Reexamining Social Determinants of Health Data Collection in the COVID-19 Era.

This Viewpoint describes the association of various factors, including demographic factors, disease-related factors, and social determinants of health, with cancer treatment delays among a cohort of patients across multiple sites who had all tested positive for SARS-CoV-2.

Factors Associated With Cancer Treatment Delay Among Patients Diagnosed With COVID-19.

Importance: The COVID-19 pandemic led to disruptions in delivery of cancer treatments; factors associated with treatment delay among patients with cancer who contract COVID-19 need further characterization. Objective: To assess the associations of patient factors, social determinants of health, severity of COVID-19, and timing of COVID-19 diagnosis with the risk of treatment delay. Design, Setting, and Participants: This prospective cohort study was conducted from March 2020 through July 2021 at 60 academic and community medical practices in the United States. Participants included patients with any cancer diagnosis who were scheduled for treatment and contracted COVID-19. Data were analyzed in February 2022. Exposure: Positive test result for SARS-CoV-2. Main Outcomes and Measures: The main outcomes were treatment delay, defined as more than 14 days between the date originally planned for treatment and the date of initiation of therapy, or discontinuation of therapy. Multivariable analyses were used to assess outcomes. Results: A total of 3028 patients (1470 patients [49%] aged ≥65 years; 1741 [58%] women) were included in the registry. With 962 of 2103 patients (46%) experiencing anticancer drug delay or discontinuation, delays were higher among Black patients compared with White patients (odds ratio [OR], 1.87; 95% CI, 1.40-2.51), Hispanic or Latino patients compared with non-Hispanic or Latino patients (OR, 1.91; 95% CI, 1.34-2.72), patients with 2 or more comorbidities compared with patients with 0 to 1 (OR, 1.23; 95% CI, 1.00-1.53), patients with metastatic disease rather than locoregional disease (OR, 1.63; 95% CI, 1.29-2.05), and patients who experienced COVID-19 complications compared with those who did not (OR, 1.52; 95% CI, 1.24-1.86). Residing in an area with a higher proportion of residents reporting Hispanic or Latino ethnicity (OR, 0.76; 95% CI, 0.60-0.95) and contracting COVID-19 later in the pandemic, compared with those who were infected in March to June 2020, (eg, January to March 2021: OR, 0.38; 95% CI, 0.26-0.53) were associated with lower likelihood of drug therapy delay. A total of 95 of 202 patients (47%) experienced delay or discontinuation of radiation treatment, with having 2 or more comorbidities associated with delay (OR, 2.69; 95% CI, 1.20-6.20). Higher local-area median household income was associated with lower likelihood of radiation treatment delay (OR, 0.41; 95% CI, 0.17-0.94). There were 89 of 125 patients (71%) who experienced surgical treatment delay, and delays were higher among patients in the South compared with those in the Midwest (OR, 9.66; 95% CI, 2.14-52.3). Interestingly, patients with 2 or more comorbidities, compared with those with 0 to 1, experienced lower likelihoods of surgical treatment delay (OR, 0.26; 95% CI, 0.07-0.88). Conclusions and Relevance: Our findings suggest that individual patient factors, social determinants of health, and COVID-19 severity and diagnosis date were associated with exacerbated health disparities during the pandemic in regards to cancer treatment delay.

Assessment of Regional Variability in COVID-19 Outcomes Among Patients With Cancer in the United States.

