Therapeutic Targets in Psoriasis.Inflammation · 2025Article
- Timing and Predictive Value of Clinical Conditions Preceding Multiple Sclerosis in the UK Biobank.Annals of clinical and translational neurology · 2025Article
- Dynamic nomogram for predicting long-term survival in patients with brain abscess.Chinese neurosurgical journal · 2025Article
- Association of nonstandardized model for end-stage liver disease score exceptions with waitlist mortality in adult liver transplant candidates.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2025Article
- Improving pressure injury risk assessment using real-world data from skilled nursing facilities: A cohort study.International wound journal · 2024Article
- Prognoses Associated With Palliative Performance Scale Scores in Modern Palliative Care Practice.JAMA network open · 2024Article
- Development and Standardization of an Osteoradionecrosis Classification System in Head and Neck Cancer: Implementation of a Risk-Based Model.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2024Article
- Observational
- Mortality prediction and influencing factors for intensive care unit patients with acute tubular necrosis: random survival forest and cox regression analysis.Frontiers in pharmacology · 2024Article
- Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2023Article
- Using Machine Learning to Leverage Biomarker Change and Predict Colorectal Cancer Recurrence.JCO clinical cancer informatics · 2023Article
- Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs.Nature communications · 2023Article
- Copula modeling for the estimation of measures of marker classification and predictiveness performance with survival outcomes.Statistical methods in medical research · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Many medical decisions involve the use of dynamic information collected on individual patients toward predicting likely transitions in their future health status. If accurate predictions are developed, then a prognostic model can identify patients at greatest risk for future adverse events and may be used clinically to define populations appropriate for targeted intervention. In practice, a prognostic model is often used to guide decisions at multiple time points over the course of disease, and classification performance (i.e., sensitivity and specificity) for distinguishing high-risk v. low-risk individuals may vary over time as an individual's disease status and prognostic information change. In this tutorial, we detail contemporary statistical methods that can characterize the time-varying accuracy of prognostic survival models when used for dynamic decision making. Although statistical methods for evaluating prognostic models with simple binary outcomes are well established, methods appropriate for survival outcomes are less well known and require time-dependent extensions of sensitivity and specificity to fully characterize longitudinal biomarkers or models. The methods we review are particularly important in that they allow for appropriate handling of censored outcomes commonly encountered with event time data. We highlight the importance of determining whether clinical interest is in predicting cumulative (or prevalent) cases over a fixed future time interval v. predicting incident cases over a range of follow-up times and whether patient information is static or updated over time. We discuss implementation of time-dependent receiver operating characteristic approaches using relevant R statistical software packages. The statistical summaries are illustrated using a liver prognostic model to guide transplantation in primary biliary cirrhosis.
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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.