Cox regression analysis on the survival rate of breast cancer patients

Yimin Chen; Weiyu Zeng; Dantong Zhu

doi:10.1117/12.2628105

22 April 2022 Cox regression analysis on the survival rate of breast cancer patients

Yimin Chen, Weiyu Zeng, Dantong Zhu

Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 121630S (2022) https://doi.org/10.1117/12.2628105
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China

Abstract

Limited studies have been conducted on the survival analysis of breast cancer patients. And no study has been investigated using cancer datasets from the UK and Canadian patients. This study aims to qualify the factors contributing to survival time for female breast cancer patients, including patients' age, tumor size, tumor stage, mutation counts, and positive lymph nodes. The hypothesis is proposed that these factors are all associated with the increasing death rate risk for breast cancer patients. The dataset comes from a study conducted on 2510 female breast cancer patients from the UK and Canada, collected by long-term clinical follow-up. The Cox model is applied to each factor to explore their relationship with the survival of patients. All the results are tested, using Schoenfeld residuals. The coefficients between the explanatory variables and survival time are 0.033863 for age, 0.064274 for lymph nodes, 0.007031 for tumor size, 0.010202 for mutation count, and 0.243451 for tumor stage. The C-index of this model is 0.65653558. Our study suggests that on the premise of having some clinical symptoms, the Cox model can be used to predict the survival time of breast cancer patients. The study has some reference value with its convenient procedure and certain accuracy. According to the outcome of Cox regression, the most pivotal explanatory variables are age, lymph nodes examined positive, tumor size, and tumor stage. As these variables increase, the expectation of the survival time of the patients will decrease.

Citation Download Citation

Yimin Chen, Weiyu Zeng, and Dantong Zhu "Cox regression analysis on the survival rate of breast cancer patients", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 121630S (22 April 2022); https://doi.org/10.1117/12.2628105

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Breast cancer

Tumors

Cancer

Lymphatic system

Data modeling

Breast

Tissues

Show All Keywords

Keywords/Phrases

Search In:

Publication Years