Abstract
Purpose
Disparities in cancer care persist between patients living in rural versus urban areas. The COVID-19 pandemic may have impacted concerns related to care and personal health differently in rural cancer patients. Using survey data collected from cancer patients in western Pennsylvania, we examined pandemic-related distress, concerns related to cancer care, impact on personal health, and the extent to which these differed by urban–rural residence.
Methods
Patients filled out an initial survey in August–December 2020; a second survey was completed in March 2021. The following patient concerns related to the pandemic were evaluated: threat of COVID-19 to their health, pandemic-related distress, perceptions of cancer care, and vaccine hesitancy. Multivariable logistic regression models were used to examine relationships between these outcomes and urban–rural residence as well as patient-related factors, including anxiety symptoms and social support.
Results
The study sample included 1,980 patients, 17% resided in rural areas. COVID-19 represented a major or catastrophic threat to personal health for 39.7% of rural and 49.0% of urban patients (p = 0.0017). Patients with high general anxiety were 10-times more likely to experience pandemic-related distress (p < 0.001). In the follow-up survey (n = 983), vaccine hesitancy was twice as prevalent among rural patients compared to urban (p = 0.012).
Conclusions
The extent to which perceptions of the threat of COVD-19 to personal health and vaccine hesitancy exacerbates rural–urban disparities in cancer care and prognosis warrants further study. Cancer patients may be vulnerable to heightened anxiety and distress triggered by the pandemic.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10552-023-01696-w.
Keywords: COVID-19 pandemic, Cancer, Rural–urban disparities, Anxiety, Vaccine hesitancy
Introduction
The COVID-19 pandemic has stressed many United States (US) healthcare systems. During the pandemic, the rapid onslaught of COVID-19 patients requiring care caused many healthcare systems to deprioritize resources and care in other areas, including oncology [1]. While US metropolitan communities initially experienced the highest COVID-19 incidence and mortality, COVID-19 incidence and mortality subsequently became disproportionately higher in rural communities compared to metropolitan [2–5]. These rural–urban disparities in the impact of COVID-19 have been attributed to limited medical resources [6], community resistance to adoption of preventive measures [7], and, after vaccines became available, lower vaccination rates [8].
Cancer-related disparities persist between patients residing in rural and urban communities in the US [9]. Screening rates are lower in rural communities compared to urban [10, 11], and many cancers, including lung, colon, and breast cancer, are diagnosed at a later stage [12–14]. Consequently, cancer mortality may be higher among rural patients [12, 15, 16]. Several factors have been reported to contribute to these rural–urban disparities, including a greater distance to care and lower availability of specialized oncologic care, lower socio-economic status (SES), older population, and higher prevalence of cancer-related risk factors [9]. The extent to which rural–urban disparities in cancer care and outcomes have been exacerbated during the COVID-19 pandemic remains to be determined.
Compared to the general population, patients with cancer are at an increased risk of contracting COVID-19, experiencing serious complications, and dying from COVID-19, largely driven by disease- and treatment-related immune suppression [17–21]. Both patients and hospitals have sought to balance reducing risk of COVID-19 exposure for patients with cancer and providing cancer care. From March-June 2020, in-person clinic visits decreased by over 50% for US patients participating in the COVID-19 and Cancer Outcomes Study [22]. Delayed and interrupted care was reported by 44% of US breast cancer survivors surveyed in April 2020 [23], and results from the COVID-19 Impact Survey showed that cancer survivors were more likely to personally delay care or cancel appointments during the pandemic [24].
During the COVID-19 pandemic, patients with cancer have generally been reported to have experienced heightened levels of anxiety [25, 26]. However, some studies found no differences in levels of anxiety between cancer patients and the general population [27], and reported that cancer patients may actually have lower perceived stress compared to individuals without cancer [28]. Anxiety and stress experienced by patients can affect treatment response, reduce quality of life, and contribute to poorer prognosis [29–32]. Delay of cancer care during the pandemic may be a source of increased anxiety and distress, but a patient’s anxiety and distress may also influence their decisions to delay care [33]. Given longstanding rural disparities in cancer care and mental health outcomes [34, 35], the COVID-19 burden in rural communities may have particularly affected concerns related to cancer care, distress, anxiety, and self-reported health among cancer patients.
Survey data was collected from a sample of cancer patients (n = 1980) from western Pennsylvania during the first COVID-19 wave. We used this data to explore the extent to which the COVID-19 pandemic may have differentially impacted patients’ perceptions of threat of COVID-19 to their personal health, concerns regarding cancer care, pandemic-related distress, and levels of anxiety by urban–rural residence. We also characterized COVID-19 vaccine hesitancy among a subset (n = 983) of these patients recontacted during the COVID-19 vaccine rollout.
