Kaplan-Meyer Survival Curves: Simulation Technique
The right censoring of survival data, being the most conventional method of research, is analyzed. The patient survival is explored in a time span that is shorter in fact than the actual survival time. However, when the actual survival time is unknown, the proxy of the observable survival time will be used for estimating the actual survival time.
The algorithm for estimation of survival probabilities is demonstrated by data on 20 patients during six months, with visualizing the technique of simulating Kaplan – Meyer curves by categorical variables (method of treatment and gender) using GraphPad Prism software for statistical data processing. It is argued that Kaplan – Meyer curves could provide an effective tool in simulating the patient survival in case of COVID-19 by various criteria of grouping: gender (male and female); treatment method; associated diseases (diabetes and others); age group; vaccinated or not vaccinated patients etc.
The significance of differences between survival curves of patienst in various groups can be found using Log-Rank test, Gehan – Wilcoxon test, Mantel – Cox test and others. The results of tests produced on the basis of data on 42 patients ill with leukemia show significant differences in the survival between two groups of patients. This confirms the assumption that the new method of treatment is more effective than the conventional one. The main deficiency of the nonparametric method of Kaplan – Meyer is that it is incapable to build curves by several categorical variables. The main advantages of Cox regression based on the Cox proportional hazards model are demonstrated.
2. Petrie A., & Sabin C. (2005). Medical Statistics at a Glance. Oxford.
3. Kleinbaum David G., & Klein M. Survival Analysis: A Self-Learning Text. Third Edition. Retrieved from uop.edu.pk/ocontents/survival-analysis-self-learning-book.pdf
4. N. V. Kovtun, I. M. Motuziuk, & R. O. Ganzha (2018). Vykorystannia rehresii Koksa dlia prohnozuvannia vyzhyvanosti zhinok z mnozhynnymy zloiakisnymy novoutvorenniamy [Using Cox Regression to Forecast the Survival of Women with Multiple Malignant Neoplasms]. Statystyka Ukrainy – Statistics of Ukraine, 4, 65–71. https://doi.org/10.31767/su. 4(83)2018.04.08 [in Ukrainian].
5. Rumyantsev P. O., Sayenko V. A., Rumyantseva U. V., & Chekin S.Yu. (2009). Statisticheskie metodyi analiza v klinicheskoy praktike. Chast. 2. Analiz vyizhivaemosti i mnogomernaya statistika [Statistical methods for the analyses in clinical practice. Part 2. Survival analysis and multivariate statistics]. Problemyi Endokrinokogii – Problems of Endocrinology, 55(6), 48–56. https://doi.org/10.14341/probl200955648-56 [In Russian].
6. Fedorenko Z. P., Hulak L. O., Mykhailovych Yu. Y., Horokh Ye. L., Ryzhov A. Yu., Sumkina O. V. et al. (2020). Rak v Ukraini, 2018–2019. Zakhvoriuvanist, smertnist, pokaznyky onkolohichnoi sluzhby [Cancer in Ukraine, 2018–2019. Morbidity, mortality, indicators of the oncological service]. Natsionalnyi instytut raku. Biuleten Natsionalnoho kantser-reiestru Ukrainy No 21 – National Institute of Cancer. Bulletin of the National Cancer Register of Ukraine No 21. Kyiv [in Ukrainian].
7. Fedorenko Z. P., Hulak L. O., Horokh E. L., Ryzhov A. Yu., Sumkina O. V., & Kutsenko L. B. (2015). Zastosuvannia pokaznyka populiatsiinoi vyzhyvanosti khvorykh na zloiakisni novoutvorennia yak kryteriiu otsinky yakosti nadannia onkolohichnoi dopomohy naselenniu Ukrainy: medodychnyi posibnyk [Using the index of the population survival of the persons ill with malignant neoplasms as the criterion for quality evaluation of the oncological aid provided to the Ukrainian population: a guidebook]. Kyiv: “Direct Line” [in Ukrainian].
8. Leukemia Dataset. Retrieved from https://statweb.stanford.edu/~olshen/hrp262spring01/spring01Assignments/anderson.txt
(Data extracted from: Freireich et al. (1963). The effect of 6-mercaptopurine on the duration of steroid-induced remissions in acute leukemia: A Model for Evaluation of Other Potentially Useful Therapy. Blood, vol. 21, issue 6, 699–716. https://doi.org/10.1182/BLOOD.V21.6.699.699).
Abstract views: 32 PDF Downloads: 26
This work is licensed under a Creative Commons Attribution 4.0 International License.