Cox Proportional Hazard Model for Survival Time of Neonatal Mortality in Neonatal Intensive Care Unit of Hospitals in River Nile State-Sudan
- 1 Faculty of Mathematical Science, El-Fashir University, El-Fashir, Sudan
- 2 Faculty of Economics & Political Sciences, Omdurman Islamic University, Omdurman, Sudan
Abstract
Cox Proportional Hazard model is a popular statistical technique for exploring the relationship between the survival time of neonates and several explanatory variables. It provides an estimate of the study variables’ effect on survival after adjustment for other explanatory variables, and allows us to estimate the hazard (or risk) of death of newborn in NICU of hospitals in River Nile State-Sudan for the period (2018-2020). Study Data represented (neonate gender, mode of delivery, birth type, neonate weight, resident type, gestational age, and survival time). Kaplan-Meier method is used to estimate survival and hazard function for survival times of newborns that have not completed their first month. Of 700 neonates in the study area, 25% of them died during 2018-2020. Variables of interest that had a significant effect on neonatal death by Cox Proportional Hazard Model analysis were neonate weight, resident type, and gestational age. In Cox Proportional Hazard Model analysis all the variables of interest had an effect on neonatal death, but the variables with a significant effect included, weight of neonate, resident type and gestational age.
- Hanagal, D.D. (2019) Modeling Survival Data Using Frailty Models. 2nd Edition, Springer Nature, East Singapore, 3-4, 12-13.
- Kallen, A. (2011) Understanding Biostatistics. 1st Edition, John Wiley & Sons, Ltd., United Kindom, 290.
- Collett, D. (2003) Modeling Survival Data in Medical Research: Texts in Statistical Science, 2nd Edition, Chapman & Hall, London, 2-3, 30-31.
- WHO Library (2006) Neonatal and Perinatal Mortality: Country, Regional and Global Estimates. World Health Organization, Switzerland, 7-8.
- Gomella, T.L., Eyal, F.G. and Mohammed, F.B. (2020) Neonatology: Management, Procedures, On-Call Problems, Disease and Drugs. 8th Edition, Mc Graw-Hill Education, Alabama, 103.
- Kleinbaum, D.G. and Klein, M. (2005) Survival Analysis: A Self-Learning Text. 2nd Edition, Springer Science + Business Media, Inc., New York, 9, 100-101.
- Kim, J.S. and Dailey, R.J. (2008) Biostatistics for Oral Health Care. 2nd Edition, Blackwell Munksqard, Vectoria, 283. https://doi.org/10.1002/9780470388303
- Chernick, M.R. and Friis, R.H. (2003) Introductory Biostatistics for the Health Sciences: Modern Applications Including Bootstrap. 2nd Edition, John Wiley & Sons, Inc., New Jersy, 341 https://doi.org/10.1002/0471458716
- Le, C.T. (2003) Introductory Biostatistics. 2nd Edition, John Wiley & Sons, Inc., New Jersy, 384-385.
- Collett, D. (2003) Modeling Survival Data in Medical Research: Texts in Statistical Science. 2nd Edition, Chapman & Hall, London, 56-58.
- Turkson, A.J., et al. (2021) The Cox Proportional Hazard Regression Model vis-à-vis ITN-Factor Impact on Mortality Due to Malaria. Open Journal of Statistics, 11, 931-962. https://doi.org/10.4236/ojs.2021.116055
- Obite, C.B., et al. (2020) A Cox Proportional Hazard Model Approach to Age at First Sexual Intercourse in Nigeria. Open Journal of Statistics, 10, 252-260. https://doi.org/10.4236/ojs.2020.102018
- Rosner, B. (2000) Fundamentals of Biostatistics. 5th Edition, Brooks/Cole, United States, 726-727.
- Marschner, I.C. (2005) Inference Principles for Biostatistics. 2nd Edition, Chapman & Hall, New York, 89-91.