Analyzing Breast Cancer Survival Disparities by Race and Demographic Location: A Survival Analysis Approach

TL;DR

This study analyzes breast cancer survival disparities across race and geography using survival analysis techniques on the SEER dataset, aiming to inform targeted interventions and reduce inequalities.

Contribution

Introduces a comprehensive survival analysis framework to identify racial and geographic disparities in breast cancer outcomes using advanced statistical models.

Findings

Identifies significant survival disparities among racial groups.

Highlights key variables influencing survival rates.

Provides validated models for predicting survival outcomes.

Abstract

This study employs a robust analytical framework to uncover patterns in survival outcomes among breast cancer patients from diverse racial and geographical backgrounds. This research uses the SEER 2021 dataset to analyze breast cancer survival outcomes to identify and comprehend dissimilarities. Our approach integrates exploratory data analysis (EDA), through this we identify key variables that influence survival rates and employ survival analysis techniques, including the Kaplan-Meier estimator and log-rank test and the advanced modeling Cox Proportional Hazards model to determine how survival rates vary across racial groups and countries. Model validation and interpretation are undertaken to ensure the reliability of our findings, which are documented comprehensively to inform policymakers and healthcare professionals. The outcome of this paper is a detailed version of statistical analysis that not just highlights disparities in breast cancer treatment and care but also serves as a foundational tool for developing targeted interventions to address the inequalities effectively. Through this research, our aim is to contribute to the global efforts to improve breast cancer outcomes and reduce treatment disparities.