Exploring Disparities in Metastatic Breast Cancer Treatment Timeliness

Healthcare inequity is a global challenge, with individuals in low- and middle-income households disproportionately affected by conditions such as metastatic breast cancer, which require timely detection and treatment. This study aims to develop predictive models that promote health equity by using diverse, representative data to identify and address health disparities in cancer care. Specifically, we examine how factors such as socioeconomic status, geographic location, race, gender, and access to healthcare resources influence treatment accessibility and diagnostic timelines. We analyzed a dataset containing 13,173 metastatic breast cancer patient records, including demographics, diagnoses, treatment options, and insurance data. Through exploratory data analysis, ANOVA, and correlation analysis, we investigated how these factors relate to the waiting period for treatment. Our findings revealed that payer type and race significantly influenced the time to treatment, suggesting potential disparities in access to or quality of care. Correlation analysis indicated weak or negligible relationships between metastatic diagnosis periods and individual factors such as age, household median income, and BMI. Addressing these disparities could help improve the equity and quality of cancer care, ultimately reducing differences in treatment timelines and patient outcomes.