Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events

Li, W, Cetin, S, Ulgen, A ORCID: https://orcid.org/0000-0002-0872-667X, Cetin, M, Sivgin, H and Yang, Y, 2023. Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events. The International Journal of Biostatistics. ISSN 1557-4679

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Abstract

COVID-19 survival data presents a special situation where not only the time-to-event period is short, but also the two events or outcome types, death and release from hospital, are mutually exclusive, leading to two cause-specific hazard ratios (csHR d and csHR r ). The eventual mortality/release outcome is also analyzed by logistic regression to obtain odds-ratio (OR). We have the following three empirical observations: (1) The magnitude of OR is an upper limit of the csHR d : |log(OR)| ≥ |log(csHR d )|. This relationship between OR and HR might be understood from the definition of the two quantities; (2) csHR d and csHR r point in opposite directions: log(csHR d ) ⋅ log(csHR r ) < 0; This relation is a direct consequence of the nature of the two events; and (3) there is a tendency for a reciprocal relation between csHR d and csHR r : csHR d ∼ 1/csHR r . Though an approximate reciprocal trend between the two hazard ratios is in indication that the same factor causing faster death also lead to slow recovery by a similar mechanism, and vice versa, a quantitative relation between csHR d and csHR r in this context is not obvious. These results may help future analyses of data from COVID-19 or other similar diseases, in particular if the deceased patients are lacking, whereas surviving patients are abundant.

Item Type:	Journal article
Publication Title:	The International Journal of Biostatistics
Creators:	Li, W., Cetin, S., Ulgen, A., Cetin, M., Sivgin, H. and Yang, Y.
Publisher:	Walter de Gruyter GmbH
Date:	3 April 2023
ISSN:	1557-4679
Identifiers:	Number Type 10.1515/ijb-2022-0083 DOI 1747973 Other
Rights:	© 2023 Walter de Gruyter GmbH, Berlin/Boston.
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	02 May 2023 12:56
Last Modified:	03 Apr 2024 03:00
URI:	https://irep.ntu.ac.uk/id/eprint/48863

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