Ovarian Cancer Epidemiology, Healthcare Access and Disparities (ORCHiD): methodology for a population-based study of black, Hispanic and white patients with ovarian cancer

• Authors: Tomi Akinyemiju, Duke University; April Deveaux, Duke University; Lauren Wilson, Duke University; Anjali Gupta, Duke University; Ashwini Joshi, Duke University; Malcolm Bevel, Duke University; Chioma Omeogu, Duke University; Onyinye Ohamadike, Duke University; Bin Huang, University of Kentucky; Maria Pisu, University of Alabama Birmingham; Margaret Liang, University of Alabama Birmingham; Molly McFatrich, Duke University; Erin Daniell, Duke University; Laura Jane Fish, Duke University; Kevin Ward, Emory University; Maria Schymura, New York State Department of Health; Andrew Berchuck, Duke University; Arnold L Potosky, Georgetown University
• Journal Title: BMJ OPEN
• Volume: Volume 11, Number 10
• Publisher: BMJ PUBLISHING GROUP | 2021-10-01, Pages e052808-e052808
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1136/bmjopen-2021-052808
• Subjects: Health Sciences, Oncology; Biology, Biostatistics
• Keywords: Science & Technology; Life Sciences & Biomedicine; Medicine, General & Internal; General & Internal Medicine; statistics & research methods; public health; epidemiology; quality in health care; gynaecological oncology; VAGINAL MICROBIOME; RACIAL DISPARITIES; MEDICAL-RECORDS; SURVIVAL; OUTCOMES; IMPACT; RACE; VALIDATION; WOMEN

Abstract

Introduction Less than 40% of patients with ovarian cancer (OC) in the USA receive stage-appropriate guideline-adherent surgery and chemotherapy. Black patients with cancer report greater depression, pain and fatigue than white patients. Lack of access to healthcare likely contributes to low treatment rates and racial differences in outcomes. The Ovarian Cancer Epidemiology, Healthcare Access and Disparities study aims to characterise healthcare access (HCA) across five specific dimensions - Availability, Affordability, Accessibility, Accommodation and Acceptability - among black, Hispanic and white patients with OC, evaluate the impact of HCA on quality of treatment, supportive care and survival, and explore biological mechanisms that may contribute to OC disparities. Methods and analysis We will use the Surveillance Epidemiology and Ends Results dataset linked with Medicare claims data from 9744 patients with OC ages 65 years and older. We will recruit 1641 patients with OC (413 black, 299 Hispanic and 929 white) from cancer registries in nine US states. We will examine HCA dimensions in relation to three main outcomes: (1) receipt of quality, guideline adherent initial treatment and supportive care, (2) quality of life based on patient-reported outcomes and (3) survival. We will obtain saliva and vaginal microbiome samples to examine prognostic biomarkers. We will use hierarchical regression models to estimate the impact of HCA dimensions across patient, neighbourhood, provider and hospital levels, with random effects to account for clustering. Multilevel structural equation models will estimate the total, direct and indirect effects of race on treatment mediated through HCA dimensions. Ethics and dissemination Result dissemination will occur through presentations at national meetings and in collaboration with collaborators, community partners and colleagues across othercancer centres. We will disclose findings to key stakeholders, including scientists, providers and community members. This study has been approved by the Duke Institutional Review Board (Pro00101872). Safety considerations include protection of patient privacy. All disseminated data will be deidentified and summarised.