ArticleBMC medical research methodology2017
Statistical methods for elimination of guarantee-time bias in cohort studies: a simulation study.
Article in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed, 62 citations in OpenAlex.
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- Common analysis pitfalls in longitudinal ctDNA studies: lead time, sensitivity and immortal time bias.EBioMedicine · 2026Review
- Inequitable Access to Catheter Ablation for Atrial Fibrillation and Adverse Outcomes in a Publicly Funded Healthcare System.CJC open · 2026Article
- Association of early serial serum NLRP3 measurements with 28-day mortality in sepsis: a single-center retrospective landmark cohort study.BMC infectious diseases · 2026Article
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- Association of Immune-Related Adverse Events and the Efficacy of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer: Adjusting for Immortal Time Bias.Thoracic cancer · 2026Article
- Very Early-Stage Detection Is Associated With Improved Survival in Patients With Unifocal Hepatocellular Carcinoma.Alimentary pharmacology & therapeutics · 2026Article
- Comparative cardiovascular risk of sulfonylureas with low- and high-affinities for cardiac mitochondrial adenosine triphosphate-sensitive potassium channels versus dipeptidyl peptidase-4 inhibitors in patients with type 2 diabetes: A cohort study.Diabetes, obesity & metabolism · 2025Article
- Risk of Alzheimer's disease and Parkinson's disease following androgen deprivation therapy in a real world nationwide cohort.Scientific reports · 2025Article
- Cytomegalovirus reactivation in the lower respiratory tract as an independent risk factor for mortality in critically Ill patients.Critical care (London, England) · 2025Article
- Addressing immortal time bias in precision medicine: Practical guidance and methods development.Health services research · 2025Article
- Optimal Duration of Consolidation Durvalumab Following Chemoradiotherapy in Stage III Non-Small Cell Lung Cancer: A Multi-institutional Retrospective Study.Targeted oncology · 2025Article
- Effect of choline alfoscerate in older adult patients with dementia: an observational study from the claims data of national health insurance.BMC geriatrics · 2024Observational
- Multiple immune-related adverse events secondary to checkpoint inhibitor therapy in patients with advanced cancer: association with treatment effectiveness.Frontiers in oncology · 2024Article
- Risk of breakthrough COVID-19 after vaccination among people with multiple sclerosis on disease-modifying therapies.Journal of neurology · 2023Article
- Cytoreductive Nephrectomy for Patients with Metastatic Sarcomatoid and/or Rhabdoid Renal Cell Carcinoma Treated with Immune Checkpoint Therapy.European urology focus · 2023Article
- Diabetes, metformin use, and survival in esophageal cancer: a population-based cohort study.JNCI cancer spectrum · 2023Article
- Cutaneous immune-related adverse events are associated with longer overall survival in advanced cancer patients on immune checkpoint inhibitors: A multi-institutional cohort study.Journal of the American Academy of Dermatology · 2023Article
- Prognostic Impact of Elevation of Cancer Antigen 15-3 (CA15-3) in Patients With Early Breast Cancer With Normal Serum CA15-3 Level.Journal of breast cancer · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAspirin has been considered to be beneficial in preventing cardiovascular diseases and cancer. Several pharmaco-epidemiology cohort studies have shown protective effects of aspirin on diseases using various statistical methods, with the Cox regression model being the most commonly used approach. However, there are some inherent limitations to the conventional Cox regression approach such as guarantee-time bias, resulting in an overestimation of the drug effect. To overcome such limitations, alternative approaches, such as the time-dependent Cox model and landmark methods have been proposed. This study aimed to compare the performance of three methods: Cox regression, time-dependent Cox model and landmark method with different landmark times in order to address the problem of guarantee-time bias.
methodsThrough statistical modeling and simulation studies, the performance of the above three methods were assessed in terms of type I error, bias, power, and mean squared error (MSE). In addition, the three statistical approaches were applied to a real data example from the Korean National Health Insurance Database. Effect of cumulative rosiglitazone dose on the risk of hepatocellular carcinoma was used as an example for illustration.
resultsIn the simulated data, time-dependent Cox regression outperformed the landmark method in terms of bias and mean squared error but the type I error rates were similar. The results from real-data example showed the same patterns as the simulation findings.
conclusionsWhile both time-dependent Cox regression model and landmark analysis are useful in resolving the problem of guarantee-time bias, time-dependent Cox regression is the most appropriate method for analyzing cumulative dose effects in pharmaco-epidemiological studies.
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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 OpenQuestion graph.