Impact of COVID-19 pandemic on breast cancer screening in a large midwestern United States academic medical center.

BACKGROUND: Access to breast screening mammogram services decreased during the COVID-19 pandemic. Our objectives were to estimate: 1) the COVID-19 affected period, 2) the proportion of pandemic-associated missed or delayed screening encounters, and 3) pandemic-associated patient attrition in screening encounters overall and by sociodemographic subgroup. METHODS: We included screening mammogram encounter EPIC data from 1-1-2019 to 12-31-2022 for females ≥40 years old. We used Bayesian State Space models to describe weekly screening mammogram counts, modeling an interruption that phased in and out between 3-1-2020 and 9-1-2020. We used the posterior predictive distribution to model differences between a predicted, uninterrupted process and the observed screening mammogram counts. We estimated associations between race/ethnicity and age group and return screening mammogram encounters during the pandemic among those with 2019 encounters using logistic regression. RESULTS: Our analysis modeling weekly screening mammogram counts included 231,385 encounters (n = 127,621 women). Model-estimated screening mammograms dropped by >98% between 03-15-2020 and 05-24-2020 followed by a return to pre-pandemic levels or higher with similar results by race/ethnicity and age group. Among 79,257 women, non-Hispanic (NH) Asians, NH Blacks, and Hispanics had significantly (p < .05) lower odds of screening encounter returns during 2020-2022 vs. NH Whites with odds ratios (ORs) from 0.70 to 0.91. Among 79,983 women, those 60-69 had significantly higher odds of any return screening encounter during 2020-2022 (OR = 1.28), while those ≥80 and 40-49 had significantly lower odds (ORs 0.77, 0.45) than those 50-59 years old. A sensitivity analysis suggested a possible pre-existing pattern. CONCLUSIONS: These data suggest a short-term pandemic effect on screening mammograms of ~2 months with no evidence of disparities. However, we observed racial/ethnic disparities in screening mammogram returns during the pandemic that may be at least partially pre-existing. These results may inform future pandemic planning and continued efforts to eliminate mammogram screening disparities.

Associations between Medicaid enrollment and diagnosis stage and survival among pediatric cancer patients.

BACKGROUND: Medicaid-associated disparities in childhood and adolescent (pediatric) cancer diagnosis stage and survival have been reported. However, a key limitation of prior studies is the assessment of health insurance at a single time point. To evaluate Medicaid-associated disparities more robustly, we used Surveillance, Epidemiology, and End Results (SEER)-Medicaid linked data to examine diagnosis stage and survival disparities in those (i) Medicaid-enrolled and (ii) with discontinuous and continuous Medicaid enrollment. METHODS: SEER-Medicaid linked data from 2006 to 2013 were obtained on cases diagnosed from 0 to 19 years. Medicaid enrollment was classified as enrolled versus not enrolled, with further classifications as continuous when enrolled 6 months before through 6 months after diagnosis, and discontinuous when not enrolled continuously for this period. We used multinomial logistic and Cox proportional hazards regression models to determine associations between enrollment measures, diagnosis stage, and cancer death adjusted for covariates. RESULTS: Among 21,502 cases, a higher odds of distant stage diagnoses were observed in association with Medicaid enrollment (odds ratio [OR] = 1.56, 95% confidence interval [CI]: 1.48-1.65), with the highest odds for discontinuous enrollment (OR = 2.0, 95% CI: 1.86-2.15). Among 30,654 cases, any Medicaid enrollment, continuous enrollment, and discontinuous enrollment were associated with 1.68 (95% CI: 1.35-2.10), 1.66 (95% CI: 1.35-2.05), and 1.89 (95% CI: 1.54-2.33) times higher hazards of cancer death versus no enrollment, respectively. CONCLUSIONS: Medicaid enrollment, particularly discontinuous enrollment, is associated with a higher  distant stage diagnosis odds and risk of death. This study supports the critical need for consistent health insurance coverage in children and adolescents.

Pediatric cancer patient emergency department visits and disposition by sociodemographic and economic characteristics.

