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1.
Applied Economics ; : 1-17, 2023.
Article in English | Web of Science | ID: covidwho-20230833

ABSTRACT

Leveraging the unexpected variation in the frequency of eating restaurant prepared food due to the COVID-19 pandemic, we seek to identify and estimate the causal relationship between the frequency of eating restaurant prepared food and people's BMI. We use first-differencing and instrumental variable approaches to correct for potential endogeneity bias due to both the time-invariant and time-varying unobserved factors. Our results show eating more restaurant prepared food has a positive and statistically significant effect on BMI, and in addition to other channels that have been identified in the literature, mood-boosting is another channel through which eating restaurant prepared food leads to weight gain. Heterogeneous effect analysis further shows that eating restaurant prepared food is more likely to have an impact on those people who lead a more stressful lifestyle before the pandemic.

3.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2009620

ABSTRACT

Background: Most patients with cancer and COVID-19 will survive the acute illness. The longer-term impacts of COVID-19 on patients with cancer remain incompletely described. Methods: Using COVID-19 and Cancer Consortium registry data thru 12/31/2021, we examined outcomes of long-term COVID-19 survivors with post-acute sequelae of SARS-CoV-2 infection (PASC aka “long COVID”). PASC was defined as having recovered w/ complications or having died w/ ongoing infection 90+ days from original diagnosis;absence of PASC was defined as having fully recovered by 90 days, with 90+ days of follow-up. Patients with SARS-CoV-2 re-infection and records with low quality data were excluded. Results: 858 of 3710 of included patients (23%) met PASC criteria. Median follow-up (IQR) for PASC and recovered patients was 180 (98-217) and 180 (90-180) days, respectively. The PASC group had a higher rate of baseline comorbidities and poor performance status (Table). Cancer types, status, and recent anticancer treatment were similar between the groups. The PASC group experienced a higher illness burden, with more hospitalized (83% vs 48%);requiring ICU (29% vs 6%);requiring mechanical ventilation (17% vs 2%);and experiencing co-infections (19% vs 8%). There were more deaths in the PASC vs recovered group (8% vs 3%), with median (IQR) days to death of 158 (120-272) and 180 (130-228), respectively. Of these, 9% were attributed to COVID-19;15% to both COVID-19 and cancer;15% to cancer;and 23% to other causes. Conversely, no deaths in the recovered group were attributed to COVID-19;57% were attributed to cancer;and 24% to other causes (proximal cause of death unknown/missing in 38% and 19%, respectively). Cancer treatment modification was more common in the recovered group (23% vs 18%). Conclusions: Patients with underlying comorbidities, worse ECOG PS, and more severe acute SARS-CoV-2 infection had higher rates of PASC. These patients suffered more severe complications and incurred worse outcomes. There was an appreciable rate of death in both PASC and non-PASC, with cancer the dominant but not only cause in fully recovered patients. Further study is needed to understand what factors drive PASC, and whether longer-term cancer-specific outcomes will be affected.

4.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2009530

ABSTRACT

Background: Patients with cancer have worse outcomes from COVID-19 infection. However, the specific impact of COVID-19 on patients with (HNC) is largely unknown. The COVID-19 and Cancer Consortium (CCC19) maintains an international registry (NCT04354701) aimed to investigate the clinical course and complications of COVID-19 in patients with cancer. Here, we report severity of COVID-19 and its complications among HNC patients. Methods: The CCC19 registry was queried for patients with HNC and laboratory confirmed SARS-CoV-2 infection. The co-primary outcomes were severity of COVID-19 illness on an ordinal scale (0: no complications;1: hospitalized, no oxygen (O2);2: hospitalized, required O2;3: ICU admission;4: mechanical ventilation (MV);5: death), and severity of complications (mild, moderate, serious). The outcomes were further stratified by demographics, recent treatment (systemic vs local;surgery, radiation (RT) vs systemic), treatment intent (palliative vs curative), and cancer status (remission, responding, stable, progressing). Results: From March 2020 to December 2021, 356 HNC patients were identified. Median age was 65 (interquartile range 58-74), 29% were female, 56% were white, 67% were former or current smokers, 20% had a BMI >30, 15% had an ECOG performance status >2, and 57% had >2 comorbidities. 154 (43%) had no complications, 61 (17%) were hospitalized without O2, 135 (38%) were hospitalized with O2, 50 (14%) required ICU, 32 (9%) required MV, and 74 (21%) died. 88 (25%) had mild, 59 (17%) had moderate, and 132 (37%) had serious complications. 33% of patients who received systemic therapy and 30% who received RT within 3 mo prior to COVID-19 diagnosis died. Mortality was higher in patients receiving palliative when compared to curative intent treatment (44% vs 16%). In addition, 50% of patients with actively progressing cancer, and 45% who had serious complications died. Importantly, 37 (n=12 palliative systemic therapy and n=25 local therapy) patients had a treatment delay due to COVID-19 diagnosis. Conclusions: Our study is the largest cohort to date describing COVID-19 outcomes in HNC patients and suggest a high rate of mortality even in those receiving local and curative intent treatment. Variables stratified by COVID-19 severity. Note: Ordinal levels 3 and 4 not shown due to small case numbers.