Materials and methods
Study population
Electronic medical record data from a large health care provider in western Pennsylvania were used to identify potential patient participants for a research study on the impact of the COVID-19 pandemic on cancer patients. Patients were eligible if they were at least 18 years old, had at least one appointment for cancer care between 13 March and 31 May 2020, and their treating physician had granted permission for them to be contacted about the study. An email invitation to participate in the study was sent to patients for whom an email address was available (n = 30,363) in August–October 2020. The email included a link to provide electronic informed consent. After providing consent, the patients were asked to fill out the first online survey. A reminder invitation was sent one week after the initial email. A total of 1,769 (5.8%) study patients were enrolled this way (the ‘email group’). Patients in this group were asked to fill out a second online survey in March 2021; 983 (55.6%) filled out this survey. REDCap was used to email the invitations to participate in the study, obtain informed consent and collect survey data. From among those without an email address (n = 18,839), we randomly selected a sample of 2000 subjects who were mailed a letter with information about the study. The letter included information on how to opt out of further contact about the study. Research assistants called the patients who did not opt out two weeks after the letters were mailed (they made up to three attempts to contact the subjects), discussed the study with them, and asked them to participate. After obtaining informed consent, the research assistant administered the survey by phone and entered the answers directly into the study-specific REDCap database. In total, 211 (10.6%) study patients were enrolled this way (the ‘letter group’). All study patients provided informed consent, and the study was approved by the University of Pittsburgh Human Research Protection Office.
Patient-related factors
Demographic information obtained via the survey included age, sex, race/ethnicity, educational attainment, primary medical insurance, and marital status. A minority status variable was created that collapsed race/ethnicity into categories of “white” and “any minority” (included all non-white and biracial patients). Educational attainment was categorized as: high school education (HSE) or less, some post-HSE (includes post-HSE training and some college), and college degree or higher. If a patient reported more than one type of medical insurance, they were assigned a primary insurance category using the following hierarchy: Medicare, Medicaid, private, and other. The Rural Urban Commuting Area (RUCA) codes for zip-code tabulating areas (ZCTAs) were used to assign patient’s residence zip code as urban (1–3) or rural (4–10) (Figure S1). Patients were also asked about the type of cancer they were diagnosed with, and whether they were currently receiving cancer treatment (and if so, about the type of treatment).
Psychosocial assessments
Emotional distress related to the COVID-19 pandemic was assessed using a modified version of the Impact of Event Scale (IES-COVID19) [36]. The IES is a validated 15-item (0–75 range) scale that assesses the frequency of common intrusion and avoidance responses to a specified traumatic stressor, (in this case “COVID-19”) during the previous week. Patients with an IES score > 25 were classified as experiencing moderate to severe distress (designated as “pandemic-related distress”) (Figure S2A). Among those patients who did not answer every item but answered ≥ 10 items for the IES-COVID 19 (n = 140), we imputed their missing item values by assigning these the average of their answered items. For those who answered less than 10 items, no IES-score (i.e., the score was set to missing) was analyzed.
General anxiety symptoms were assessed with the Generalized Anxiety Disorder Scale-7 (GAD-7). The GAD-7 is a validated seven item, self-rated scale (range 0–21) that assesses common symptoms of anxiety during the past two weeks and can be used as screening tool for generalized anxiety disorder [37]. Further clinical evaluation is recommended for GAD-7 scores ≥ 10 (designated as “high anxiety”) (Figure S2B). Among those patients who did not answer every item but did answer ≥ five items for the GAD-7 (n = 57), the imputation procedure as described for the IES score was applied. For those who answered less than five items had no GAD-7 score (i.e., the score was set to missing).
Emotional and tangible social support were assessed with a modified and validated eight-item version of the Medical Outcomes Study Social Support Survey [38]. These items were asked on a 0–4 scale (corresponding to “never”, “rarely”, “sometimes”, “usually”, “always”). The items were summed (range 0–32) to assign each patient a social support score, and those with scores greater than 16 were considered to have “high social support”.
Impact on health and worry
Patients’ perceptions of the impact of COVID-19 on their health were assessed with two face valid questions. The question “Which of the following statements accurately reflects your feelings on the potential impact of COVID-19 on your personal health?” was asked with the following response options of: COVID-19 represents a: (1) catastrophic, (2) major, (3) moderate, (4) minor, and (5) insignificant threat to my personal health. A second question, “How worried are you about getting COVID-19?”, was asked with response options of: (1) very worried, (2) worried, (3) neutral, (4) not very worried, (5) not at all worried. The impact on personal health and worry about contracting COVID-19 were both evaluated as ordinal predictor and as binary outcome (highest two compared to lowest three categories) in statistical models. Patients were also asked if they had ever been tested for COVID-19 and if they had ever tested positive for COVID-19.
Concern regarding cancer care
Patients’ concerns regarding their cancer care during the COVID-19 pandemic were assessed with two face valid questions. The first question addressed whether patients had any concerns about going to a doctor’s office or hospital for cancer treatment or follow-up appointments (no, yes). Patients were then asked whether these concerns have caused them to delay or stop treatment or cancel medical appointments (no, yes). These were evaluated as binary outcomes (no, yes) in statistical models.
Vaccine usage assessment
The follow-up survey administered in March 2021 to patients in the email group included several questions related to COVID-19 vaccines. The first question asked whether subjects had received a vaccine for COVID-19, with response options of: (1) yes, (2) no, (3), no, but I have an appointment to get it, and (4) no, but I was offered and refused. If the patient answered “no” to having received a vaccine (option 2), they were subsequently asked to indicate what they would do if they were offered a vaccine at the time of the survey, with the following response options: “Would definitely get it”, “Would probably get it”, “Would probably NOT get it”, “Would definitely NOT get it”, and “Don’t know”. Patients were considered not “vaccine hesitant” if they had received a COVID-19 vaccine or planned to (i.e., answered “yes” or “no, but I have an appointment to get it” to the first question) or had not yet received a COVID-19 vaccine but “Would definitely get it” or “Would probably get it” if offered (second question). All other patients were considered “vaccine hesitant.”