Importance: The COVID-19 pandemic has had a distinct spatiotemporal pattern in the United States. Patients with cancer are at higher risk of severe complications from COVID-19, but it is not well known whether COVID-19 outcomes in this patient population were associated with geography. Objective: To quantify spatiotemporal variation in COVID-19 outcomes among patients with cancer. Design, Setting, and Participants: This registry-based retrospective cohort study included patients with a historical diagnosis of invasive malignant neoplasm and laboratory-confirmed SARS-CoV-2 infection between March and November 2020. Data were collected from cancer care delivery centers in the United States. Exposures: Patient residence was categorized into 9 US census divisions. Cancer center characteristics included academic or community classification, rural-urban continuum code (RUCC), and social vulnerability index. Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. The secondary composite outcome consisted of receipt of mechanical ventilation, intensive care unit admission, and all-cause death. Multilevel mixed-effects models estimated associations of center-level and census division-level exposures with outcomes after adjustment for patient-level risk factors and quantified variation in adjusted outcomes across centers, census divisions, and calendar time. Results: Data for 4749 patients (median [IQR] age, 66 [56-76] years; 2439 [51.4%] female individuals, 1079 [22.7%] non-Hispanic Black individuals, and 690 [14.5%] Hispanic individuals) were reported from 83 centers in the Northeast (1564 patients [32.9%]), Midwest (1638 [34.5%]), South (894 [18.8%]), and West (653 [13.8%]). After adjustment for patient characteristics, including month of COVID-19 diagnosis, estimated 30-day mortality rates ranged from 5.2% to 26.6% across centers. Patients from centers located in metropolitan areas with population less than 250 000 (RUCC 3) had lower odds of 30-day mortality compared with patients from centers in metropolitan areas with population at least 1 million (RUCC 1) (adjusted odds ratio [aOR], 0.31; 95% CI, 0.11-0.84). The type of center was not significantly associated with primary or secondary outcomes. There were no statistically significant differences in outcome rates across the 9 census divisions, but adjusted mortality rates significantly improved over time (eg, September to November vs March to May: aOR, 0.32; 95% CI, 0.17-0.58). Conclusions and Relevance: In this registry-based cohort study, significant differences in COVID-19 outcomes across US census divisions were not observed. However, substantial heterogeneity in COVID-19 outcomes across cancer care delivery centers was found. Attention to implementing standardized guidelines for the care of patients with cancer and COVID-19 could improve outcomes for these vulnerable patients.

Cancer Clinical Trial Participation at the 1-Year Anniversary of the Outbreak of the COVID-19 Pandemic.

Importance: During the initial outbreak of the COVID-19 pandemic, cancer clinical trial participation decreased precipitously. Given the continued pandemic-especially the severe wave of new cases and deaths in winter 2020 to 2021-a vital question is whether trial enrollments have remained low or even worsened. Objective: To examine the experience of cancer clinical trial enrollment 1 year after the COVID-19 outbreak. Design, Setting, and Participants: This cohort study examines initial enrollments to treatment trials and cancer control and prevention (CCP) trials conducted by the SWOG Cancer Research Network between January 1, 2016, and February 28, 2021. Participants include patients enrolled in the trials. Exposures: Landmark time points reflecting the onset and the apex, respectively, of the initial COVID-19 wave (March 1 to April 25, 2020) and the winter 2020 to 2021 wave (October 4, 2020, to January 23, 2021). Main Outcomes and Measures: This study used interrupted time-series analysis to examine enrollments over time related to the COVID-19-derived exposure variables using negative-binomial regression. Relative risk (RR) estimates representing weekly enrollment changes compared with expected rates (had the pandemic not occurred) were derived. The numbers of enrollments lost during the pandemic were estimated. Results: Overall, 29 398 patients (mean [SD] age, 60.3 [13.2] years) were enrolled (24 034 before the pandemic and 5364 during the pandemic), with 9198 patients (31.3%) aged 65 years or older, 17 199 female patients (58.6%), 3039 Black patients (10.8%), and 2260 Hispanic patients (7.9%). Most enrollments (19 451 [66.2%]) were to treatment trials. During the initial COVID-19 wave, there was a 9.0% model-estimated weekly reduction in enrollments (RR, 0.91; 95% CI, 0.89-0.93; P < .001), with effects compounding each week. Enrollment recovered thereafter, but decreased again during the winter 2020 to 2021 wave, although by only 2.0% each week (RR, 0.98; 95% CI, 0.97-0.99; P < .001). Overall, during the pandemic, actual enrollments were 77.3% of expected enrollments (5364 of 6913 enrollments; 95% CI, 70.5%-85.0%; P < .001). Actual enrollments were 54.0% of expected enrollments for CCP trials (1421 of 2641 enrollments; 95% CI, 43.0%-67.0%; P < .001) and 91.0% of expected enrollments for treatment trials (3922 of 4304 enrollments; 95% CI, 81.0%-102.0%; P = .12). Conclusions and Relevance: In this cohort study, clinical trial enrollments decreased during the full year of the COVID-19 pandemic. Enrollment reductions were primarily to CCP trials, whereas, remarkably, there was not strong evidence of enrollment reductions to treatment trials. This finding suggests that clinical research rapidly adapted to the circumstances of enrolling and treating patients on protocols during the COVID-19 pandemic.

Care Delivery Impact of the COVID-19 Pandemic on Breast Cancer Care.

