A Statistical Analysis of the Factors with Nonrandom Impact on the Survival Rate of Women with Breast Cancer, by Type of Medical Treatment

Author:

Kovtun N. V.ORCID,Motuziuk I. M.ORCID,Dumenko O. M.ORCID

Abstract

A statistical analysis of the factors with nonrandom impact of the survival rate of women with breast cancer, by type of medical treatment in Ukraine, was made using data from the National Cancer Register. The complexity and ambiguity of the problem related with the choice of a special treatment type, i. e. surgical treatment or combined surgical treatment, was emphasize. The combined surgical treatment is available in two options: as a combination of surgical treatment and radiation therapy and a combination of surgical treatment, radiation therapy and chemical therapy. The data on female patients who had medical treatment in the National Institute of Cancer used for a statistical analysis to reveal positive and negative results from each type of special medical treatment.  The need for the assumption on proportionality was substantiated, with its testing based on a graphic analysis by grouping factors. The obtained results led to the conclusion that the model could be extended by the categorical factors: type of treatment (grouping factor), type of surgical operation, phase of decease. The assessment was made based on analyzing the factors’ impact by type of medical treatment. It was demonstrated that the model could be extended by interaction effects that would enable for estimating the relative risk depending on a combination of the treatment group and the respective factor. None of the effects included in the model could prove to be statistically significant. It means that no conclusions could be made about the factors’ interactions by type of the medical treatment. The interpretation of all the other factors that proved to be significant was applied to all the population. The strongest projection weight in the model was with the factor of decease phase, followed by the type of medical treatment and, in equal proportions, by the age and the type of surgical operation. The results of checking the global test could demonstrate the feasibility of predicting the survival rate for the overall model with the significance level equal to 0.05. It was proved that adjuvant and chemical therapies could reduce the risks of the recurrence, but this result had not an ultimate statistical validity. Despite of the positive non-recurrence result, the survival rate by groups still reduces, being an obvious effect of the abovementioned groups of medical treatment.

Publisher

National Academy of Statistics Accounting and Audit

Subject

General Medicine

Reference13 articles.

1. Motuziuk, I. M., & Dumenko, O. M. (2020). Statystychnyi analiz faktoriv, shcho vplyvaiut na vyzhyvanist zhinok, khvorykh na rak hrudnoi zalozy, za vydamy spetsialnoho likuvannia [Statistical Analysis of Factors Influencing Survival of Women with Breast Cancer by Treatment Types]. Statystyka Ukrainy – Statistics of Ukraine, 1, 108–115. Doi: 10.31767/su. 1(88)2020.01.13

2. Lu, J., & Shen, D. (2014). Survival analysis approaches and new developments using SAS. Pharmaceutical Industry SAS Users Group Proceedings. Retrieved from https://www.pharmasug.org/proceedings/2014/PO/PharmaSUG-2014-PO02.pdf

3. Pro stvorennia ta vprovadzhennia medyko-tekhnolohichnykh dokumentiv zi standartyzatsii medychnoi dopomohy v systemi Ministerstva okhorony zdorovia Ukrainy: nakaz Ministerstva okhorony zdorovia Ukrainy vid 28.09.2012 r. № 751, stanom na 26.09.2018 r. [On the creation and implementation of medical and technological documents on the standardization of medical care in the system of the Ministry of Health of Ukraine: order of the Ministry of Health of Ukraine of September 28, 2012 No. 751, as of September 26, 2018]. www.dec.gov.ua.Retrieved from https://www.dec.gov.ua/wp-content/uploads/2019/11/751_1422_nakaz_moz.pdf [in Ukrainian].

4. Royston, P., Parmar, M. K., & Altman, D. G. (2008). Visualizing of survival in time-to-event studies: a compliment to Kaplan-Meier Plots. Journal of the National Cancer Institute, 100, 92–97. DOI:10.1093/jnci/djm265

5. Barton, B., & Peat, J. (2014). Medical statistics: a guide to data analysis and critical appraisal. (2nd ed.). Chichester, West Sussex; Hoboken, NJ: John Wiley & Sons, Ltd.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3