ImportanceCytokine storm due to COVID-19 can cause high morbidity and mortality and may be more common in patients with cancer treated with immunotherapy (IO) due to immune system activation.ObjectiveTo determine the association of baseline immunosuppression and/or IO-based therapies with COVID-19 severity and cytokine storm in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included 12 046 patients reported to the COVID-19 and Cancer Consortium (CCC19) registry from March 2020 to May 2022. The CCC19 registry is a centralized international multi-institutional registry of patients with COVID-19 with a current or past diagnosis of cancer. Records analyzed included patients with active or previous cancer who had a laboratory-confirmed infection with SARS-CoV-2 by polymerase chain reaction and/or serologic findings.ExposuresImmunosuppression due to therapy; systemic anticancer therapy (IO or non-IO).Main Outcomes and MeasuresThe primary outcome was a 5-level ordinal scale of COVID-19 severity: no complications; hospitalized without requiring oxygen; hospitalized and required oxygen; intensive care unit admission and/or mechanical ventilation; death. The secondary outcome was the occurrence of cytokine storm.ResultsThe median age of the entire cohort was 65 years (interquartile range [IQR], 54-74) years and 6359 patients were female (52.8%) and 6598 (54.8%) were non-Hispanic White. A total of 599 (5.0%) patients received IO, whereas 4327 (35.9%) received non-IO systemic anticancer therapies, and 7120 (59.1%) did not receive any antineoplastic regimen within 3 months prior to COVID-19 diagnosis. Although no difference in COVID-19 severity and cytokine storm was found in the IO group compared with the untreated group in the total cohort (adjusted odds ratio [aOR], 0.80; 95% CI, 0.56-1.13, and aOR, 0.89; 95% CI, 0.41-1.93, respectively), patients with baseline immunosuppression treated with IO (vs untreated) had worse COVID-19 severity and cytokine storm (aOR, 3.33; 95% CI, 1.38-8.01, and aOR, 4.41; 95% CI, 1.71-11.38, respectively). Patients with immunosuppression receiving non-IO therapies (vs untreated) also had worse COVID-19 severity (aOR, 1.79; 95% CI, 1.36-2.35) and cytokine storm (aOR, 2.32; 95% CI, 1.42-3.79).Conclusions and RelevanceThis cohort study found that in patients with cancer and COVID-19, administration of systemic anticancer therapies, especially IO, in the context of baseline immunosuppression was associated with severe clinical outcomes and the development of cytokine storm.Trial RegistrationClinicalTrials.gov Identifier: NCT04354701

Background Literature on severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection in cancer patients is scarce in Latin America. This population seems to have a higher risk for adverse outcomes. This study aims to correlate clinical characteristics with outcomes in patients with cancer. Methods We included all patients with cancer and confirmed SARS‐CoV‐2 infection from April 19 to December 31, 2020, at the Instituto Nacional de Cancerologia, Mexico. Clinical information was obtained from medical and epidemiological records. For the association between variables and hospitalization, invasive mechanical ventilation (IMV), and mortality, univariate and multivariate logistic regression were performed; odds ratios and 95% confidence intervals were calculated. Results Four hundred thirty‐three patients were included; 268 (62%) were female, the median age was 55 years. One hundred thirty‐five (31%), 131 (30%), and 93 (21%) patients had obesity, hypertension, and diabetes mellitus (DM), respectively. Three hundred forty‐one (79%) had solid cancer. One hundred seventy (39%) had advanced cancer. Two hundred (46%) patients were hospitalized. Age ( p < 0.01), male gender ( p = 0.03), hematological malignancies (HM) ( p = 0.04) and advanced cancer ( p = 0.03) increased the risk for hospital admission. Forty‐five (10%) patients required IMV. Age ( p = 0.02); DM ( p = 0.04); high C‐reactive protein ( p < 0.01), and lactate dehydrogenase ( p = 0.03) were associated with IMV. Mortality within 30 days after diagnosis was 18% (76 cases). Associated characteristics were age ( p = 0.04) and low albumin ( p < 0.01). Conclusions In this study, patients with cancer showed higher mortality, need for hospitalization, and IMV compared with other non‐cancer cohorts. We did not find an increased risk in mortality for HM. Although our cohort was younger than others previously reported, age was a strong predictor of adverse outcomes. Variables associated with IMV and death were similar to those previously described in cancer patients with COVID‐19.

