Ovarian Cancer Epidemiology, Healthcare Access and Disparities (ORCHiD): methodology for a population-based study of black, Hispanic and white patients with ovarian cancer
Bin Huang,
Lauren Wilson,
Maria Pisu,
Tomi Akinyemiju,
Andrew Berchuck,
Ashwini Joshi,
Kevin Ward,
Margaret Liang,
April Deveaux,
Anjali Gupta,
Malcolm Bevel,
Chioma Omeogu,
Onyinye Ohamadike,
Molly McFatrich,
Erin Daniell,
Laura Jane Fish,
Maria Schymura,
Arnold L Potosky
Affiliations
Bin Huang
1 Division of Biostatistics & Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
Lauren Wilson
1 Department of Anesthesiology, Critical Care and Pain Management, Hospital for Special Surgery, New York City, New York, USA
Maria Pisu
Division of Preventive Medicine, The University of Alabama, Birmingham, Alabama, USA
Tomi Akinyemiju
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Andrew Berchuck
Division of Gynecologic Oncology, Duke University School of Medicine, Durham, North Carolina, USA
Ashwini Joshi
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Kevin Ward
Georgia Cancer Registry, Emory University, Atlanta, Georgia, USA
Margaret Liang
Division of Preventive Medicine, The University of Alabama, Birmingham, Alabama, USA
April Deveaux
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Anjali Gupta
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Malcolm Bevel
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Chioma Omeogu
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Onyinye Ohamadike
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Molly McFatrich
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Erin Daniell
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
Laura Jane Fish
Department of Family Medicine and Community Health, Duke University, Durham, North Carolina, USA
Maria Schymura
New York State Cancer Registry, New York State Department of Health, Albany, New York, USA
Arnold L Potosky
Georgetown University Medical Center, Washington, District of Columbia, USA
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.
