Identifying predictors of COVID-related delays in cancer-specific medical care.

PURPOSE: Evidence of the impact of the COVID-19 pandemic on cancer prevention and control is growing, but little is known about patient-level factors associated with delayed care. We analyzed data from a survey focused on Iowan cancer patients' COVID-19 experiences in the early part of the pandemic. METHODS: Participants were recruited from the University of Iowa Holden Comprehensive Cancer Center's Patients Enhancing Research Collaborations at Holden (PERCH) program. We surveyed respondents on demographic characteristics, COVID-19 experiences and reactions, and delays in any cancer-related health care appointment, or cancer-related treatment appointments. Two-sided significance tests assessed differences in COVID-19 experiences and reactions between those who experienced delays and those who did not. RESULTS: There were 780 respondents (26% response), with breast, prostate, kidney, skin, and colorectal cancers representing the majority of respondents. Delays in cancer care were reported by 29% of respondents. In multivariable-adjusted models, rural residents (OR 1.47; 95% CI 1.03, 2.11) and those experiencing feelings of isolation (OR 2.18; 95% CI 1.37, 3.47) were more likely to report any delay, where experiencing financial difficulties predicted delays in treatment appointments (OR 5.72; 95% CI 1.96, 16.67). Health insurance coverage and concern about the pandemic were not statistically significantly associated with delays. CONCLUSION: These findings may inform cancer care delivery during periods of instability when treatment may be disrupted by informing clinicians about concerns that patients have during the treatment process. Future research should assess whether delays in cancer care impact long-term cancer outcomes and whether delays exacerbate existing disparities in cancer outcomes.

Perspectives on Referring for Rectal Cancer Surgery: a Survey Study of Gastroenterologist and General Surgeons in Iowa.

PURPOSE: To understand referral practices for rectal cancer surgical care and to secondarily determine differences in referral practices by two main hypothesized drivers of referral: the rurality of the community endoscopists' practice and their affiliation with a colorectal surgeon. METHODS: Community gastroenterologists and general surgeons in Iowa completed a mailed questionnaire on practice demographics, volume, and referral practices for rectal cancer patients. Rurality was operationalized with RUCA codes. RESULTS: Twenty-two of 53 gastroenterologists (42%) and 120 of 188 general surgeons (64%) (total 144/241, 60%) in Iowa responded. Most performed colonoscopies, including 22 gastroenterologists (100%) and 96 general surgeons (80%). Regular referral of rectal cancer patients to colorectal surgeons was reported for 57% of urban physicians affiliated with a colorectal surgeon, 33% of urban physicians not affiliated with a colorectal surgeon, and 57% and 72% of physicians in large and small rural areas, respectively, who were not affiliated with a colorectal surgeon. High surgeon volume, high hospital volume, and colorectal surgeon specialty were important factors in the referral decisions for over half the physicians. 69% of diagnosing urban general surgeons reported performing rectal cancer surgery about half the time or more, while 85% of small rural and 60% of large rural diagnosing general surgeons reported never or rarely performing rectal cancer surgery. CONCLUSIONS: Diagnosing physicians have variable rectal cancer referral practices, including consistency in referred to surgeon and prioritization of volume and specialization. Prioritizing specialized or high-volume rectal cancer surgical care would require changing existing referring patterns.

Comparing COVID-19 Response Behaviors between a Cancer Patient Sample and a Population-Based Cancer-Free Sample in a Rural Midwestern State.

INTRODUCTION: The COVID-19 pandemic caused an increase in fear, anxiety, and depressive symptoms globally. For populations at increased risk for adverse outcomes due to illness, such as cancer patients, these worries may have been exacerbated. Understanding how the pandemic impacted cancer patients will inform better preparation for future events that cause disturbances to cancer care delivery. METHODS: This study analyzed data from two surveys to determine whether cancer patients' responses differed from a cancer-free population-based sample in terms of concerns, preventive behaviors, and thoughts on their healthcare provider's communication regarding COVID-19 in a US Midwestern state. In August 2020, a survey was sent to 10,009 Iowans aged 18 and older, randomly selected from the 2018 Iowa voter registration file. In September 2020, a survey was emailed to 2,954 cancer patients aged 18 and older who opted into the University of Iowa Holden Comprehensive Cancer Center's Patients Enhancing Research Collaborations at Holden program. Previously validated and pretested Likert-type and multiple-choice items assessed concern regarding COVID-19, social distancing perception and behaviors, and demographic characteristics of respondents. We used χ2 tests and logistic regression to examine differences between the cancer patient and general population survey responses. RESULTS: We included 3,622 responses from the general population survey and 780 responses from the cancer patient survey in this analysis. Cancer patient survey respondents were more frequently older, lived in urban areas, had Medicare insurance coverage, had a college degree or higher, and were married. Cancer patients were more likely to report engaging in social distancing behaviors and greater concern regarding the pandemic. CONCLUSION: This study suggests differences in the impact of the COVID-19 pandemic on cancer patients compared to cancer-free members of the general population. These results indicate the need for consideration of cancer patients' physical and mental health during large-scale disruptions to cancer care.

Well-being and stress vulnerability in ovarian cancer survivors during the COVID-19 pandemic.

