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Background: Hispanic/Latinx people have the second highest cervical cancer incidence rates in the U.S. However, there is a lack of disaggregated data on clinical outcomes for this diverse and populous group, which is critical to direct resources and funding where they are most needed. This study assessed differences in stage at diagnosis of cervical cancer among Hispanic/Latinx subpopulations and associated factors., Methods: We analyzed patients with primary cervical cancer from 2004 to 2019 in the National Cancer Database. Hispanic/Latinx patients were further categorized into Mexican, Puerto Rican (PR), Cuban, Dominican, and Central/South American, as per standard NCDB categories, and evaluated based on stage at diagnosis and sociodemographic characteristics. Multinomial logistic regression quantified the odds of advanced stage at presentation. Regression models were adjusted for age, education, neighborhood income, insurance status, and additional factors., Results: Hispanic/Latinx cervical cancer patients were more likely to be uninsured (18.9% vs. 6.0%, p < 0.001) and more likely to live in low-income neighborhoods (28.6% vs. 16.9%, p < 0.001) when compared to non-Hispanic White populations. Uninsured Hispanic/Latinx patients had 37.0% higher odds of presenting with regional versus localized disease (OR 1.37; 95% CI, 1.19-1.58) and 47.0% higher odds of presenting with distant versus. Localized disease than insured patients (OR 1.47; 95% CI, 1.33-1.62). When adjusting for age, education, neighborhood income, and insurance status, PR patients were 48% more likely than Mexican patients to present with stage IV versus stage I disease (OR 1.48; 95% CI, 1.34-1.64)., Conclusion: Disaggregating health data revealed differences in stage at cervical cancer presentation among Hispanic/Latinx subpopulations, with insurance status as a major predictor. Further work targeting structural factors, such as insurance status, within specific Hispanic/Latinx subpopulations is needed., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Racial and ethnic minority groups experience a disproportionate burden of SARS-CoV-2 illness and studies suggest that cancer patients are at a particular risk for severe SARS-CoV-2 infection., Aims: The objective of this study was examine the association between neighborhood characteristics and SARS-CoV-2 infection among patients with cancer., Methods and Results: We performed a cross-sectional study of New York City residents receiving treatment for cancer at a tertiary cancer center. Patients were linked by their address to data from the US Census Bureau's American Community Survey and to real estate tax data from New York's Department of City Planning. Models were used to both to estimate odds ratios (ORs) per unit increase and to predict probabilities (and 95% CI) of SARS-CoV2 infection. We identified 2350 New York City residents with cancer receiving treatment. Overall, 214 (9.1%) were infected with SARS-CoV-2. In adjusted models, the percentage of Hispanic/Latino population (aOR = 1.01; 95% CI, 1.005-1.02), unemployment rate (aOR = 1.10; 95% CI, 1.05-1.16), poverty rates (aOR = 1.02; 95% CI, 1.0002-1.03), rate of >1 person per room (aOR = 1.04; 95% CI, 1.01-1.07), average household size (aOR = 1.79; 95% CI, 1.23-2.59) and population density (aOR = 1.86; 95% CI, 1.27-2.72) were associated with SARS-CoV-2 infection., Conclusion: Among cancer patients in New York City receiving anti-cancer therapy, SARS-CoV-2 infection was associated with neighborhood- and building-level markers of larger household membership, household crowding, and low socioeconomic status., Novelty and Impact: We performed a cross-sectional analysis of residents of New York City receiving treatment for cancer in which we linked subjects to census and real estate date. This linkage is a novel way to examine the neighborhood characteristics that influence SARS-COV-2 infection. We found that among patients receiving anti-cancer therapy, SARS-CoV-2 infection was associated with building and neighborhood-level markers of household crowding, larger household membership, and low socioeconomic status. With ongoing surges of SARS-CoV-2 infections, these data may help in the development of interventions to decrease the morbidity and mortality associated with SARS-CoV-2 among cancer patients., (© 2022 The Authors. Cancer Reports published by Wiley Periodicals LLC.)