The Role of Multiple Mediation with Contextual Neighborhood Measures in Ovarian Cancer Survival

Andrew B Lawson; Yao Xin; Edward S Peters; Courtney Johnson; Theresa Hastert; Elisa V Bandera; Anthony J Alberg; Lindsey Collin; Paul Terry; Maxwell Akonde; Hannah Mandle; Michele L Cote; Melissa Bondy; Jeffrey Marks; Lauren C Peres; Kendra L Ratnapradipa; Joellen M Schildkraut

doi:10.1016/j.annepidem.2024.10.002

The Role of Multiple Mediation with Contextual Neighborhood Measures in Ovarian Cancer Survival

Ann Epidemiol. 2024 Oct 8:S1047-2797(24)00244-8. doi: 10.1016/j.annepidem.2024.10.002. Online ahead of print.

Authors

Andrew B Lawson¹, Yao Xin², Edward S Peters³, Courtney Johnson⁴, Theresa Hastert⁵, Elisa V Bandera⁶, Anthony J Alberg⁷, Lindsey Collin⁸, Paul Terry⁹, Maxwell Akonde⁷, Hannah Mandle⁴, Michele L Cote¹⁰, Melissa Bondy¹¹, Jeffrey Marks¹², Lauren C Peres¹³, Kendra L Ratnapradipa³, Joellen M Schildkraut⁴

Affiliations

¹ Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, 29425, USA; Usher Institute, Centre for Population Health Sciences, Edinburgh Medical School, University of Edinburgh, UK. Electronic address: lawsonab@musc.edu.
² Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, 29425, USA.
³ Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska, USA.
⁴ Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.
⁵ Department of Oncology, Wayne State University School of Medicine, Population Studies and Disparities Research Program, Karmanos Cancer Institute, Detroit, Michigan, USA.
⁶ Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA.
⁷ Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
⁸ Huntsman Cancer Institute, Department of Population Health Sciences, University of Utah, Salt Lake City, UT.
⁹ Department of Medicine, University of Tennessee Medical Center-Knoxville, Knoxville, TN, USA.
¹⁰ Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, Indiana, USA.
¹¹ Department of Epidemiology and Population Health, Stanford University, College of Medicine, Stanforrd, California, USA.
¹² Department of Surgery, Duke University School of Medicine, Durham, NC, USA.
¹³ Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.

PMID: 39389398
DOI: 10.1016/j.annepidem.2024.10.002

Abstract

Background: Mediation by multiple agents can affect the relation between neighborhood deprivation and segregation indices and ovarian cancer survival. In this paper, we examine a variety of potential clinical mediators in the association between deprivation indices (DIs) and segregation indices (SIs) with all-cause survival among women with ovarian cancer in the African American Cancer Epidemiology Study (AACES).

Methods: We use novel Bayesian multiple mediation structural models to assess the joint role of mediators (stage at diagnosis, histology, diagnostic delay) combined with the DIs and SIs (Yost, ADI, Kolak's URB, ICE-income) and a set of confounders with survival. The confounder set is selected in a preliminary step, and each DI or SI is included in separate model fits.

Results: When multiple mediators are included, the total impact of DIs and SIs on survival is much reduced. Unlike the single mediator examples previously reported, the Yost, ADI and ICE-income indices do not display significant direct effects. This suggests that when important clinical mediators are included, the impact of neighborhood SES indices is significantly attenuated. It is also clear that certain behavioral and demographic measures such as physical activity, smoking, or adjusted family income do not have a significant role in survival when mediated by clinical factors.

Conclusion: Multiple mediation via clinical and diagnostic-related measures reduces the contextual effects of neighborhood measures on ovarian cancer survival. The robust association of the Kolak URB index on survival may be due to its relevance to access to care, unlike SES-based indices whose impact was significantly reduced when important clinical mediators were included.

Keywords: African American Cancer Epidemiology Study (AACES); Bayesian Mixed effect models; deprivation; multiple mediation; neighborhood; ovarian cancer; segregation; survival.