6.
Journal of Clinical Oncology ; 39(15 SUPPL), 2021.
Article in English | EMBASE | ID: covidwho-1339364

ABSTRACT

Background: COVID-19 has been associated with immune modulation that may predispose infected patients to bacterial, viral, or fungal coinfections. Due to critical illness, > 70% of patients with severe COVID-19 receive empiric antibacterial or antifungal therapy, along with standard anti-COVID-19 treatments. However, the frequency of proven or probable secondary infections is < 10%. To our knowledge, there are no studies evaluating co-infections in patients with cancer and COVID-19, a vulnerable group with multiple risk factors for co-infections. We aim to describe the prevalence of bacterial, viral, and fungal co-infections, identify risk factors for coinfection, and investigate the potential impact of co-infections on mortality, in patients with a history of cancer and COVID-19. Methods: The CCC19 registry (NCT04354701) includes patients with active or prior hematologic or invasive solid malignancies reported across academic and community sites. We captured bacterial, fungal, or viral coinfections diagnosed within ±2 weeks from diagnosis of COVID-19, identified factors associated with an increased risk of having a coinfection, and evaluated the association of coinfections with 30-day all-cause mortality. Results: We examined 6732 patients with a history of cancer and a laboratory-confirmed diagnosis of SARS-CoV-2 reported to CCC19 by 82 sites between March 17, 2020 and February 3, 2021, with complete data on coinfection status. Median age was 65 (interquartile range: 55-75) years with 48% male, 52% non-Hispanic white, 19% non-Hispanic black, and 16% Hispanic. 5448 (81%) had solid tumors and 1466 (22%) had hematologic malignancies. Bacterial infections were reported in 823 patients (12%), including 296 Gram+ and 245 Gram- bacterial events. Documented viral (176 patients, 3%) and fungal (59 patients, 0.9%) co-infections were rare. The risk for co-infections increased with age, and they were more frequent among men, older patients, and those with diabetes, pulmonary or renal comorbid conditions, active progressive cancer, or hematologic malignancies (unadjusted P< 0.01). The frequency of reported co-infections decreased over the study period (divided into quartiles, Mantel-Haenszel P< 0.01). All-cause mortality rates were higher among those with bacterial (24% vs. 10%), viral (22% vs. 12%), and fungal (37% vs. 12%) coinfections compared to those without (unadjusted P< 0.01). Conclusions: The frequency of bacterial infections in patients with cancer and COVID-19 is relatively low. Viral and fungal co-infections are uncommon. Coinfections are associated with higher mortality rates. Several patient and tumor factors can be used for risk stratification and guide early empiric antimicrobial agent selection, which may improve clinical outcomes. These data could inform antimicrobial stewardship interventions in this tenuous patient population.

