The DOI matches its Crossref record; 25 of the 26 references it cites were found in a registry or an index.
Survival Bias Associated with Time-to-Treatment Initiation in Drug Effectiveness Evaluation: A Comparison of Methods
Abstract
The authors compared five methods of studying survival bias associated with time-to-treatment initiation in a drug effectiveness study using medical administrative databases (1996-2002) from Quebec, Canada. The first two methods illustrated how survival bias could be introduced. Three additional methods were considered to control for this bias. Methods were compared in the context of evaluating statins for secondary prevention in elderly patients post-acute myocardial infarction who initiated statins within 90 days after discharge and those who did not. Method 1 that classified patients into users and nonusers at discharge resulted in an overestimation of the benefit (38% relative risk reduction at 1 year). In method 2, following users from the time of the first prescription and nonusers from a randomly selected time between 0 and 90 days attenuated the effect toward the null (10% relative risk reduction). Method 3 controlled for survival bias by following patients from the end of the 90-day time window; however, it suffered a major loss of statistical efficiency and precision. Method 4 matched prescription time distribution between users and nonusers at cohort entry. Method 5 used a time-dependent variable for treatment initiation. Methods 4 and 5 better controlled for survival bias and yielded similar results, suggesting a 20% risk reduction of recurrent myocardial infarction or death events.
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“A recent simulation study by Nelson et al.168 bolsters the rationale for training these composite models, showing that first-generation methylation ageing clocks do worse than random chance at identifying causal ageing loci due to cohort selection effects that occur in cross-sectional ageing cohorts169,170.”
From Measuring biological age using omics data (2022) · cites this paper as [170]
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Metadata
- Authors
- Zhou, Z., Rahme, E., Abrahamowicz, M., & Pilote, L.
- Affiliations
- McGill University (CA)
- Corresponding author
- Zhou, Zheng
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-09-28
- Volume
- 162
- Issue
- 10
- Pages
- 1016-1023
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2161515661
- Cited by
- 425
- References
- 26
- Citations by year
- 2026: 27 · 2025: 36 · 2024: 34 · 2023: 31 · 2022: 43 · 2021: 36 · 2020: 24 · 2019: 22 · 2018: 22 · 2017: 27 · 2016: 18 · 2015: 12 · 2014: 17 · 2013: 10 · 2012: 7
- FWCI
- 8.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- survivorship bias, time to treatment, statins, secondary prevention, acute myocardial infarction, elderly patients, reinfarction, time-varying covariates
- MeSH terms
- Aged, Aged, 80 and over, Drug Administration Schedule, Female, Follow-Up Studies, Humans, Male, Myocardial Infarction, Outcome and Process Assessment, Health Care, Drug Prescriptions, Quebec, Retrospective Studies, Cohort Studies, Bias, Survival Analysis, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Secondary Prevention
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