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Nested case-control studies in cohorts with competing events.

Martin Wolkewitz1, Ben S Cooper, Mercedes Palomar-Martinez

  • 1From the aInstitute of Medical Biometry and Medical Informatics, University of Freiburg, Freiburg, Germany; bFreiburg Center for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany; cCentre for Clinical Vaccinology and Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom; dMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; eHospital Universitari Arnau de Vilanova, Lleida, Spain; fUniversitat Autónoma de Barcelona, Barcelona, Spain; gService of Intensive Care Medicine, Hospital de Galdakao-Usansolo, Bizkaia, Spain; and hService of Intensive Care Medicine, Parc de Salut Mar, Barcelona, Spain.

Epidemiology (Cambridge, Mass.)
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Summary

Nested case-control studies can estimate subdistribution hazard ratios using a novel sampling method. This approach, demonstrated with hospital-acquired infections, also allows cumulative incidence function estimation with full cohort data.

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Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Nested case-control studies commonly use incidence density sampling to approximate hazard ratios.
  • Estimating cumulative incidence functions typically requires full cohort data.
  • Competing events complicate cumulative incidence function estimation in cohort studies.

Purpose of the Study:

  • To propose a novel sampling method for nested case-control studies to estimate subdistribution hazard ratios.
  • To demonstrate the method using hospital-acquired infection as an example.
  • To enable cumulative incidence function estimation for the event of interest using full cohort data.

Main Methods:

  • A new sampling method for nested case-control studies is proposed.
  • The method is applied to data on hospital-acquired infections.
  • Full cohort information is utilized for cumulative incidence function estimation.

Main Results:

  • The proposed sampling method allows for the estimation of subdistribution hazard ratios in nested case-control studies.
  • The approach facilitates the estimation of cumulative incidence functions when competing events are present.

Conclusions:

  • The novel sampling method enhances nested case-control study capabilities for analyzing time-to-event data with competing risks.
  • This methodology provides a robust way to estimate both subdistribution hazards and cumulative incidence functions.