Statistical analysis
For each patient-related factor, the distribution within the entire cohort and by urban–rural residence was examined; Pearson’s Chi-square tests or t-tests were used to evaluate differences in patient-related factors between rural and urban patients. Associations between urban–rural residence and patient-related factors and outcomes related to the pandemic (e.g., pandemic-related distress) were evaluated using multivariable logistic regression models. The following covariates were selected a priori and adjusted for in our models: age, sex, minority status, educational attainment, marital status, reported living with cancer, survey group (email vs. letter), and month survey was filled out. All association estimates were expressed as odds ratios (OR) and corresponding 95% confidence intervals (CIs) were computed. To examine whether associations differed by urban–rural residence, the interaction between urban–rural residence and a given patient-related factor within these logistic regression models was evaluated, and analyses were stratified by urban–rural residence. All analyses were performed using R 4.1.2.
Results
The 1980 study patients in the cohort completed the initial survey in August–December 2020. Characteristics of the cohort at enrollment, overall and by urban–rural residence status, are presented in Table 1. The majority of the patients were female (60.8%) and self-reported as white (96.5%); the average age was 64.1 years. To the question “Are you currently living with cancer?”, 1036 (52.7%) said “yes”, and 761 (38.7%) indicated that they were “currently receiving treatment”. Among those not currently receiving treatment, 54.8% (n = 648) had finished their treatment, 26.1% (n = 309) were being watched (“don’t need treatment”), and thirteen had not started their treatment yet. Seventeen percent of the cohort (n = 345) resided in rural ZCTAs. Based on the GAD-7 score, 283 (14.4%) patients had high anxiety. Rural patients were less likely to have a college education or higher than urban patients (p < 0.001). No differences in the distribution of sex, age, minority status, marital status, anxiety, living with cancer, and currently receiving treatment were observed between the rural and urban patients.
Table 1.
Characteristics of the study cohort at enrollment and by urban–rural residence status
| Overall (na = 1980) | Urban (n = 1635) | Rural (n = 345) | pb | |
|---|---|---|---|---|
| Age (± sd; in years) | 64.1 (12.4) | 64.0 (12.5) | 64.8 (12.0) | 0.31 |
| Sex | 0.78 | |||
| Male | 770 (39.2%) | 638 (39.3%) | 132 (38.5%) | |
| Female | 1196 (60.8%) | 985 (60.7%) | 211 (61.5%) | |
| Minority | 0.11 | |||
| White (alone) | 1897 (96.5%) | 1560 (96.2%) | 337 (98.0%) | |
| Minority | 68 (3.5%) | 61 (3.8%) | 7 (2.0%) | |
| Marital status | 0.66 | |||
| Married | 1339 (67.8%) | 1103 (67.6%) | 236 (68.4%) | |
| Divorced | 259 (13.1%) | 218 (13.4%) | 41 (11.9%) | |
| Never married | 182 (9.2%) | 153 (9.4%) | 29 (8.4%) | |
| Widowed | 196 (9.9%) | 157 (9.6%) | 39 (11.3%) | |
| Educational attainment | < 0.001 | |||
| High school education or less | 356 (18.0%) | 273 (16.7%) | 83 (24.1%) | |
| Post high school education or some college | 542 (27.4%) | 421 (25.8%) | 121 (35.2%) | |
| College or higher | 1077 (54.5%) | 937 (57.4%) | 140 (40.7%) | |
| Survey group | 0.0018 | |||
| 1769 (89.3%) | 1477 (90.3%) | 292 (84.6%) | ||
| Letter | 211 (10.7%) | 158 (9.7%) | 53 (15.4%) | |
| Primary type of medical insurance | 0.038 | |||
| Medicare | 1118 (57.0%) | 911 (56.1%) | 207 (61.6%) | |
| Private | 639 (32.6%) | 550 (33.8%) | 89 (26.5%) | |
| Medicaid | 81 (4.1%) | 62 (3.8%) | 19 (5.7%) | |
| Other | 123 (6.3%) | 102 (6.3%) | 21 (6.2%) | |
| Social and emotional support | 0.35 | |||
| Low | 190 (9.9%) | 152 (9.7%) | 38 (11.3%) | |
| High | 1720 (90.1%) | 1423 (90.3%) | 297 (88.7%) | |
| Anxiety | 0.95 | |||
| No or low anxiety (GAD-7 score < 10) | 1684 (85.6%) | 1389 (85.6%) | 295 (85.5%) | |
| High anxiety (GAD-7 score ≥ 10) | 283 (14.4%) | 233 (14.4%) | 50 (14.5%) | |
| Reported currently living with cancer | 0.81 | |||
| No | 928 (47.3%) | 763 (47.1%) | 165 (47.8%) | |
| Yes | 1036 (52.7%) | 856 (52.9%) | 180 (52.2%) | |
| Type of cancer (among living with cancer) | 0.10 | |||
| Breast | 209 (20.2%) | 164 (19.2%) | 45 (25.1%) | |
| Colon and Rectum | 50 (4.8%) | 41 (4.8%) | 9 (5.0%) | |
| Leukemia | 142 (13.7%) | 114 (13.3%) | 28 (15.6%) | |
| Lung | 79 (7.6%) | 71 (8.3%) | 8 (4.5%) | |
| Lymphoma | 100 (9.7%) | 86 (10.1%) | 14 (7.8%) | |
| Myeloma | 61 (5.9%) | 51 (6.0%) | 10 (5.6%) | |
| Prostate | 91 (8.8%) | 83 (9.7%) | 8 (4.5%) | |
| Other | 301 (29.1%) | 244 (28.6%) | 57 (31.8%) | |
| Reported currently receiving cancer treatment | 0.39 | |||
| No | 1207 (61.3%) | 989 (60.9%) | 218 (63.4%) | |
| Yes | 761 (38.7%) | 635 (39.1%) | 126 (36.6%) | |
