Quantitative Issues in Cancer Research Working Group Seminar

Carmen B. Rodriguez, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health

A Bayesian Mixture Model Approach to Examining Socioeconomic Disparities in Endometrial Cancer Care in Massachusetts.

Abstract: Endometrial cancer (EC) is the most common gynecologic cancer in the United States. On average, African American women have 55% higher 5-year mortality risk compared to white women, and like other minority groups, they are vulnerable to receiving care that is not concordant with evidence-based treatment guidelines. These differences are linked to systemic and structural factors relating to difficulties in accessing care and the socioeconomic environments in which individuals reside. Previous research has examined socioeconomic factors (e.g., education, income) individually/independently, but these often interact as social determinants of health. In this project, we took a multifactorial approach in how we examine racial-ethnic and socioeconomic factors leading to bias and disparities in EC care. We follow a social determinants of health framework to describe neighborhood socioeconomic status (NSES) profiles/clusters. We identified NSES profiles through the application of a multivariate Bernoulli mixture model. Using census tract aggregate level data and patient-level information from 9318 patients collected in the 2006-2017 Massachusetts Cancer Registry, we examined differences in receipt of optimal care for EC patients in Massachusetts by NSES profiles. We compared the stability of our cluster profiles across three waves of the American Community Survey 5-year estimates (2006-2010,2011-2015 and 2015-2019), and compared these results to other aggregate measures used in cancer surveillance datasets.