{"title":"Racial and ethnic disparities in mortality among World Trade Center Health Registry enrollees with post-9/11 cancer","authors":"Rebecca D. Kehm, Jiehui Li, James E. Cone","doi":"10.1002/cam4.70071","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Introduction</h3>\n \n <p>There are well-documented racial and ethnic disparities in mortality after cancer in the general population, but less is known about whether disparities also exist in disaster-exposed populations.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We conducted a longitudinal cohort study of 4341 enrollees in the World Trade Center Health Registry (WTCHR) with a first-ever primary invasive cancer diagnosis after 9/11/2001 and followed through 2020. We examined associations of race and ethnicity with all-cause mortality risk and cause-specific mortality risk using multivariable Cox proportional hazards regression models and Fine and Gray's proportional sub-distribution hazards models, respectively. Models were adjusted for baseline characteristics and tumor characteristics. We also examined models further adjusted for socioeconomic status (SES), and we used inverse odds weighting to formally test for mediation by SES.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Compared to non-Hispanic White enrollees with cancer, non-Hispanic Blacks had higher risks for all-cause mortality (adjusted hazard ratio (aHR) = 1.20, 95% CI = 1.02–1.41) and non-cancer mortality (aHR = 1.48, 95% CI = 1.09–2.01) in the full model. In the model without SES, Hispanic enrollees with cancer had higher risks for all-cause mortality (aHR = 1.32, 95% CI = 1.09–1.60) and cancer mortality (aHR = 1.31, 95% CI = 1.05–1.64) compared to non-Hispanic Whites; these associations became not statistically significant in the full model. In the inverse odds weighting analysis, SES explained 24% and 29% of the disparity in all-cause mortality risk observed in non-Hispanic Blacks and Hispanics, respectively, compared to non-Hispanic Whites.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>This study found that there are racial and ethnic disparities in mortality after cancer in the WTCHR. Additional studies are needed to further explore the factors mediating these disparities.</p>\n </section>\n </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.70071","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cam4.70071","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
There are well-documented racial and ethnic disparities in mortality after cancer in the general population, but less is known about whether disparities also exist in disaster-exposed populations.
Methods
We conducted a longitudinal cohort study of 4341 enrollees in the World Trade Center Health Registry (WTCHR) with a first-ever primary invasive cancer diagnosis after 9/11/2001 and followed through 2020. We examined associations of race and ethnicity with all-cause mortality risk and cause-specific mortality risk using multivariable Cox proportional hazards regression models and Fine and Gray's proportional sub-distribution hazards models, respectively. Models were adjusted for baseline characteristics and tumor characteristics. We also examined models further adjusted for socioeconomic status (SES), and we used inverse odds weighting to formally test for mediation by SES.
Results
Compared to non-Hispanic White enrollees with cancer, non-Hispanic Blacks had higher risks for all-cause mortality (adjusted hazard ratio (aHR) = 1.20, 95% CI = 1.02–1.41) and non-cancer mortality (aHR = 1.48, 95% CI = 1.09–2.01) in the full model. In the model without SES, Hispanic enrollees with cancer had higher risks for all-cause mortality (aHR = 1.32, 95% CI = 1.09–1.60) and cancer mortality (aHR = 1.31, 95% CI = 1.05–1.64) compared to non-Hispanic Whites; these associations became not statistically significant in the full model. In the inverse odds weighting analysis, SES explained 24% and 29% of the disparity in all-cause mortality risk observed in non-Hispanic Blacks and Hispanics, respectively, compared to non-Hispanic Whites.
Conclusion
This study found that there are racial and ethnic disparities in mortality after cancer in the WTCHR. Additional studies are needed to further explore the factors mediating these disparities.
期刊介绍:
Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas:
Clinical Cancer Research
Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations
Cancer Biology:
Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery.
Cancer Prevention:
Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach.
Bioinformatics:
Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers.
Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.