| Type of treatment (among currently in treatment) | 0.93 | |||
| Chemotherapy only | 149 (19.7%) | 125 (19.8%) | 24 (19.4%) | |
| Immunotherapy only | 91 (12.1%) | 76 (12.0%) | 15 (12.1%) | |
| Medication only | 276 (36.6%) | 231 (36.6%) | 45 (36.3%) | |
| Other only | 93 (12.3%) | 80 (12.7%) | 13 (10.5%) | |
| Two or more treatments | 146 (19.3%) | 119 (18.9%) | 27 (21.8%) | |
| Treatment status (among not currently in treatment) | 0.42 | |||
| I finished my treatment | 648 (54.8%) | 525 (54.2%) | 123 (57.2%) | |
| I don’t need to be treatment—I’m being watched | 309 (26.1%) | 250 (25.8%) | 59 (27.4%) | |
| I did not start treatment yet | 13 (1.1%) | 12 (1.2%) | 1 (0.5%) | |
| Other | 213 (18.0%) | 181 (18.7%) | 32 (14.9%) | |
| Ever been tested for COVID-19 | 0.90 | |||
| No | 1528 (78.0%) | 1262 (78.1%) | 266 (77.8%) | |
| Yes | 430 (22.0%) | 354 (21.9%) | 76 (22.2%) | |
| Tested positive for COVID-19 (among those tested) | 0.85 | |||
| No | 400 (95.5%) | 330 (95.4%) | 70 (95.9%) | |
| Yes | 19 (4.5%) | 16 (4.6%) | 3 (4.1%) |
aCounts across strata may not sum to total analytic sample size due to missing data
bP-values obtained from Pearson’s χ-square test for categorical variables; t-test for continuous variable
Worry about contracting COVID-19
Within the cohort, 927 patients (46.8%) indicated being worried or very worried about getting COVID-19 (Table S1 and Fig. 1A). Twenty-two percent (n = 430) of patients had been tested for COVID-19 with 19 (4.4%) testing positive (Table 1). There was no association between worry and having tested for COVID-19 or testing positive for COVID-19 (data not shown). Factors associated with a higher level of worry included being female and having a college education or higher (p < 0.05 for both). Patients with high anxiety were 4.77-times (95% CI: 3.48, 6.55) more likely to report worry about getting COVID-19, while those with high social support were less likely to report worry about getting COVID-19 (OR: 0.66, 95% CI: 0.48, 0.92). Patients reporting that they were currently living with cancer were more likely to report worry about getting COVID-19 (OR: 1.23, 95% CI: 1.02, 1.49). Urban–rural residence was not associated with worry about getting COVID-19, 42.6% of the rural patients versus 47.8% of the urban patients were worried or very worried about contracting COVID-19 (Table 2). Urban–rural residence did not interact with any patient-related factors to change the likelihood of reporting worry about contracting COVID-19 (Figure S3A).
Fig. 1.
Distribution of worry of contracting COVID-19 (a) and impact of COVID-19 on personal health (b) among cancer patients participating in study. Distributions are presented for urban–rural residence and other patient-related factors. Pearson’s chi-square tests were used to test the association between urban–rural residence, and *, **, ***, correspond to p < 0.05, p < 0.01, and p < 0.001
Table 2.
Associations with urban–rural residence for worry about getting COVID-19, impact of COVID-19 on personal health, distress, concerns related to cancer care due to the COVID-19 pandemic, and vaccine hesitancy
| Entire cohort | Urban | Rural | punadjusteda | OR (95% CI)b | padjustedb | |
|---|---|---|---|---|---|---|
| Worried about getting COVID-19 | 0.081 | 0.32 | ||||
| Not worried or not very worried | 1051 (53.1%) | 853 (52.2%) | 198 (57.4%) | 1.00 | ||
| Worried or very worried | 927 (46.9%) | 780 (47.8%) | 147 (42.6%) | 0.88 (0.69, 1.13) | ||
| Impact of COVID-19 on personal health | 0.0017 | 0.012 | ||||
| Moderate or less threat | 1039 (52.6%) | 831 (51.0%) | 208 (60.3%) | 1.00 | ||
| Major or catastrophic threat | 935 (47.4%) | 798 (49.0%) | 137 (39.7%) | 0.73 (0.57, 0.93) | ||
| Experienced moderate to severe distress | 0.46 | 0.53 | ||||
| No | 1464 (74.5%) | 1203 (74.2%) | 261 (76.1%) | 1.00 | ||
| Yes | 501 (25.5%) | 419 (25.8%) | 82 (23.9%) | 0.91 (0.68, 1.22) | ||
| Concerned about going to a doctor’s office or hospital for current treatment or follow-up appointments | 0.31 | 0.76 | ||||
| No | 1221 (62.1%) | 999 (61.6%) | 222 (64.5%) | 1.00 | ||
| Yes | 744 (37.9%) | 622 (38.4%) | 122 (35.5%) | 0.96 (0.75, 1.24) | ||
| Delayed or stopped treatment or cancelled medical appointments | 0.67 | 0.53 | ||||
| No | 1647 (84.6%) | 1361 (84.8%) | 286 (83.9%) | 1.00 | ||
| Yes | 299 (15.4%) | 244 (15.2%) | 55 (16.1%) | 1.11 (0.80, 1.55) | ||
| Hesitant to get COVID-19 vaccine | 0.012 | 0.012 | ||||
| No | 900 (91.7%) | 772 (92.7%) | 128 (86.5%) | 1.00 | ||
| Yes | 81 (8.3%) | 61 (7.3%) | 20 (13.5%) | 2.07 (1.18, 3.65) |
aP-value obtained from Pearson’s χ-square test
bAssociation estimates and p-values obtained from logistic regression models adjusted for age, sex, minority status, educational attainment, marital status, reported living with cancer, survey group, and month of survey
Impact of COVID-19 on personal health