PURPOSE: COVID-19 has altered healthcare delivery. Previous work has focused on patients with cancer and COVID-19, but little has been reported on healthcare system changes among patients without COVID-19. METHODS: We performed a retrospective study of patients with breast cancer (BC) in New York City between February 1, 2020, and April 30, 2020. New patients were included as were patients scheduled to receive intravenous or injectable therapy. Patients with COVID-19 were excluded. Demographic and treatment information were obtained by chart review. Delays and/or changes in systemic therapy, surgery, radiation, and radiology related to the pandemic were tracked, along with the reasons for delay and/or change. Univariate and multivariable analysis were used to identify factors associated with delay and/or change. RESULTS: We identified 350 eligible patients, of whom 149 (42.6%) experienced a delay and/or change, and practice reduction (51.0%) was the most common reason. The patients who identified as Black or African American, Asian, or Other races were more likely to experience a delay and/or change compared with White patients (Black, 44.4%; Asian, 47.1%; Other, 55.6%; White, 31.4%; P = .001). In multivariable analysis, Medicaid compared with commercial insurance (odds ratio [OR], 3.04; 95% CI, 1.32 to 7.27) was associated with increased odds of a delay and/or change, whereas stage II or III BC compared with stage I (OR, 0.38; 95% CI, 0.15 to 0.95; and OR, 0.28; 95% CI, 0.08 to 0.092, respectively) was associated with decreased odds of a delay and/or change. CONCLUSION: Almost half of the patients with BC without COVID-19 had a delay and/or change. We found racial and socioeconomic disparities in the likelihood of a delay and/or change. Further studies are needed to determine the impact these care alterations have on BC outcomes.

Perioperative Morbidity and Mortality of Patients With COVID-19 Who Undergo Urgent and Emergent Surgical Procedures.

OBJECTIVE: To evaluate the perioperative morbidity and mortality of patients with COVID-19 who undergo urgent and emergent surgery. SUMMARY BACKGROUND DATA: Although COVID-19 infection is usually associated with mild disease, it can lead to severe respiratory complications. Little is known about the perioperative outcomes of patients with COVID-19. METHODS: We examined patients who underwent urgent and emergent surgery at 2 hospitals in New York City from March 17 to April 15, 2020. Elective surgical procedures were cancelled throughout and routine, laboratory based COVID-19 screening was instituted on April 1. Mortality, complications, and admission to the intensive care unit were compared between patients with COVID-19 detected perioperatively and controls. RESULTS: Among 468 subjects, 36 (7.7%) had confirmed COVID-19. Among those with COVID-19, 55.6% were detected preoperatively and 44.4% postoperatively. Before the routine preoperative COVID-19 laboratory screening, 7.7% of cases were diagnosed preoperatively compared to 65.2% after institution of screening (P = 0.0008). The perioperative mortality rate was 16.7% in those with COVID-19 compared to 1.4% in COVID-19 negative subjects [aRR = 9.29; 95% confidence interval (CI), 5.68-15.21]. Serious complications were identified in 58.3% of COVID-19 subjects versus 6.0% of controls (aRR = 7.02; 95%CI, 4.96-9.92). Cardiac arrest, sepsis/shock, respiratory failure, pneumonia, acute respiratory distress syndrome, and acute kidney injury were more common in those with COVID-19. The intensive care unit admission rate was 36.1% in those with COVID-19 compared to 16.4% of controls (aRR = 1.34; 95%CI, 0.86-2.09). CONCLUSIONS: COVID-19 is associated with an increased risk for serious perioperative morbidity and mortality. A substantial number of patients with COVID-19 are not identified until after surgery.

Coronavirus Spectrum Infections (COVID-19, MERS, SARS) in Cancer Patients: A Systematic Review of the Literature.

BACKGROUND: Coronavirus 2019 (COVID-19) has spread rapidly around the world to become a global pandemic. There is limited data on the impact of COVID-19 among patients with cancer. METHODS: A systematic review was performed to determine outcomes of adult patients with cancer affected by coronavirus infections, specifically SARS, MERS, and COVID-19. Studies were independently screened by two reviewers and assessed for quality and bias. Outcomes measured included study characteristics, cancer type, phase of care at the time of diagnosis, and clinical presentation. Morbidity and mortality outcomes were analyzed to assess the severity of infection as compared to the general population. RESULTS: A total of 19 studies with 110 patients were included. Of these, 66.4% had COVID-19 infections, 32.7% MERS and only one patient with SARS. The majority of COVID-19 studies were based on studies in China. There was a 56.6% rate of a severe event, including ICU admission or requiring mechanical ventilation, with an overall 44.5% fatality rate. CONCLUSIONS: Patients with cancer with coronavirus infections may be more susceptible to higher morbidity and mortality.