7.
Journal of Clinical Oncology ; 39(15 SUPPL), 2021.
Article in English | EMBASE | ID: covidwho-1339268

ABSTRACT

Background: Patients (pts) with cancer have a high risk of venous thromboembolic (VTE) complications, further enhanced by anti-cancer treatments, specifically hormonal therapies, targeted therapies (VEGF inhibitors, other TKIs) and immune checkpoint inhibitors (ICIs). We hypothesized that high-risk therapies would predispose pts with cancer and COVID-19 to higher risk of VTE complications. Methods: CCC19 is the largest international registry (NCT04354701) recording outcomes of pts with cancer and COVID-19. The registry was queried for hospitalized pts who developed VTE and received systemic cancer treatment in the year prior to COVID-19. Incidence of VTE was analyzed as the primary endpoint;30-day any cause mortality & need for ICU admission at baseline were secondary endpoints in pts with and without VTE respectively. Pts were stratified by treatment type and time from last treatment dose: <2 wk, 2-4 wk, 1-3 months (mos), 3-12 mos. Results: As of February 9th 2021, 4217 hospitalized pts with complications data were present in the registry. 1867 (44%) pts had received systemic anti-cancer therapy within the year prior to COVID-19 and were analyzed. There were a total of 186 (10%) VTE events. Of these, VTE incidence was 141 (10.5%) in pts with solid tumors and 57 (9%) in pts with hematologic malignancies. Overall 30-day mortality was 20% and 22% in pts with and without VTE respectively, while direct admission to ICU at presentation was seen in 17% and 10% of pts with and without VTE, respectively. Treatment timing and drug exposures are below (Table). Receipt of systemic anti-cancer treatment within 3 mos vs 3-12 mos was associated with increased rate of VTE, OR 2.44, 95% CI 1.18-5.84, p=0.011 (univariate Fisher test). Conclusions: We describe the incidence of VTE events in pts with cancer and COVID-19 with recent systemic cancer therapy. ICI and VEGFi were associated with numerically higher rates of VTE;other examined drugs and drug classes were not. Timing of therapy appears to modify risk of VTE. Although retrospective, with possible selection and confounding biases, our analysis suggests that factors other than anticancer drug exposures may drive VTE events in this population.

8.
Journal of Clinical Oncology ; 39(15 SUPPL), 2021.
Article in English | EMBASE | ID: covidwho-1339224

ABSTRACT

Background: In-hospital mortality among patients with cancer (pts) and COVID-19 infection is high. The frequency of, and factors associated with, donot- resuscitate (DNR) or do-not-intubate (DNI) orders at hospital admission (HA), and their correlation with care, has not been well studied. In November 2020, we began collecting this information for pts who were hospitalized at initial presentation in the CCC19 registry (NCT04354701). Methods: We investigated: 1. the frequency of, and factors associated with, DNR/DNI orders at HA;2. change in code status during HA;and 3. the correlation between DNR/DNI orders and palliative care consultation (PC), mortality or length of stay (LOS). We included hospitalized, adult pts with cancer and COVID-19 from 57 participating sites. Reported characteristics include age, ECOG performance status (PS), and cancer status. Comparative statistics include 2-sided Wilcoxon rank sum and Fisher's exact tests. Results: 744 pts had known baseline and/or changed code status (CS);most (79%) maintained their baseline CS (Table). Those with DNR±DNI orders at HA were older (median age 79 vs 69 yrs, p<0.001) and more likely to have: ECOG PS 2+ vs 0-1 (45% vs 22%, OR 3.95, p<0.001), metastatic disease (45% vs 35%, OR 1.72, p=0.005) and progressing cancer (32% vs 16%, OR 2.69, p<0.001), but equally likely to have received systemic anticancer therapy in the prior 3 months (38% vs 45%, p=0.15). N=192 pts with a change in CS from full to DNR±DNI were younger (median age 73), had better PS (37% ECOG PS 2+), and were less likely to have progressing cancer (23%) than those with DNR±DNI orders at baseline. However, their LOS was significantly longer, median 9 vs 6 days, p<0.001. Compared to those with DNR±DNI orders at HA, pts whose CS changed to DNR±DNI were more likely to die, OR 2.94, 95% CI 1.76-4.97, p<0.001. PC was obtained in 106 (14%) pts and associated with transition to DNR±DNI in 47 (44%), affirmation of admission CS in 58 (55%), and reversal in 1 (1%). Median LOS for pts receiving PC was 11 vs 6 days, p<0.001. Conclusions: In our sample, the majority of patients with cancer and COVID-19 were full code at hospital admission. DNR±DNI status, whether at baseline or assigned during the hospital course, was associated with worse prognosis. Longer length of stay for patients changing code status and/or receiving palliative care consultation was observed likely suggesting earlier palliative care consultation is an important, but likely underutilized component in the care of patients with cancer and COVID-19. (Table Presented).

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