In nested case-control studies, incidence density sampling is the time-dependent matching procedure to approximate hazard ratios. The cumulative incidence function can also be estimated if information from the full cohort is used. In the presence of competing events, however, the cumulative incidence function depends on the hazard of the disease of interest and on the competing events hazard. Using hospital-acquired infection as an example (full cohort), we propose a sampling method for nested case-control studies to estimate subdistribution hazard ratios. With further information on the full cohort, the cumulative incidence function for the event of interest can then be estimated as well.
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From 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.
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Correspondence: Martin Wolkewitz, Institute of Medical Biometry and Medical Informatics, Stefan-Meier-Str. 26, 79104 Freiburg, Germany. E-mail: firstname.lastname@example.org.