Sampling designs for rare time-dependent exposures: a comparison of the nested exposure case-control design and exposure density sampling
Abstract: In extensive cohort studies, the ascertainment of covariate information on all individuals can be challenging. In hospital epidemiology, an additional issue is often the time-dependency of the exposure of interest. We revisit and compare two sampling designs constructed for rare time-dependent exposures and possibly common outcomes – the nested exposure case-control design and exposure density sampling. Both designs enable efficient hazard ratio estimation by sampling all exposed individuals but only a small fraction of the unexposed ones. Moreover, they account for time-dependent exposure to avoid immortal time bias. We evaluate and compare their performance using data of patients hospitalised in the neuro-intensive care unit at the Burdenko Neurosurgery Institute in Moscow, Russia. Three different types of hospital-acquired infections with different prevalence are considered. Additionally, inflation factors, a primary performance measure, are discussed. We enhance both designs to allow for a competitive analysis of combined and competing endpoints compared to the full cohort approach while substantially reducing the amount of necessary information. Nonetheless, exposure density sampling outperforms the nested exposure case-control design concerning efficiency and accuracy in most considered settings
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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Epidemiology and infection. - 149 (2021) , e122, ISSN: 1469-4409
- Ereignis
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Veröffentlichung
- (wo)
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Freiburg
- (wer)
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Universität
- (wann)
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2021
- Urheber
- DOI
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10.1017/s095026882100090x
- URN
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urn:nbn:de:bsz:25-freidok-2180827
- Rechteinformation
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:57 MESZ
Datenpartner
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Beteiligte
- Feifel, Jan
- Cube, Maja von
- Ohneberg, Kristin
- Ershova, Ksenia
- Wolkewitz, Martin
- Beyersmann, Jan
- Schumacher, Marc
- Universität
Entstanden
- 2021
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