OBJECTIVE: This study was designed to examine (1) whether ovarian cancer (OC) survivors would have greater well-being vs. elevated distress compared to community members during a universal health stressor (COVID-19) and (2) how resources and risk factors at diagnosis predicted vulnerability to a subsequent health-related stressor. METHODS: One hundred seventeen OC survivors were recruited from two academic medical centers and compared to a community-based sample on COVID-related distress and disruption. Latent class analysis identified differentially impacted groups of survivors. RESULTS: Survivors reported lower distress than community members. Predictors of higher distress included shorter-term survivorship, greater disruption, and poorer emotional well--being (EWB) at diagnosis. Survivors were divided into high- and low-COVID-19-impact subgroups; high-impact individuals endorsed higher perceived stress and lower EWB at diagnosis. CONCLUSION: Survivors reported lower COVID-related distress than community participants. While depression at diagnosis did not predict later distress, EWB was a strong predictor of response to a novel health-related stressor.

Association of Distance to Gynecologic Oncologist and Survival in a Rural Midwestern State.

Objectives: Rural ovarian cancer patients experience worse survival compared to urban patients. We assessed whether distance to gynecologic oncology specialists was associated with survival for patients in a rural state. Methods: Demographic, tumor, and treatment characteristics were extracted from the Iowa Cancer Registry for patients diagnosed between 1990 and 2018. Data were linked to the county-level 2018-2019 Area Health Resource File (number of surgeons and hospital beds per 100,000 population). Rurality was defined using 2013 Rural-Urban Continuum Codes; distance to the nearest gynecologic oncologist was calculated from the centroid of the county of residence to the centroid of the nearest county with a high volume health care center with a gynecologic oncologist. Associations with survival were assessed using multivariable Cox proportional hazards models. Results: Analyses included 1,562 ovarian cancer patients. Mean distance to gynecologic oncology was 60.8 miles, and median survival was 23 months. Unadjusted models showed increased distance from gynecologic oncology had progressively greater risk of death 30-49 miles (hazard ratio [HR] = 1.09, confidence interval [CI]: 1.04-1.15), 50-69 miles (HR = 1.19, CI: 1.07-1.32), 70+ miles (HR = 1.30, CI: 1.11-1.51). In adjusted models, association of distance to gynecologic oncology with risk of death was not significant; however, more advanced cancer stage and age, unmarried status, and higher county-level poverty were independently associated with increased risk of death. Conclusions: Above and beyond demographics and stage, distance to gynecologic oncology care was not an independent predictor of ovarian cancer survival. Further studies are needed to determine how to mitigate the factors contributing to worsened ovarian cancer survival among rural patients.

Rural and urban differences in perceptions, behaviors, and health care disruptions during the COVID-19 pandemic.

PURPOSE: The objective of this study was to assess perceptions, health behaviors, and disruptions related to the COVID-19 pandemic in a largely rural, Midwestern state, and to examine differences between rural and urban respondents. METHODS: A questionnaire was mailed August 2020 to a sample of 10,009 registered voters in Iowa ages 18-100 years, with oversampling from 6 select rural counties. Previously validated and tested items assessed COVID-19 precautions, health care disruptions, emotional reactions, health behavior changes, telehealth and experiences with the internet, and demographic characteristics. FINDINGS: There were 4,048 respondents (40% response rate); 65% were rural and 35% were urban residents. The average age of respondents was 58.3 years and 45% of respondents identified as female. Rural respondents reported less concern about COVID-19 in their community (29% vs 40%, P<.001) and lower perceived importance of social distancing (51% vs 64%, P<.001). Urban respondents more often reported experiencing disruption to daily living, stronger negative emotional reactions, and displayed more pronounced behavior change compared to their rural counterparts. For example, urban respondents reported more pandemic-related job losses (6% vs 4%, P = .05), disruptions to daily activities (48% vs 35%, P<.001), and use of telehealth services during the pandemic (24% vs 16%, P<.001). CONCLUSIONS: The majority of respondents reported disruptions to normal activities, medical appointment cancellations, and emotional distress during the first 6 months of the pandemic. The impact of the pandemic on urban residents appeared to be greater than for rural respondents. Timing of pandemic spread and varying beliefs are potential explanations.

Disparity of ovarian cancer survival between urban and rural settings.

OBJECTIVE: To determine if there is a difference in overall survival of patients with epithelial ovarian cancer in rural, urban, and metropolitan settings in the United States. METHODS: We performed a retrospective cohort study using 2004-2016 National Cancer Database (NCDB) data including high and low grade, stage I-IV disease. Bivariate analyses used Student's t-test for continuous variables and χ2 test for dichotomous variables. Kaplan-Meier curves estimated survival of patients based on location of residence, and univariate analyses using Cox proportional HR assessed survival based on baseline characteristics. Multivariate analysis was performed to account for significant covariates. Propensity score matching was used to validate the multivariate survival model. For all tests, p<0.05 was considered statistically significant. RESULTS: A total of 111 627 patients were included with a mean age of 62.5 years for metroolitan (range 18-90), 64.0 years for rural (range 19-90) and 63.2 years for urban areas (range 18-90). Of all patients included, 94 290 were in a metropolitan area (counties >1 million population or 50 000-999 999), 15 386 were in an urban area (population of 10 000-49 999), and 1951 were in a rural area (non-metropolitan/non-core population). Univariate Cox proportional hazards models showed clinically significant differences in survival in patients from metropolitan, urban, and rural areas. Multivariate Cox proportional hazards models showed a clinically significant increase in HRs for patients in rural settings (HR 1.17; 95% CI 1.06 to 1.29). Increasing age and stage, non-insured status, non-white race, and comorbidity were also significant for poorer survival. CONCLUSION: Patients with ovarian cancer who live in rural settings with small populations and greater distance to tertiary care centers have poorer survival. These differences hold after controlling for stage, age, and other significant risk factors related to poorer outcomes. To improve clinical outcomes, we need further studies to identify which of these factors are actionable.