Forty-seven percent of patients (n = 935) reported that COVID-19 represented a major or catastrophic threat to their personal health (Table S2 and Fig. 1B). Patient-related factors associated with reporting that COVID-19 represented a major or catastrophic threat to personal health included belonging to a minority group (p = 0.030) and having never married (p < 0.001). Patients with high anxiety were more likely (OR: 3.85, 95% CI: 2.84, 5.23) and those with high social support were less likely (OR: 0.69, 95% CI: 0.50, 0.96) to report that COVID-19 represented a major or catastrophic threat to their health. Patients reporting that they were currently living with cancer were 1.48-times (95% CI: 1.23, 1.79) more likely to report that COVID-19 represented a major or catastrophic threat to their health, especially those with leukemia, lung, myeloma, and “other” cancers (p < 0.05 for all). Patients currently treated with two or more treatments were 2.23-times (95% CI: 1.49, 3.35) more likely to report that COVID-19 represented a major or catastrophic threat to their health compared to those not currently receiving treatment. Rural patients were less likely to report that COVID-19 represented a major or catastrophic threat to their health than urban patients (39.7% vs. 49.0%, p = 0.0017; OR: 0.73, 95% CI: 0.57, 0.93; Table 2). Urban–rural residence interacted with educational attainment, and rural patients with some post-HSE or college degree or higher were twice as likely to report that COVID-19 represented a major or catastrophic threat to their health (p = 0.061 and 0.095, for interaction between urban–rural residence and some post-HSE and college degree or higher, respectively) (Figure S3B).
Patient-related factors for reporting pandemic-related distress
A quarter of the patients (n = 501) reported experiencing pandemic-related distress during the week before completing their initial survey. Older age was associated with a lower likelihood of reporting distress (p < 0.001) (Table S3). Females were 2.32-times (95% CI: 1.81, 2.96) more likely to report experiencing distress than males. High anxiety was positively associated with likelihood of experiencing distress (OR: 10.06, 95% CI: 7.35, 13.78), while having high social support was inversely associated with likelihood of distress (OR: 0.62, 95% CI: 0.44, 0.89). The likelihood of distress was higher for patients reporting currently living with cancer compared to those not (OR: 1.26, 95% CI: 1.01, 1.58). In addition, the likelihood of distress was higher for those reporting that COVID-19 represented a major or catastrophic threat to their personal health (OR = 1.88, 95% CI: 1.67, 2.12), and for those worried about getting COVID-19 (OR = 2.06, 95%CI: 1.84, 2.32) (Table 3). Although urban–rural residence was not associated with distress (Table 2), the likelihood of distress was higher for rural patients with some post-HSE (OR: 2.22, 95% CI: 1.00, 4.92), while no association was observed among urban patients (p = 0.0018 for interaction between urban–rural residence and some post-HSE) (Fig. 2A and Table S3).
Table 3.
Associations between impact of COVID-19 on personal health, worry about getting COVID-19 and pandemic-related distress and concerns related to cancer care
| Odds Ratio (95% CI)a | pinteractionb | |||
|---|---|---|---|---|
| Entire Cohort | Urban | Rural | ||
| Experienced moderate to severe distress | ||||
| Impact on personal health | 1.88 (1.67, 2.12) | 1.85 (1.62, 2.10) | 2.13 (1.57, 2.87) | 0.51 |
| Worry about getting COVID-19 | 2.06 (1.84, 2.32) | 1.97 (1.74, 2.24) | 2.85 (2.01, 4.05) | 0.13 |
| Concerned about going to a doctor’s office or hospital for cancer treatment or follow-up appointments | ||||
| Impact on personal health | 2.23 (2.00, 2.49) | 2.36 (2.08, 2.67) | 1.89 (1.48, 2.41) | 0.18 |
| Worry about getting COVID-19 | 2.63 (2.35, 2.95) | 2.78 (2.44, 3.16) | 2.21 (1.71, 2.87) | 0.080 |
| Delayed or stopped treatment or cancelled medical appointments | ||||
| Impact on personal health | 1.97 (1.71, 2.27) | 1.98 (1.69, 2.33) | 1.91 (1.39, 2.63) | 0.99 |
| Worry about getting COVID-19 | 2.48 (2.13, 2.89) | 2.58 (2.17, 3.07) | 2.11 (1.49, 2.97) | 0.30 |
aAssociation estimates obtained from logistic model adjusted for age, sex, minority status, educational attainment, marital status, living with cancer, survey group, and month of survey. All estimates had a p < 0.001 within all groups
bP-value for interaction obtained from interaction term between urban–rural residence and COVID-19 concern of interest (either impact on personal health or worry about getting COVID-19) included in logistic model adjusted for age, sex, minority status, educational attainment, marital status, reported living with cancer, survey group, month of survey, urban–rural residence, and COVID-19 concern of interest
Fig. 2.
