Ovarian Cancer Epidemiology, Healthcare Access and Disparities (ORCHiD): methodology for a population-based study of black, Hispanic and white patients with ovarian cancer.
Ovarian Cancer Epidemiology, Healthcare Access and Disparities (ORCHiD): methodology for a population-based study of black, Hispanic and white patients with ovarian cancer.
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DOI：
10.1136/bmjopen-2021-052808
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发表时间：
2021-10-04
期刊：
影响因子：
2.9
通讯作者：
Potosky AL
中科院分区：
文献类型：
--
作者：
Akinyemiju T;Deveaux A;Wilson L;Gupta A;Joshi A;Bevel M;Omeogu C;Ohamadike O;Huang B;Pisu M;Liang M;McFatrich M;Daniell E;Fish LJ;Ward K;Schymura M;Berchuck A;Potosky AL
在美国，不到40%的卵巢癌（OC）患者接受了适合分期的手术和化疗。黑人癌症患者比白人患者更容易抑郁、疼痛和疲劳。缺乏获得医疗保健的机会可能导致低治疗率和结果的种族差异。卵巢癌流行病学、医疗保健可及性和差异研究旨在从五个特定维度（可得性、可负担性、可及性、住宿和可接受性）来描述黑人、西班牙裔和白人卵巢癌患者的医疗保健可及性（HCA），评估HCA对治疗质量、支持性护理和生存率的影响，并探索可能导致卵巢癌差异的生物学机制。我们将使用与9744名年龄在65岁及以上的OC患者的医疗保险索赔数据相关的监测流行病学和最终结果数据集。我们将从美国9个州的癌症登记处招募1641名OC患者（413名黑人，299名西班牙裔和929名白人）。我们将检查与三个主要结果相关的HCA维度：(1)接受质量，指南依从性初始治疗和支持性护理，(2)基于患者报告结果的生活质量，(3)生存。我们将获得唾液和阴道微生物组样本来检测预后生物标志物。我们将使用分层回归模型来估计HCA维度在患者、社区、提供者和医院层面的影响，并使用随机效应来解释聚类。多层结构方程模型将通过HCA维度估计种族对治疗的总、直接和间接影响。结果的传播将通过在全国会议上的报告以及与其他癌症中心的合作者、社区伙伴和同事的合作进行。我们将向包括科学家、供应商和社区成员在内的关键利益相关者披露调查结果。该研究已获得杜克大学机构审查委员会（Pro00101872）的批准。安全考虑包括保护患者隐私。所有传播的数据将被识别和总结。
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. 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. 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.
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