ArticleStatistics in medicine2020
A causal framework for classical statistical estimands in failure-time settings with competing events.
Article in Statistics in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers, 1 of them a synthesis that pooled it.
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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
169 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Heterogeneity in design and analysis of ICU delirium randomized trials: a systematic review.Trials · 2021Pooled it
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- Effect of colonoscopy screening on risks of colorectal cancer and related death: instrumental variable estimation of per-protocol effects.European journal of epidemiology · 2025Trial
- Evaluating the effectiveness of systemic heparin during arteriovenous fistula creation by emulating a target trial.American journal of epidemiology · 2025Trial
- Effectiveness of treat-to-target cholesterol-lowering interventions on cardiovascular disease and all-cause mortality risk in the community-dwelling population: a target trial emulation.Nature communications · 2024Trial
- Comparative Effectiveness of Switching to Bictegravir From Dolutegravir-, Efavirenz-, or Raltegravir-Based Antiretroviral Therapy Among Individuals With HIV Who are Virologically Suppressed.Open forum infectious diseases · 2024Trial
- Bias of the additive hazard model in the presence of causal effect heterogeneity.Lifetime data analysis · 2024Trial
- Compliance-Adjusted Estimates of Aspirin Effects Among Older Persons in the ASPREE Randomized Trial.American journal of epidemiology · 2023Trial
- The Effect of Prenatal Treatments on Offspring Events in the Presence of Competing Events: An Application to a Randomized Trial of Fertility Therapies.Epidemiology (Cambridge, Mass.) · 2020Trial
- The effect of hypothetical interventions to limit weight gain on incident type 2 diabetes mellitus among people with HIV initiating antiretroviral therapy in the United States, 2012-2021.American journal of epidemiology · 2026Article
- Pooled Multinomial Logistic Regression for Parametric G-computation in the Presence of Competing Events.Epidemiology (Cambridge, Mass.) · 2026Article
- Joint non-linear dose-response associations of device-measured physical activity and cardiorespiratory fitness with cardiovascular disease: a cohort and Mendelian randomisation study.British journal of sports medicine · 2026Article
- Residual thromboembolic risk and outcomes of oral anticoagulation discontinuation after atrial fibrillation ablation: a target trial emulation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026Article
- Censoring, Competing Events, and Multistate Models: Comment on Beyersmann et al. "Hazards Constitute Key Quantities for Analyzing, Interpreting and Understanding Time-to-Event Data".Biometrical journal. Biometrische Zeitschrift · 2026Article
- Risk of type 2 diabetes mellitus after treatment with direct-acting antivirals for hepatitis C virus in people with HIV.AIDS (London, England) · 2026Observational
- Modeling treatment effects on absorbing outcomes in clinical trials: Leveraging longitudinal and ordinal data for efficiency gains.Statistical methods in medical research · 2026Article
- Improving the design of observational studies in orthopaedics: a practical guide to target trial emulation.International orthopaedics · 2026Review
- Causal effect on the number of life years lost due to a specific event: average treatment effect and variable importance.Lifetime data analysis · 2026Article
- Continuation Versus Discontinuation of Nonselective Beta-Blockers After Transjugular Intrahepatic Portosystemic Shunt Placement: A Real-World, Target-Trial Emulation Analysis.Journal of clinical medicine · 2026Article
109 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
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Abstract
In failure-time settings, a competing event is any event that makes it impossible for the event of interest to occur. For example, cardiovascular disease death is a competing event for prostate cancer death because an individual cannot die of prostate cancer once he has died of cardiovascular disease. Various statistical estimands have been defined as possible targets of inference in the classical competing risks literature. Many reviews have described these statistical estimands and their estimating procedures with recommendations about their use. However, this previous work has not used a formal framework for characterizing causal effects and their identifying conditions, which makes it difficult to interpret effect estimates and assess recommendations regarding analytic choices. Here we use a counterfactual framework to explicitly define each of these classical estimands. We clarify that, depending on whether competing events are defined as censoring events, contrasts of risks can define a total effect of the treatment on the event of interest or a direct effect of the treatment on the event of interest not mediated by the competing event. In contrast, regardless of whether competing events are defined as censoring events, counterfactual hazard contrasts cannot generally be interpreted as causal effects. We illustrate how identifying assumptions for all of these counterfactual estimands can be represented in causal diagrams, in which competing events are depicted as time-varying covariates. We present an application of these ideas to data from a randomized trial designed to estimate the effect of estrogen therapy on prostate cancer mortality.
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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.