Associations between distress (a), any concerns (b), and delaying care (c) and patient-related factors stratified by urban–rural residence. Odds ratios (ORs) and corresponding 95% confidence intervals (CI) are presented in the plots. Association estimates were obtained from logistic regression models stratified by urban–rural residence and adjusted for age, sex, minority status, educational attainment, marital status, reported living with cancer, survey group, and month of survey. P-value for interaction obtained from interaction term between urban–rural residence and patient-related factor of interest included in logistic model adjusted for age, sex, minority status, educational attainment, marital status, reported living with cancer, survey group, month of survey, urban–rural residence, and patient-related factor (if not already adjusted for in model). The ORs for distress and anxiety were too large to be presented in the plots and were 9.12 (95% CI 6.48, 12.83) and 19.81 (95% CI 7.81, 50.26) for urban and rural patients, respectively. Among rural patients with cancer, the OR for minority status and delay of care was 4.76 (95% CI 0.92, 24.69). Symbols “^”, “*”, “**”, correspond to p < 0.1, p < 0.05, and p < 0.01 significance levels, respectively
Concerns regarding cancer care during the COVID-19 pandemic
Within our cohort, 744 patients (38%) expressed concerns about going to a doctor’s office or hospital for cancer treatment or follow-up appointments. Females, those with a college degree or higher, and those with high anxiety were more likely to express concerns (p < 0.01 for all) (Table S4). Patients reporting that they were currently living with cancer were 1.31-times (95% CI: 1.08, 1.60) more likely to express concerns. The likelihood of expressing concerns was higher for those reporting that COVID-19 represented a major or catastrophic threat to their personal health as well as those worried about getting COVID-19 (Table 3). The prevalence of rural and urban patients with concerns was similar, 38.4% and 35.5%, respectively (Table 2). Rural patients with some post-HSE were 2.03-times (95% CI: 1.01, 4.10) more likely to express concerns while no association was observed among urban (p = 0.035 for interaction between urban–rural residence and some post-HSE) (Fig. 2B and Table S4). The association between worry about getting COVID-19 and expressing concerns was stronger among urban patients (OR = 2.78, 95% CI: 2.44, 3.16) compared to rural (OR = 2.21, 95% CI: 1.71, 2.87) (p = 0.080 for interaction between urban–rural residence and worry about getting COVID-19) (Table 3).
Delaying or stopping treatment or cancelling medical appointments due to COVID-19 concerns
The prevalence in our cohort of delaying or stopping treatment or cancelling medical appointments due to concerns related to the COVID-19 pandemic was 15% (n = 299). Females were more likely to delay care than males (p = 0.043) (Table S5). High anxiety was associated with a 3.34-times higher likelihood of delaying care (95% CI: 2.40, 4.64). High social support was associated with a lower likelihood of delaying care (OR: 0.62, 95% CI: 0.41, 0.94). Reporting that COVID-19 represented a major or catastrophic threat to their personal health as well as being worried about contracting COVID-19 were strongly associated with higher likelihood of delaying care (Table 3). Although urban–rural residence was not associated with delaying care (Table 2), rural patients currently receiving treatment were 3.09-times (95% CI: 1.32, 7.25) more likely to delay care compared to rural patients not undergoing treatment, but no association between receiving current treatment and delaying care was observed among urban patients (p = 0.024 for interaction between urban–rural residence and delaying care) (Fig. 2C and Table S5).
Vaccine hesitancy during the COVID-19 pandemic
Among the 983 study patients who filled out the follow-up survey, 771 (78.4%) had already received the COVID-19 vaccine, 53 (5.4%) had an appointment to get it, and 158 (16.1%) had not received the vaccine at the time of survey completion. Eight percent (n = 81) of patients were vaccine hesitant. Rural patients were twice as likely to be vaccine hesitant compared to urban patients (p = 0.012) (Table 2). Older age, college degree or higher, and high anxiety were associated with lower likelihood of vaccine hesitancy (p < 0.05 for all) (Table 4). Currently living with cancer and currently receiving cancer treatment were not associated with vaccine hesitancy.
Table 4.
