Healthcare Access Domains Mediate Racial Disparities in Ovarian Cancer Treatment Quality in a US Patient Cohort: A Structural Equation Modelling Analysis

Author:

Akinyemiju Tomi12ORCID,Chen Quan3ORCID,Wilson Lauren E.1ORCID,Previs Rebecca A.4ORCID,Joshi Ashwini1ORCID,Liang Margaret5ORCID,Pisu Maria6ORCID,Ward Kevin C.7ORCID,Berchuck Andrew4ORCID,Schymura Maria J.8ORCID,Huang Bin3ORCID

Affiliation:

1. 1Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.

2. 2Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina.

3. 3Division of Cancer Biostatistics and Kentucky Cancer Registry, University of Kentucky, Lexington, Kentucky.

4. 4Division of Gynecologic Oncology, Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina.

5. 5Division of Gynecologic Oncology, Department of Obstetrics & Gynecology, University of Alabama at Birmingham, Birmingham, Alabama.

6. 6Division of Preventive Medicine and O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama.

7. 7Georgia Cancer Registry, Emory University, Atlanta, Alabama.

8. 8New York State Cancer Registry, New York State Department of Health, Albany, New York.

Abstract

Abstract Background: Ovarian cancer survival disparities have persisted for decades, driven by lack of access to quality treatment. We conducted structural equation modeling (SEM) to define latent variables representing three healthcare access (HCA) domains: affordability, availability, and accessibility, and evaluated the direct and indirect associations between race and ovarian cancer treatment mediated through the HCA domains. Methods: Patients with ovarian cancer ages 65 years or older diagnosed between 2008 and 2015 were identified from the SEER-Medicare dataset. Generalized SEM was used to estimate latent variables representing HCA domains by race in relation to two measures of ovarian cancer-treatment quality: gynecologic oncology consultation and receipt of any ovarian cancer surgery. Results: A total of 8,987 patients with ovarian cancer were included in the analysis; 7% were Black. The affordability [Ω: 0.876; average variance extracted (AVE) = 0.689], availability (Ω: 0.848; AVE = 0.636), and accessibility (Ω: 0.798; AVE = 0.634) latent variables showed high composite reliability in SEM analysis. Black patients had lower affordability and availability, but higher accessibility compared with non-Black patients. In fully adjusted models, there was no direct effect observed between Black race to receipt of surgery [β: −0.044; 95% confidence interval (CI), −0.264 to 0.149]; however, there was an inverse total effect (β: −0.243; 95% CI, −0.079 to −0.011) that was driven by HCA affordability (β: −0.025; 95% CI, −0.036 to −0.013), as well as pathways that included availability and consultation with a gynecologist oncologist. Conclusions: Racial differences in ovarian cancer treatment appear to be driven by latent variables representing healthcare affordability, availability, and accessibility. Impact: Strategies to mitigate disparities in multiple HCA domains will be transformative in advancing equity in cancer treatment.

Funder

National Cancer Institute

National Institutes of Health

Publisher

American Association for Cancer Research (AACR)

Subject

Oncology,Epidemiology

Reference42 articles.

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