Parametric Modeling of Survival Times Among Breast Cancer Patients in a Teaching Hospital, Osogbo
Journal of Cancer Treatment and Research
Volume 5, Issue 5, September 2017, Pages: 81-85
Received: Oct. 31, 2016; Accepted: Nov. 21, 2016; Published: Sep. 13, 2017
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Authors
Phillip Oluwatobi Awodutire, Department of Statistics, Federal Polytechnic of Oil and Gas, Bonny, Nigeria
Oladapo Adedayo Kolawole, Department of Surgery, Ladoke Akintola University of Technology Teaching Hospital, Osogbo, Nigeria
Oluwatosin Ruth Ilori, Department of Community Medicine, Ladoke Akintola University of Technology Teaching Hospital, Ogbomoso, Nigeria
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Abstract
In Nigeria, Breast Cancer is the most common malignancy among women. Unfortunately, many breast cancer patients present for treatment late. Using a parametric survival model to predict the survival times of patients and contribution of the prognostic factors, the study focused on the 1-year survival of breast cancer patients from the day of presentation. A total 89 women, who were diagnosed with breast cancer in which 32.56% reported early for treatment from 2009 to 2014, were recorded. Age, stage of presentation, average years of breastfeeding, neoadjuvant treatment offered, age at menarche and use of contraceptives were the variables used in the study. The predictive model that can be used to predict survival times of breast cancer patients was obtained. The results showed that stage at presentation is significant at 0.05 significance level.
Keywords
Survival Times, Parametric Model, Breast Cancer, Predictive, Prognostic Factor
To cite this article
Phillip Oluwatobi Awodutire, Oladapo Adedayo Kolawole, Oluwatosin Ruth Ilori, Parametric Modeling of Survival Times Among Breast Cancer Patients in a Teaching Hospital, Osogbo, Journal of Cancer Treatment and Research. Vol. 5, No. 5, 2017, pp. 81-85. doi: 10.11648/j.jctr.20170505.12
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Adetifa, F. A. and Ojikutu, R. K. (2009): Prevalence and Trends in Breast Cancer in Lagos State, Nigeria. African Research Review, 3 (5).
[2]
Adisa, A. O., Arowolo, O. A., Akinkuolie, A. A., Titiloye, N. A., Alatise, O. I., Lawal, O. O. and Adesunkanmi, A. R. K. (2011): Metastatic breast cancer in a Nigerian tertiary hospital. African Health Sciences, 11 (2).
[3]
Afolayan, A. (2012): Breast cancer trends in a Nigerian population: an analysis of cancer registry data. International Journal of Life Science and Pharma Research, 2 (3).
[4]
McPherson, K., Steel, C. M., Dixon, J. M. (2000): ABC of Breast Diseases, BMJ vol 21.
[5]
El Saghir N. S., Adebamowo C. A., Anderson B. O., Carlson R. W., Bird P. A., Corbex M., Badwe R. A., Bushnaq M. A., Eniu A., Gralow J. R., Harness J. K., Masetti R., Perry F., Samiei M., Thomas D. B., Wiafe-Addai B., Cazap E. (2011): Breast cancer management in low resource countries (LRCs): consensus statement from the Breast Health Global Initiative. Vol 20 Suppl 2: S3-S11.
[6]
Parkin, D. M., Bray, F., Ferlay, J., Pisani, P. (2002): Global Cancer Statistics, CA; a Cancer Journal for Clinicians 2005 Mar; 55 (2): 74-108.
[7]
Luciana Martins da Rosa1, Vera Radünz (2012): Survival Rates to Woman with Breast Cancer: Review Text Context Nursing, Florianópolis, 2012 Oct-Dec; 21 (4): 980-9.
[8]
Najaf, Z., Marzieh D., Abass R. (2012): Modeling of Breast Cancer Prognostic Factors using a Parametric Log-Logistic Model in Fars province, Southern Iran. Asian Pacific Journal of Cancer Prevention, Vol 13, 2012 1537.
[9]
Montesarrat Rue, Sandra Lee, Ester Vilaprinyo, Montserrat Martinez-Alonso, Misericordia Carles, Rafael Marcos-Gragera, Roger Pla and Josep- Alfons Espinas: Effectiveness of Early Detection of Breast Cancer Mortality Reduction in Catalonia (Spain). BMC Cancer 2009; 9: 326, doi: 10.1186/1471-2407-9-326.
[10]
Ojewusi Ayoola A., Obembe Taiwo, Aruogun Oyedunni S and Olugbayela Tunde (2016): Breast Cancer Awareness, Attitude and Screening Practices in Nigeria; a systematic review. 7 (2), pp. 11-25.
[11]
Aalen, O. O. (2000): Medical statistics-no time for complacency. Statistical Methods In Medical Research 9, 31-40.
[12]
Baghestani A. R., Moghaddam S. S., Majd H. A, Akbari M. E, Nafissi N., Gohari K. (2015): Survival Analysis of Patients with Breast Cancer using Weibull Parametric Model. Asian Pacific Journal of Cancer Prevention, article 85, vol 16, issues 18, pages 8567-8571.
[13]
Usman M., Dikko H. G., Bala S., Gulmbe S. U (2014): An Application of Kaplan-Meier Survival Analysis using Breast Cancer DATA. Sub-Saharan African Journal of Medicine/ vol1/Issue3.
[14]
Carey K. Anders, Rebecca Johnson, Jennifer Litton, Marianne Phillips and Archie Bleyer (2009): Breast cancer before age 40 years. Semin Oncol. June; 36(3): 237-249. doi: 10.1053/j.semioncol.2009.03.001
[15]
Vallinayagam V., Prathap S. and Venkatesan P. (2014): Parametric Regression Models in the Analysis of Breast Cancer Survival Data; International Journal of Science and Technology. Vol 3, No. 3.
[16]
Elvan A. H (2010): Comparison of Five Survival Models; Breast Cancer Registry Data from Egw University Cancer Research Center, International Biometric Society Journal.
[17]
Collett, D. (2003): Modelling Survival Data in Medical Research, Second Edition; Chapman & Hall/ CRC Press, Boca Raton, FL.
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