Joshua S. Richman

The National Call Center for Homeless Veterans (NCCHV) is available 24 hours/7 days a week to connect Veterans experiencing homelessness or risk with information, referrals, and linkages to Veterans Affairs (VA) and community-based services. This study describes characteristics of call center contacts (n = 251 668) with Veterans during 2019-2023, including demographics, identified social needs, and contact outcomes. The majority of contacts were made by Veterans themselves (vs third party) and most frequently resulted in NCCHV referring the Veteran to their local VA Medical Center; most Veterans who contacted NCCHV had previously used VA healthcare. This study offers insights into which Veterans may need additional attention to connect to VA care and those who remain at high risk of housing instability after connecting with VA. Future work should assess how Veterans are linked with care, with the goal of improving the response to Veterans’ needs and guide strategies to prevent homelessness.

We evaluated the role of total body irradiation (TBI) and its interaction with smoking in relation to subsequent lung cancer after blood or marrow transplantation (BMT) by leveraging the BMT Survivor Study. Participants included individuals who underwent BMT (1974-2014) at 3 centers and who survived ≥2 years. The impact of TBI and smoking was evaluated using Fine-Gray subdistribution hazard models. Standardized incidence ratios were calculated using age- and sex-specific incidence rates obtained from the Surveillance, Epidemiology, and End Results Program. Of the 6981 BMT survivors (median age, 46 years; 58.5% male), 113 developed subsequent lung cancer at a median of 7 years after BMT, representing a 40% higher risk when compared with the general population (95% confidence interval [CI], 1.2-1.7). In the subcohort with smoking data available (n = 3767), there was a significant TBI-smoking interaction (P< .0001). When compared with no TBI never smokers, the risk was increased among TBI-exposed ≥10-year smokers (adjusted subdistribution hazard ratio [asHR], 3.9; 95% CI, 3.0-8.9) and no TBI ≥10-year smokers (asHR, 3.0; 95% CI, 1.3-5.6). Among the <10-year smokers, the risk was not increased, regardless of TBI exposure (TBI: asHR, 1.4; 95% CI, 0.9-3.5; no TBI: asHR, 1.1; 95% CI, 0.30-4.3; reference: no TBI never smokers). TBI exposure in the absence of smoking did not increase the risk (asHR, 0.6; 95% CI, 0.2-1.7). Additional risk factors included older age at BMT, male sex, and pre-BMT exposure to anthracyclines and/or topoisomerase II inhibitors. These findings support personalized surveillance for BMT survivors at heightened risk for subsequent lung cancer.

PURPOSE: The Commission on Cancer (CoC) seeks to expand access to high-quality care through community engagement standards targeting centers' catchment areas and efforts to accredit centers in more areas including rural hospitals. Little is known about the social, environmental, and geographic characteristics of their catchment areas. To support future investigation into the impact of CoC-accredited centers, this study compares characteristics of cancer care utilization–based catchment areas, termed Cancer Service Areas ( CSAs ), with and without CoC-accredited centers. METHODS: Geocoded CoC-accredited centers and cancer care patient flows extracted from Medicare claims data were used to delineate CSAs using a spatially constrained community detection method. Characteristics including environmental justice index (EJI), social vulnerability index (SVI), rurality, travel time, and localization index (LI, a ratio of cancer care received by patients within a CSA) were aggregated by CSA. A logistic regression model was created to evaluate characteristics associated with the presence of a CoC-accredited center within a CSA. RESULTS: Six hundred sixty-eight CSAs were defined, of which 511 CSAs had at least one CoC-accredited center. CSAs with CoC-accredited centers had lower health vulnerability (odds ratio [OR], 0.65 [95% CI, 0.427 to 0.993]) and lower racial and ethnic minority status vulnerability (OR, 0.61 [95% CI, 0.424 to 0.886]), but no differences for other components of the EJI or SVI. These CSAs also had higher LIs, meaning patients remained in their local CSA for care (OR, 9.00 [95% CI, 2.408 to 33.640] for high v low LIs). CONCLUSION: Minority and comorbid populations may have more difficulty accessing cancer center care, further exacerbating observed variations in cancer outcomes. Cancer centers may address this by broadening their outreach into at-risk catchment areas.