Associations between patient-related factors and vaccine hesitancy
| Not Hesitant | Hesitant | OR (95% CI)a | pa | |
|---|---|---|---|---|
| Age (in years) | 0.95 (0.93, 0.97) | < 0.001 | ||
| Sex | ||||
| Female | 360 (92.3%) | 30 (7.7%) | 1.00 | |
| Male | 534 (91.3%) | 51 (8.7%) | 0.87 (0.52, 1.45) | 0.58 |
| Minority | ||||
| White (alone) | 873 (91.8%) | 78 (8.2%) | 1.00 | |
| Minority | 23 (92.0%) | 2 (8.0%) | 0.92 (0.20, 4.12) | 0.91 |
| Marital status | ||||
| Married | 644 (92.3%) | 54 (7.7%) | 1.00 | |
| Divorced | 108 (90.8%) | 11 (9.2%) | 1.19 (0.59, 2.42) | 0.62 |
| Never married | 81 (88.0%) | 11 (12.0%) | 0.90 (0.41, 1.97) | 0.79 |
| Widowed | 65 (92.9%) | 5 (7.1%) | 1.43 (0.51, 4.01) | 0.49 |
| Educational attainment | ||||
| High school education or less | 91 (85.8%) | 15 (14.2%) | 1.00 | |
| Post high school education or some college | 239 (89.5%) | 28 (10.5%) | 0.64 (0.31, 1.33) | 0.23 |
| College or higher | 565 (93.7%) | 38 (6.3%) | 0.34 (0.17, 0.68) | 0.0022 |
| Primary type of medical insurance | ||||
| Medicare | 498 (94.0%) | 32 (6.0%) | 1.00 | |
| Private | 317 (91.1%) | 31 (8.9%) | 0.79 (0.41, 1.54) | 0.49 |
| Medicaid | 23 (76.7%) | 7 (23.3%) | 1.38 (0.44, 4.34) | 0.58 |
| Other | 53 (85.5%) | 9 (14.5%) | 1.06 (0.41, 2.69) | 0.91 |
| Social and emotional support | ||||
| Low | 82 (95.3%) | 4 (4.7%) | 1.00 | |
| High | 790 (91.1%) | 77 (8.9%) | 2.09 (0.71, 6.16) | 0.18 |
| Anxiety | ||||
| No or low anxiety (GAD score < 10) | 789 (91.5%) | 73 (8.5%) | 1.00 | |
| High anxiety (GAD score ≥ 10) | 106 (93.0%) | 8 (7.0%) | 0.31 (0.13, 0.77) | 0.012 |
| Reported currently living with cancer | ||||
| No | 436 (90.5%) | 46 (9.5%) | 1.00 | |
| Yes | 457 (93.1%) | 34 (6.9%) | 0.81 (0.49, 1.32) | 0.39 |
| Type of cancer (among reported living with cancer)b | ||||
| Breast | 89 (95.7%) | 4 (4.3%) | 0.48 (0.16, 1.41) | 0.18 |
| Colon and Rectum | 20 (90.9%) | 2 (9.1%) | 0.37 (0.05, 2.96) | 0.35 |
| Leukemia | 65 (89.0%) | 8 (11.0%) | 1.80 (0.77, 4.22) | 0.18 |
| Lung | 35 (97.2%) | 1 (2.8%) | 0.30 (0.04, 2.30) | 0.25 |
| Lymphoma | 43 (95.6%) | 2 (4.4%) | 0.50 (0.11, 2.20) | 0.36 |
| Myeloma | 32 (94.1%) | 2 (5.9%) | 0.79 (0.18, 3.51) | 0.75 |
| Prostate | 48 (96.0%) | 2 (4.0%) | 0.63 (0.14, 2.90) | 0.55 |
| Other | 123 (90.4%) | 13 (9.6%) | 1.11 (0.55, 2.24) | 0.77 |
| Reported currently receiving cancer treatment | ||||
| No | 550 (91.4%) | 52 (8.6%) | 1.00 | |
| Yes | 343 (92.5%) | 28 (7.5%) | 1.14 (0.62, 2.11) | 0.67 |
| Type of treatment (among reported currently in treatment)c | ||||
| Chemotherapy only | 63 (91.3%) | 6 (8.7%) | 1.06 (0.37, 3.06) | 0.92 |
| Immunotherapy only | 36 (85.7%) | 6 (14.3%) | 2.35 (0.81, 6.82) | 0.12 |
| Medication only | 133 (93.7%) | 9 (6.3%) | 1.01 (0.45, 2.26) | 0.99 |
| Other only | 46 (95.8%) | 2 (4.2%) | 0.73 (0.16, 3.36) | 0.69 |
| Two or more treatments | 63 (94.0%) | 4 (6.0%) | 0.97 (0.31, 3.09) | 0.96 |
aAssociation estimates and p-values obtained from logistic regression models adjusted for age, sex, minority status, educational attainment, marital status, reported living with cancer, survey group, and month of survey
bCompared to those who did not report currently living with cancer
cCompared to those who reported not currently receiving cancer treatment
Discussion
Among 1980 cancer patients in western Pennsylvania surveyed during the first wave of the COVID-19 pandemic, being a rural versus being an urban resident was associated with differences pertaining to: (1) reporting that COVID-19 represented a major or catastrophic threat to personal health, and (2) reporting vaccine hesitancy during the first phase of the vaccine rollout. Compared to urban patients, rural patients were less likely to report that COVID-19 represented a major or catastrophic threat to their personal health. Rural patients also expressed more vaccine hesitancy than urban patients.
For both urban and rural cancer patients, having higher levels of general anxiety (assessed using GAD-7) was associated with higher prevalence of all COVID-19 pandemic-related outcomes surveyed. This association was particularly strong for pandemic-related distress, where we observed that patients with high anxiety were 10-times more likely to report pandemic-related distress. A quarter of our patients reported moderate or severe pandemic-related distress, which was lower than the prevalence of pandemic-related distress (37%) in a study of older British adults [39]. While our study was the first to use a validated IES-COVID19 scale [36] to evaluate distress due to the pandemic, several studies have adapted the published IES-revised scale, which includes symptoms of hyperarousal, as well as intrusion and avoidance, to assess pandemic-related distress [40]. Using the IES-revised scale, the prevalence of severe post-traumatic distress (PTSD) symptoms varied across different cancer patient populations during the first wave of the COVID-19 pandemic. Severe distress was reported by 60% of Italian women with cancer [41], 32% of Chinese thyroid cancer patients [42], and 21% of French cancer patients [43]. Among French cancer patients, those whose cancer care was adjusted were twice as likely to experience PTSD symptoms [43].