BACKGROUND: Limited research has been conducted on cancer-related emergency department (ED) patterns among pediatric cancer patients, including whether there are differences in the characteristics of individuals who seek ED care for cancer complications. The objectives of this study were to determine whether rates and disposition of cancer-related ED visits and hospital admissions in childhood cancer patients differ by sociodemographic factors. METHODS: A cross-sectional analysis of ED encounters with a cancer diagnosis code among patients aged 0-19 years from the 2019 National Emergency Department Sample (NEDS) was conducted. Weighted logistic regression models were utilized to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for a primary cancer-related encounter, and hospital admission overall and by subgroup characteristics. RESULTS: Of the unweighted 6,801,711 ED encounters in children aged 0-19 years, 10,793 were classified as visits by cancer patients. ED encounters of Hispanic versus non-Hispanic White pediatric cancer patients had higher odds of having a cancer-related primary diagnosis (OR = 1.15, 95% CI: 1.04-1.27). ED encounters of non-Hispanic Black pediatric patients and those in the lowest zip code income quartile had higher odds of hospital admission (OR = 1.28, 95% CI: 1.08-1.53; OR = 1.30, 95% CI: 1.15-1.46), while rurality was associated with lower odds of hospital admission (OR = 0.69, 95% CI: 0.57-0.83). CONCLUSION: These results suggest that pediatric cancer patients from certain under-resourced communities are more likely to use the ED for cancer treatment complications, and their encounters are more likely to result in admission to the hospital.

When do people increase COVID-19 protective behaviors? A longitudinal analysis of the impact of infections among close contacts and in the community.

Studies examining individual-level changes in protective behaviors over time in association with community-level infection and self or close-contact infection with SARS-CoV-2 are limited. We analyzed overall and demographic specific week-to-week changes in COVID-19 protective behaviors and their association with COVID-19 infections (regional case counts and self or close contacts). Data were collected through 37 consecutive weekly surveys from 10/17/2021 - 6/26/2022. Our survey panel included 212 individuals living or working in St. Louis City and County, Missouri, U.S.A. Frequency of mask-wearing, handwashing, physical distancing, and avoiding large gatherings was self-reported (more/the same/less than the prior week). Close contact with COVID-19 was reported if the panel member, their household member, or their close contact tested positive, got sick, or was hospitalized for COVID-19 in the prior week. Regional weekly COVID-19 case counts were matched to the closest survey administration date. We used generalized linear mixed models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations. Evidence for effect modification was assessed using the likelihood ratio test. Increased protective behaviors were positively associated with COVID-19 case counts (ORhighest vs. lowest case count category = 4.39, 95% CI 3.35-5.74) and with participant-reported self or close contacts with COVID-19 (OR = 5.10, 95% CI 3.88-6.70). Stronger associations were found for White vs. Black panel members (p <.0001). Individuals modulated their protective behaviors in association with regional COVID-19 case counts and self or close contact infection. Rapid reporting and widespread public awareness of infectious disease rates may help reduce transmission during a pandemic by increasing protective behaviors.

Facility patient volume and survival among individuals diagnosed with malignant central nervous system tumors.

PURPOSE: Prior research indicates that the volume of central nervous system (CNS) tumor patients seen by a facility is associated with outcomes. However, most studies have focused on short-term survival and specific CNS tumor subtypes. Our objective was to examine whether facility CNS tumor patient volume is associated with longer-term CNS tumor survival overall and by subtype. METHODS: We obtained National Cancer Database (NCDB) data including individuals diagnosed with CNS tumors from 2004 to 2016. Analyses were stratified by age group (0-14, 15-39, 40-64, and ≥ 65 years) and tumor type. We used Cox Proportional Hazards (PH) regression and restricted mean survival time (RMST) analyses to examine associations between survival and facility patient volume percentile category adjusting for potential confounding factors. RESULTS: Our analytic dataset included data from 130,830 individuals diagnosed with malignant first primary CNS tumors. We found a consistently reduced hazard rate of death across age groups for individuals reported by higher vs. lower (> 95th vs. ≤ 70th percentile) volume facilities (hazard ratio (HR)0-14 = 0.78, 95% confidence interval (CI) 0.64-0.95; HR15-39 = 0.87, 95% CI 0.78-0.96; HR40-64 = 0.82, 95% CI 0.76-0.88; HR≥65 = 0.80, 95% CI 0.75-0.86). Significantly longer survival times within 5 years for higher vs. lower volume facilities were observed ranging from 1.20 months (15-39) to 3.08 months (40-64) higher. Associations varied by CNS tumor subtype for all age groups. CONCLUSIONS: These results suggest facility factors influence CNS tumor survival with longer survival for patients reported by higher volume facilities. Understanding these factors will be critical to developing strategies that eliminate modifiable differences in survival times.