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. 2019 Oct 9;3(4):pkz084.
doi: 10.1093/jncics/pkz084. eCollection 2019 Dec.

Race, Socioeconomic Status, and Health-Care Access Disparities in Ovarian Cancer Treatment and Mortality: Systematic Review and Meta-Analysis

Shama Karanth  1 , Mackenzie E Fowler  1 , XiHua Mao  1 , Lauren E Wilson  1 , Bin Huang  1 , Maria Pisu  1 , Arnold Potosky  1 , Tom Tucker  1 , Tomi Akinyemiju  1
Affiliations

Race, Socioeconomic Status, and Health-Care Access Disparities in Ovarian Cancer Treatment and Mortality: Systematic Review and Meta-Analysis

Shama Karanth et al. JNCI Cancer Spectr. .

Abstract

Background: Ovarian cancer remains a leading cause of death from gynecological malignancies. Race, socioeconomic status (SES), and access to health care are important predictors of quality treatment and survival. We provide a systematic review and meta-analysis on the role of these predictors on disparities in ovarian cancer treatment and mortality.

Methods: Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched PubMed, EMBASE, and Scopus for relevant articles published between January 2000 and March 2017. We selected studies published in the United States that evaluated the role of race, SES, or health-care access on disparities in ovarian cancer treatment or survival. Pooled relative risk (RR) and 95% confidence intervals (CIs) were calculated for each outcome using a random-effects model.

Results: A total of 41 studies met the inclusion criteria for systematic review. In meta-analysis, there was a 25% decrease (RR = 0.75, 95% CI = 0.66 to 0.84) in receipt of adherent ovarian cancer treatment and 18% increased risk (RR = 1.18, 95% CI = 1.11 to 1.26) of mortality for blacks compared to whites. Receipt of adherent ovarian cancer treatment was 15% lower (RR = 0.85, 95% CI = 0.77 to 0.94) in the lowest vs highest SES group and 30% lower (RR = 0.70, 95% CI = 0.58 to 0.85) among patients at lower vs higher hospital volumes.

Conclusion: We found consistent and strong evidence for continued lack of quality ovarian cancer treatment and higher mortality among ovarian cancer patients who are black, are of low SES, and/or have poor access to care. Interventions focused on these groups targeting specific barriers to care are needed to reduce disparities in ovarian cancer treatment and mortality.

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Figures

Figure 1.
Figure 1.
Meta-analysis of the association between race (Blacks vs whites, Hispanics vs whites, Asian/Pacific Islander vs whites) and ovarian cancer treatment. Asian/API = Asian/Pacific Islander; CI = confidence interval; NCCN = National Comprehensive Cancer Network; RR = relative risk.
Figure 2.
Figure 2.
Meta-analysis of the association between race (blacks vs whites, Hispanics vs whites) and ovarian cancer mortality. CI = confidence interval; RR = relative risk.
Figure 3.
Figure 3.
Meta-analysis of the association between socioeconomic status and ovarian cancer outcomes. CI = confidence interval; NCCN = National Comprehensive Cancer Network; RR = relative risks; SES = socioeconomic status.
Figure 4.
Figure 4.
Meta-analysis of the association between insurance status (Medicare, Medicaid vs private insurance and/or managed care) and ovarian cancer treatment. CI = confidence interval; NCCN = National Comprehensive Cancer Network; RR = relative risks.
Figure 5.
Figure 5.
Meta-analysis of the association between insurance status (uninsured, public, self-pay, other vs private insurance and/or managed care) and ovarian cancer treatment. CI = confidence interval; RR = relative risk.
Figure 6.
Figure 6.
Meta-analysis of the association between hospital characteristics (contrast is worse vs better for all exposures) and receipt of ovarian cancer treatment. ACoS = American College of Surgeons; CI = confidence interval; Excis = excision; NCCN = National Comprehensive Cancer Network; RR = relative risks
Figure 7.
Figure 7.
Meta-analysis of the association between comorbidities (higher vs lower burden) and ovarian cancer outcomes.
See this image and copyright information in PMC

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