A composite ranking of risk factors for COVID-19 time-to-event data from a Turkish cohort. (June 2022)
- Record Type:
- Journal Article
- Title:
- A composite ranking of risk factors for COVID-19 time-to-event data from a Turkish cohort. (June 2022)
- Main Title:
- A composite ranking of risk factors for COVID-19 time-to-event data from a Turkish cohort
- Authors:
- Ulgen, Ayse
Cetin, Sirin
Cetin, Meryem
Sivgin, Hakan
Li, Wentian - Abstract:
- Abstract: Having a complete and reliable list of risk factors from routine laboratory blood test for COVID-19 disease severity and mortality is important for patient care and hospital management. It is common to use meta-analysis to combine analysis results from different studies to make it more reproducible. In this paper, we propose to run multiple analyses on the same set of data to produce a more robust list of risk factors. With our time-to-event survival data, the standard survival analysis were extended in three directions. The first is to extend from tests and corresponding p-values to machine learning and their prediction performance. The second is to extend from single-variable to multiple-variable analysis. The third is to expand from analyzing time-to-decease data with death as the event of interest to analyzing time-to-hospital-release data to treat early recovery as a meaningful event as well. Our extension of the type of analyses leads to ten ranking lists. We conclude that 20 out of 30 factors are deemed to be reliably associated to faster-death or faster-recovery. Considering correlation among factors and evidenced by stepwise variable selection in random survival forest, 10 ~ 15 factors seem to be able to achieve the optimal prognosis performance. Our final list of risk factors contain calcium, white blood cell and neutrophils count, urea and creatine, d -dimer, red cell distribution widths, age, ferritin, glucose, lactate dehydrogenase, lymphocyte,Abstract: Having a complete and reliable list of risk factors from routine laboratory blood test for COVID-19 disease severity and mortality is important for patient care and hospital management. It is common to use meta-analysis to combine analysis results from different studies to make it more reproducible. In this paper, we propose to run multiple analyses on the same set of data to produce a more robust list of risk factors. With our time-to-event survival data, the standard survival analysis were extended in three directions. The first is to extend from tests and corresponding p-values to machine learning and their prediction performance. The second is to extend from single-variable to multiple-variable analysis. The third is to expand from analyzing time-to-decease data with death as the event of interest to analyzing time-to-hospital-release data to treat early recovery as a meaningful event as well. Our extension of the type of analyses leads to ten ranking lists. We conclude that 20 out of 30 factors are deemed to be reliably associated to faster-death or faster-recovery. Considering correlation among factors and evidenced by stepwise variable selection in random survival forest, 10 ~ 15 factors seem to be able to achieve the optimal prognosis performance. Our final list of risk factors contain calcium, white blood cell and neutrophils count, urea and creatine, d -dimer, red cell distribution widths, age, ferritin, glucose, lactate dehydrogenase, lymphocyte, basophils, anemia related factors (hemoglobin, hematocrit, mean corpuscular hemoglobin concentration), sodium, potassium, eosinophils, and aspartate aminotransferase. Graphical Abstract: ga1 Highlights: An "intra-data" meta analysis is carried out by using prediction performance, being multi-variable, and utilizing time-to-release information. About 20 blood test factors are associated with COVID-19 severity (or mildness) and mortality, consistent with other reports. … (more)
- Is Part Of:
- Computational biology and chemistry. Volume 98(2022)
- Journal:
- Computational biology and chemistry
- Issue:
- Volume 98(2022)
- Issue Display:
- Volume 98, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 98
- Issue:
- 2022
- Issue Sort Value:
- 2022-0098-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-06
- Subjects:
- COVID-19 -- Survival analysis -- Competing risks -- Composite ranking
Chemistry -- Data processing -- Periodicals
Biology -- Data processing -- Periodicals
Biochemistry -- Data processing
Biology -- Data processing
Molecular biology -- Data processing
Periodicals
Electronic journals
542.85 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14769271 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compbiolchem.2022.107681 ↗
- Languages:
- English
- ISSNs:
- 1476-9271
- Deposit Type:
- Legaldeposit
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