Fifteen percent of patients in our study reported high anxiety levels, which seems low when compared to studies of Italian women with cancer [41] and Chinese thyroid cancer patients [42] that found that 40% of patients reported high anxiety (assessed using GAD-7, as in our study). Both published studies also identified an association between disruption of cancer care and higher levels of anxiety, consistent with the association between anxiety and delaying or stopping cancer care in our study. In a prior study of US cancer patients, high levels of anxiety were reported among those who were moderately or severely distressed due to the pandemic (based on IES-revised) [44]. Given that the pandemic affected different global populations at different timepoints in 2020, this may contribute to differing levels of distress and anxiety across studies. Together, these findings strongly suggest that during a pandemic cancer patients may require specialized follow-up that includes mental health care, regardless of urban–rural residence.
Within our cohort, factors associated with delaying or stopping treatment or canceling medical appointments included being female, having a college degree or higher, and high anxiety. High social support on the other hand was associated with a lower likelihood of delaying care. The prevalence of delaying care was 15% in our cohort, consistent with the study by Caston et al. that found that ~ 13% of US cancer patients chose to delay their care from May–December 2020 [45]. During the COVID-19 pandemic, US cancer survivors were 44% more likely to cancel doctor’s appointments compared to adults without cancer [24]. In line with our results, Caston et al. found that patients more fearful of COVID-19 were more likely to delay care and interrupt treatment [45]. The increased likelihood of delaying and stopping care among rural patients currently in treatment in our study is somewhat unexpected, given that rural patients reported that COVID-19 represented lower threat to their personal health. Further research is needed to understand additional factors involved in a patient’s decision to delay care during the pandemic.
In the US, cancer patients were generally prioritized to receive the COVID-19 vaccine, given their higher risk of severe disease and death from infection [17–21]. While 9% of our study sample expressed vaccine hesitancy, this was lower than reported vaccine hesitancy in the US general population, which ranged from 17% in January 2021 to 25% in May 2021 [8]. The prevalence of vaccine hesitancy among cancer patients in other studies varied and may be dependent on location of study population and timepoint in 2021. From an online survey conducted from January–February 2021 (mostly US adults), 13% of cancer patients reported expressing vaccine hesitancy [46] while a study of Australian adult cancer patients from June–August 2021 found that 6% of patients would definitely not or probably not take the COVID-19 vaccine if offered [47]. Among Mexican women with breast cancer surveyed in March 2021, 34% expressed vaccine hesitancy [48]. Prior studies have shown that rural US residents were more vaccine hesitant than urban residents [8, 49], and the adult vaccination coverage from December 2020–April 2021 was 38% in urban areas of US while only 29% in rural areas of US [50]. In a survey of US adults in March 2020, 40% of those who reported living in rural areas expressed vaccine hesitancy compared to 30% in urban areas [49]. Vaccine hesitancy was 20% more likely in more rural counties (i.e. micropolitan and non-core) compared to large metropolitan counties [8]. The general higher prevalence of vaccine hesitancy within rural US populations may extend to rural cancer patient populations, presenting another factor that may exacerbate rural–urban disparities in cancer prognosis and care.
Our study has several limitations. All responses were self-reported and thus susceptible to response bias. The mostly online convenience sampling frame may have introduced sampling bias with regards to age (use of the internet) and socio-economic status (access to the internet). We could not examine the impact of racial disparities and patient factors on these pandemic-related outcomes since the sample of minority patients was small. A strength of our study, however, is that the overall sample size is quite large. Our survey also captured numerous detailed outcomes and psychological measures.
In conclusion, our analyses indicate that urban–rural residence may influence how cancer patients perceive the potential threat of COVID-19 to their health. While vaccine hesitancy was low among cancer patients overall in this western Pennsylvania sample, rural patients were more likely to be hesitant. This hesitancy should be addressed by oncologists and the cancer care team. During a pandemic, urban–rural residence continues to be a crucial factor to consider during cancer care and could contribute to disparities in clinical outcomes.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgments
We thank the UPMC Hillman Cancer Center academic and network physicians granting permission for their patients to be contacted and invited to participate in this study and all of the participating patients who were graciously willing to contribute their time to the study and share their experiences.
Author contributions
KD: Formal analysis, methodology, data curation, writing—original draft, and writing—review and editing. MR: Conceptualization, methodology, project administration, investigation, resources, writing—original draft, and writing—review and editing. LR: Conceptualization, investigation, resources, and writing—review and editing. CAL: Conceptualization, methodology, and writing—review and editing. SD: Investigation, and writing—review and editing. HA: writing—original draft, and writing—review and editing. BS: Investigation, and writing—review and editing. DHB: Conceptualization, methodology, writing—original draft, and writing—review and editing. BD: Conceptualization, formal analysis, data curation, methodology, project administration, investigation, resources, writing—original draft, and writing—review and editing.
Funding
This project was supported in part by NIH/NCI P30CA047904.
Data availability
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethical approval
The study was approved by the University of Pittsburgh Human Research Protection Office.
Consent to participate
Informed consent was obtained from all individual patient participants included in the study.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.