Comparison of nested case-control and survival analysis methodologies for analysis of time-dependent exposure
Open accessAbstract
Background: Epidemiological studies of exposures that vary with time require an additional level of methodological complexity to account for the time-dependence of exposure. This study compares a nested case-control approach for the study of time-dependent exposure with cohort analysis using Cox regression including time-dependent covariates. Methods: A cohort of 1340 subjects with four fixed and seven time-dependent covariates was used for this study. Nested case-control analyses were repeated 100 times for each of 4, 8, 16, 32, and 64 controls per case, and point estimates were compared to those obtained using Cox regression on the full cohort. Computational efficiencies were evaluated by comparing central processing unit times required for analysis of the cohort at sizes 1, 2, 4, 8, 16, and 32 times its initial size. Results: Nested case-control analyses yielded results that were similar to results of Cox regression on the full cohort. Cox regression was found to be 125 times slower than the nested case-control approach (using four controls per case). Conclusions: The nested case-control approach is a useful alternative for cohort analysis when studying time-dependent exposures. Its superior computational efficiency may be particularly useful when studying rare outcomes in databases, where the ability to analyze larger sample sizes can improve the power of the study.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The nested case-control design is commonly used in pharmacosurveillance research and provides estimates of effects that are consistent with those obtained from time to event analysis.
“The nested case-control design is commonly used in pharmacosurveillance research and provides estimates of effects that are consistent with those obtained from time to event analysis.67 68 69 70”
From Levothyroxine dose and risk of fractures in older adults: nested case-control study (2011) · cites this paper as [69]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 22 · Cited by 234
Research works printed but not linked: 14
- Mantel N Synthetic retrospective studies and related topics Biometrics 1973 29 479 486 4793136
- Lubin JH Extensions of analytic methods for nested and population-based incident case-control studies J Chronic Dis 1986 39 379 388 3700579 10.1016/0021-9681(86)90124-4 · DOI
- White E Hunt JR Casso D Exposure measurement in cohort studies: the challenges of prospective data collection Epidemiol Rev 1998 20 43 56 9762508
- Fisher LD Lin DY Time-dependent covariates in the Cox proportional-hazards regression model Annu Rev Public Health 1999 20 145 157 10352854 10.1146/annurev.publhealth.20.1.145 · DOI
- Essebag V Hadjis T Platt RW Pilote L Amiodarone and the risk of bradyarrhythmia requiring permanent pacemaker in elderly patients with atrial fibrillation and prior myocardial infarction J Am Coll Cardiol 2003 41 249 254 12535818 10.1016/S0735-1097(02)02709-2 · DOI
- Ury HK Efficiency of case-control studies with multiple controls per case: continuous or dichotomous data Biometrics 1975 31 643 649 1100136
- Pang D A relative power table for nested matched case-control studies Occup Environ Med 1999 56 67 69 10341749 PMC1757658
- Lee JY Uses of clinical databases Am J Med Sci 1994 308 58 62 8010340
- Baron JA Weiderpass E An introduction to epidemiological research with medical databases Ann Epidemiol 2000 10 200 204 10854954 10.1016/S1047-2797(00)00039-9 · DOI
- Mitchell JB Bubolz T Paul JE Pashos CL Escarce JJ Muhlbaier LH Wiesman JM Young WW Epstein RS Javitt JC Using Medicare claims for outcomes research Med Care 1994 32 JS38 51 8028412
- Tamblyn R Lavoie G Petrella L Monette J The use of prescription claims databases in pharmacoepidemiological research: the accuracy and comprehensiveness of the prescription claims database in Quebec J Clin Epidemiol 1995 48 999 1009 7775999 10.1016/0895-4356(94)00234-H · DOI
- Langholz B Thomas D Xiang A Stram D Latency analysis in epidemiologic studies of occupational exposures: application to the Colorado Plateau uranium miners cohort Am J Ind Med 1999 35 246 256 9987557
- Rachet B Sasco AJ Abrahamowicz M Benyamine D Prognostic factors for mortality in nasopharyngeal cancer: accounting for time-dependence of relative risks Int J Epidemiol 1998 27 772 780 9839732 10.1093/ije/27.5.772 · DOI
- Quantin C Abrahamowicz M Moreau T Bartlett G MacKenzie T Tazi MA Lalonde L Faivre J Variation over time of the effects of prognostic factors in a population-based study of colon cancer: comparison of statistical models Am J Epidemiol 1999 150 1188 1200 10588079
- Authors
- Essebag, V., Platt, R. W., Abrahamowicz, M., & Pilote, L.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- McGill University (CA)
- McGill University Health Centre (CA)
- Corresponding author
- Pilote, Louise
- Venue
- BMC Medical Research Methodology
- Published
- 2005-01-25
- Volume
- 5
- Issue
- 1
- Pages
- 5-5
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC548149
- OpenAlex
- W1775522749
- Cited by
- 234
- References
- 22
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 16 · 2023: 11 · 2022: 21 · 2021: 12 · 2020: 14 · 2019: 7 · 2018: 18 · 2017: 6 · 2016: 16 · 2015: 14 · 2014: 22 · 2013: 12 · 2012: 9
- FWCI
- 3.81
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Medical Research Methodology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- eScholarship@McGill (McGill) (submittedVersion)
- Funders
- McGill University
- Canadian Institutes of Health Research
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- nested case-control design, time-varying exposure, Cox proportional hazards model, time-varying covariates, computational efficiency, rare outcomes, cohort analysis, method comparison
- MeSH terms
- Aged, Amiodarone, Anti-Arrhythmia Agents, Atrial Fibrillation, Female, Humans, Male, Pacemaker, Artificial, Quebec, Risk Factors, Time Factors, Cohort Studies, Proportional Hazards Models, Survival Analysis, Case-Control Studies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