Supplemental Table 2 shows results from the multivariable spatial lag model including terms for the interactions between rural urban continuum code and cancer center presence, rural urban continuum code and minority health social vulnerabilty index, rural urban continuum code and late stage at presentation, and late stage at presentation and cancer center presence. To facilitate interpretation of the main study exposure (cancer center presence in the HSA), the model that is displayed in the main manuscript (Table 2) includes categories for metropolitan versus non-metropolitan with and without cancer centers rather than interaction terms.

Background:Treatment at a cancer center improves outcomes for individual patients, but the impact of cancer centers on the regions they serve is unknown. This study examines the association between cancer center presence and cancer mortality within health service areas (HSA), which define US regional care markets.Methods:Cancer centers and cancer mortality were mapped to HSAs using geospatial analysis. The association between cancer center presence and cancer mortality was analyzed using a multivariable spatial lag model, adjusting for the percent of incident cases presenting at late stage, social vulnerability, environmental burden, and rurality. Results are reported as deaths per 100,000 people with 95% confidence interval (CI).Results:Of 940 HSAs, 43% (n = 407) contained at least one cancer center. HSAs with a cancer center had lower cancer mortality than those without a cancer center [158 (95% CI, 155.9–159.5) versus 165 (95% CI, 162.5–166.6) deaths per 100,000 people]. In adjusted analyses, metropolitan HSAs with cancer centers had 4.4 fewer deaths (−8.4 to −0.4) than those without cancer centers whereas there was no observed effect of cancer center presence in nonmetropolitan HSAs (1.4; 95% CI, −1.4 to 4.3). Factors associated with higher cancer mortality were late stage at presentation and greater environmental burden.Conclusions:Cancer center presence within metropolitan healthcare markets was associated with modestly lower cancer mortality.Impact:There is a need to evaluate underlying mechanisms whereby cancer center presence may affect population-level cancer mortality in metropolitan, but not nonmetropolitan HSAs, including direct patient care and indirect effects such as community health promotion.

Supplemental Table 3 shows results from the sensitivity analysis evaluating cancer center density (number of centers per HSA) as a continuous variable rather than the categorical variable of cancer center presence in HSA.

Supplemental Table 1 shows the completed STROBE checklist for the study

Background: Treatment at a cancer center improves outcomes for individual patients, but the impact of cancer centers on the regions they serve is unknown. This study examines the association between cancer center presence and cancer mortality within health service areas (HSA), which define US regional care markets. Methods: Cancer centers and cancer mortality were mapped to HSAs using geospatial analysis. The association between cancer center presence and cancer mortality was analyzed using a multivariable spatial lag model, adjusting for the percent of incident cases presenting at late stage, social vulnerability, environmental burden, and rurality. Results are reported as deaths per 100,000 people with 95% confidence interval (CI). Results: Of 940 HSAs, 43% (n = 407) contained at least one cancer center. HSAs with a cancer center had lower cancer mortality than those without a cancer center [158 (95% CI, 155.9–159.5) versus 165 (95% CI, 162.5–166.6) deaths per 100,000 people]. In adjusted analyses, metropolitan HSAs with cancer centers had 4.4 fewer deaths (−8.4 to −0.4) than those without cancer centers whereas there was no observed effect of cancer center presence in nonmetropolitan HSAs (1.4; 95% CI, −1.4 to 4.3). Factors associated with higher cancer mortality were late stage at presentation and greater environmental burden. Conclusions: Cancer center presence within metropolitan healthcare markets was associated with modestly lower cancer mortality. Impact: There is a need to evaluate underlying mechanisms whereby cancer center presence may affect population-level cancer mortality in metropolitan, but not nonmetropolitan HSAs, including direct patient care and indirect effects such as community health promotion.