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Background: Post-acute COVID-19 syndrome (PACS) is a multi-system disease comprising persistent symptomatology after the acute phase of infection. Long-term PACS effects significantly impact patient outcomes, but their incidence remains uncharacterized due to high heterogeneity between studies. Therefore, we aimed to summarize published data on PACS, characterizing the clinical presentation, prevalence, and modifiers of prevalence estimates. Method: In this systematic review and meta-analysis, we research MEDLINE for original studies published from January 1st, 2020, to January 31st, 2021, that reported proportions of PACS manifestations. Studies were eligible for inclusion if they included patients aged ≥18 years with confirmed COVID-19 by RT-PCR or antigen testing and a minimum follow-up of 21 days. The prevalence of individual manifestations across studies was pooled using random-effects meta-analysis. For evaluating determinants of heterogeneity, meta-regression analysis was performed. This study was registered in PROSPERO (CRD42019125025). Results: After screening 1,235 studies, we included 29 reports for analysis. Twenty-seven meta-analyses were performed, and 61 long-term manifestations were described. The pooled prevalence of PACS was 56% (95%CI 45-66%), with the most common manifestations being diminished health status, fatigue, asthenia, dyspnea, myalgias, hyposmia and dysgeusia. Most of the included studies presented high heterogeneity. After conducting the meta-regression analysis, we identified that age, gender, number of comorbidities, and reported symptoms significantly modify the prevalence estimation of PACS long-term manifestations. Conclusion: PACS is inconsistently reported between studies, and population characteristics influence the prevalence estimates due to high heterogeneity. A systematized approach for the study of PACS is needed to characterize its impact adequately.

Background Cancer patients (CPs) with COVID-19 have an increased risk of adverse outcomes. In addition, CPs seem to have a lower immune response to SARS-CoV-2 vaccination. This study aimed to evaluate SARS-CoV-2 spike antibodies (anti-S Abs) following COVID-19 vaccination in CPs and healthcare workers (HCWs). Methods We conducted a point-seroprevalence study in CPs and HCWs who received a two-dose scheme with either BNT162b2, AZD1222, or Sputnik-V vaccine. We measured anti-S Abs by quantitative immunoassay to assess humoral immune response. Besides, we quantified anti-nucleocapsid antibodies in a subgroup of individuals to determine prior infection. We compared anti-S Abs titers in both groups and stratified by vaccine type, prior infection, and clinical characteristics. We conducted a multivariate logistic regression to determine variables associated with a poor humoral response. Results Six hundred forty-one individuals were included: 174 (27%) CPs and 467 (73%) HCWs. The median anti-S Abs titter was higher among HCWs compared to CPs (2568 U/mL vs. 1807 U/mL, p=0.002). Both CPs and HCWs with prior infection had higher anti-S Abs titter (p&lt; 0.001). Regardless of the time since vaccination, a higher proportion of subjects with titers &lt; 250 U/mL was observed in CPs (p&lt; 0.001) (Fig 2). In the multivariate analysis, older age (p=0.036), AZD1222 (p=0.003), and Sputnik-V (p=0.020) were associated with lower humoral response among the entire cohort. SARS-CoV-2 spike antibody titers among cancer patients and healthcare workers. Global differences in anti-S Abs titers between CPs and HCWs groups (a) and antibody titers in CPs and HCWs groups stratified by type of received vaccine (b). Abbreviations: CP: Cancer patients, HCW: Healthcare workers. SARS-CoV-2 spike antibody titers according to time since vaccination among cancer patients and healthcare workers. Abbreviations: CP: Cancer patients, HCW: Healthcare workers. Conclusion In this study, both CPs and HCWs showed an adequate response to vaccination; however, CPs had lower anti-S Abs titers and a faster decline over time. Based on our results, new strategies should be assessed to sustain the humoral response to vaccination and thus decrease the COVID-19 burden among the oncologic population. Disclosures All Authors: No reported disclosures.