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

Li Wentian (), Cetin Sirin, Ulgen Ayse (), Cetin Meryem, Sivgin Hakan and Yang Yaning
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Li Wentian: The Robert S. Boas Center for Genomics and Human Genetics, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
Cetin Sirin: Department of Biostatistics, Faculty of Medicine, Amasya University, Amasya, Türkiye
Ulgen Ayse: Department of Biostatistics, Faculty of Medicine, Girne American University, Karmi, Cyprus
Cetin Meryem: Department of Microbiology, Faculty of Medicine, Amasya University, Amasya, Türkiye
Sivgin Hakan: Department of Internal Medicine, Faculty of Medicine, Tokat GaziosmanPasa University, Tokat, Türkiye
Yang Yaning: Department of Statistics and Finance, University of Science and Technology of China, Hefei, China

The International Journal of Biostatistics, 2024, vol. 20, issue 1, 43-56

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 )

Keywords: cause-specific hazard ratio; COVID-19; mutually exclusive events; time to hospital release (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1515/ijb-2022-0083

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