全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Survival Rate Analysis on Breast Cancer Cases at Univesity College Hospital, Ibadan, Nigeria

DOI: 10.4236/ojs.2022.122017, PP. 238-260

Keywords: Survival Rate, Breast Cancer, Kaplan-Meier Estimator, Log-Rank Test and Multivariate Cox Regression

Full-Text   Cite this paper   Add to My Lib

Abstract:

Breast cancer is one of the leading diseases that affect women’s lives. It affects their lives in so many ways by denying them the required standard of health needed to carry out all of their daily activities for some days, weeks, months or years before eventually causing death. This research estimates the survival rate of breast cancer patients and investigates the effects of stage of tumor, gender, age, ethnic group, occupation, marital status and type of cancer upon the survival of patients. Data used for the study were extracted from the case file of patients in the Radiation Oncology Department, University College Hospital, Ibadan using a well-structured pro forma in which 74 observations were censored and 30 events occurred. The Kaplan-Meier estimator was used to estimate the overall survival probability of breast cancer patients following their recruitment into the study and determine the mean and median survival times of breast cancer patients following their time of recruitment into the study. Since there are different groups with respect to the stages of tumor at the time of diagnosis, the log-rank test was used to compare the survival curve of the stages of tumor with considering p-values below 0.05 as statistically significant. Multivariate Cox regression was used to investigate the effects of some variables on the survival of patients. The overall cumulative survival probability obtained is 0.175 (17.5%). The overall estimated mean time until death is 28.751 weeks while the median time between admission and death is 23 weeks. As the p-value (0.000032) of the log-rank test for comparing stages of tumor is less than 0.05, it is concluded that there is significant evidence of a difference in survival times for the stages of tumor. The survival function plot for the stages of tumor shows that patients with stage III tumor are less likely to survive. From the estimated mean time until death for the stages of tumor, it was deduced that stage I tumor patients have an increased chance of survival. Types of cancer, gender, marital status, ethnic group, occupation and patient’s age at entry into the study are not important predictors of chances of survival.

References

[1]  National Breast Cancer Foundation (2016) Breast Cancer Prevention and Control.
[2]  Danny, R.Y., Susanna, M.C. and Peter, D.B. (2008) Incidence and Mortality of Female Breast Cancer in the Asian Pacific Region.
[3]  Globacon (2008) Estimates of World Wide Burden of Cancer. Pubmed.
[4]  World Health Reports (2008) Primary Health Care: Now More than Ever.
https://www.who.int
[5]  Boyle, P. and Levin, B. (2008) World Cancer Report 2008. International Agency for Research on Cancer, Lyon.
[6]  Johan, L.D. (2012) American Joint Committee on Cancer/International Union against Cancer Staging System for Adenocarcinoma of the Stomach: Increased Complexity without Clear Improvement in Predictive Accuray.
[7]  Jedy-Agba, E., Curado, M.P., Ogunbiyi, O., Oga, E., Fabowale, T., Igbinoba, F., Osubor, G., Out, T., Kumai, H., Koechlin, A., Osinubi, P., Dakum, P., Blattner, W. and Adebamowo, C.A. (2012) Cancer Incidence in Nigeria: A Report from Population-Based Cancer Registries. Cancer Epidemiology, 36, e271-e278.
https://doi.org/10.1016/j.canep.2012.04.007
[8]  Ntekim, A., Nuhu, F.T. and Campbell, O.B. (2009) Breast Cancer in Young Female in Ibadan, Nigeria. 242-246.
[9]  Coleman, M.P., Quaresma, M., Berrino, F., Lutz, J.M., De-Angelis, R., Capocaccia, R., Balli, P., Ratchet, B., Gatta, G., Hakulinen, T., Micheli, A., Sant, M., Weir, H.K., Elwood, J.M., Tsukuma, H., Koifman, S.E., Silva, G.A., Francisci, S., Santaquilani, M., Verdecchia, A., Storm, H.H. and Young, J.L. (2008) Advanced Breast Cancer Survival in Five Continents: A World Wide Population-Based Study (CONCORD). The Lancet Oncology, 9, 730-756.
https://doi.org/10.1016/S1470-2045(08)70179-7
[10]  Rezaianzadeh, A., Peacock, J., Reidpatg, D., Talei, A., Hosseini, S.V. and Mehrabani, D. (2009) BMC Cancer.
[11]  Esmail-Akbari, M., Movahedi, M., Zedah, M.K., Moradi, A., Ghanbari-Motlagh, A. and Mirzaei, H. (2012) Survival Rate of Breast Cancer Based on Gegraphical Variation in Iran, a National Study. Iranian Red Crescent Medical Journal, 14, 798-804.
https://doi.org/10.5812/ircmj.3631
[12]  David, G.K. (1996) Survival Analysis: A Self-Learning Text. Springer-Verlag, New York.
[13]  Compton, C.C., Bryd, D.R., Garcia-Aguilar, J., Kurtzman, S.H. and Olawaiye, A. (2012) Incidence of Breast Cancer. A Companion to the Seventh Editions of the AJCC Cancer Staging Manual and Handbook.
[14]  Hosmer, D.W., Lemeshaw, S. and May, S. (2008) Applied Survival Analysis: Regression Modelling of Time-to-Event Data. 2nd Edition, John Wiley & Sons, Inc., Hoboken.
https://doi.org/10.1002/9780470258019
http://www.cancer.net/cancer-types/breast-cancer/medical-illustrations
[15]  Usman, M., Dikko, H., Bala, S. and Gulumbe, S.U. (2014) An Application of Kaplan-Meier Survival Analysis Using Breast Cancer Data. The Sub-Saharan African Journal of Medicine, 1, 132-137.
https://doi.org/10.4103/2384-5147.138940
[16]  Lee, E.T. and Wang, J.W. (2003) Statistical Methods for Survival Data Analysis. 4th Edition, John Wiley & Sons, Inc., Hoboken.
https://doi.org/10.1002/0471458546
[17]  Bland, J.M. and Altman, D.G. (1998) Survival Probabilities (The Kaplan-Meier Method). BMJ, 317, Article No. 1572.
https://doi.org/10.1136/bmj.317.7172.1572

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133