ArticleAmerican journal of epidemiology2016
Comparison of Statistical Approaches for Dealing With Immortal Time Bias in Drug Effectiveness Studies.
Article in American journal of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses 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.
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
56 citing papers in PubMed, 2 syntheses or guidelines pooled it, 114 citations in OpenAlex.
- Identifying, handling and impact of immortal time bias on addressing treatment effects in observational studies using routinely collected data.BMC medical research methodology · 2025Pooled it
- Aspirin, metformin, and statin use on the risk of gastric cancer: A nationwide population-based cohort study in Korea with systematic review and meta-analysis.Cancer medicine · 2022Pooled it
- Mortality in homeless people enrolled in the French housing first randomized controlled trial: a secondary outcome analysis of predictors and causes of death.BMC public health · 2021Trial
- Modality-specific survival outcomes of biomarker-matched therapy in unresected non-small cell lung cancer: a clinicogenomic cohort study.Translational lung cancer research · 2026Article
- Empowering clinical trial design with agentic intelligence and real-world data.Nature communications · 2026Article
- Inequitable Access to Catheter Ablation for Atrial Fibrillation and Adverse Outcomes in a Publicly Funded Healthcare System.CJC open · 2026Article
- Long-term mortality and causes of death after venous thromboembolism: findings from the Atherosclerosis Risk in Communities Cohort Study.Journal of thrombosis and haemostasis : JTH · 2026Article
- Article
- Methodological Considerations for CAUTI Risk Prediction in Stroke Patients [Letter].International journal of general medicine · 2026Article
- Requiring continuous enrollment during follow-up? A call for robust research methods.Journal of managed care & specialty pharmacy · 2025Article
- Bariatric metabolic surgery and cancer risk: Target trial emulation using iterative time distribution matching.Biomolecules & biomedicine · 2025Article
- Long-Term Outcomes Following Catheter-Based Therapies in Older Adults With Acute Pulmonary Embolism.JACC. Advances · 2025Article
- Glucocorticoid-induced hyperglycaemia in hospitalised adults: A matched cohort study (2013-2023).Diabetes, obesity & metabolism · 2025Article
- Simultaneously Dealing With Immortal Time Bias and Residual Confounding: A Case Study of a High-Dimensional Propensity Score Approach With a Nested Case-Control Framework in Multiple Sclerosis Research.Pharmacoepidemiology and drug safety · 2025Article
- Direct-Acting Antivirals and Risk of Hepatitis C Extrahepatic Manifestations.JAMA network open · 2025Article
- Cytomegalovirus reactivation in the lower respiratory tract as an independent risk factor for mortality in critically Ill patients.Critical care (London, England) · 2025Article
- Outcomes of Discontinuing Long-Term Opioid Therapy among Older Cancer Survivors in Long-Term Care Settings.Journal of the American Medical Directors Association · 2025Article
- Association of clinical signs of possible serious bacterial infections identified by community health workers with mortality of young infants in South Asia: a prospective, observational cohort study.EClinicalMedicine · 2025Article
- Addressing immortal time bias in precision medicine: Practical guidance and methods development.Health services research · 2025Article
- Illustrating the structures of bias from immortal time using directed acyclic graphs.International journal of epidemiology · 2024Article
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5 authors.
Funding
Abstract
In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time-distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = -0.002, mean squared error = 0.025; PTDM: bias = -1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995-2008).
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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 Socratic graph.