Characteristics of patients with hematologic malignancies without seroconversion post-COVID19 third vaccine dosing (3V): Real-world data from large midwestern healthcare system

Background: Patients (Pts) with hematologic malignancies (HM) are at greater risk of severe morbidity and mortality caused by COVID19 and show a lower response to the two-dose COVID19 mRNA vaccine series. The primary vaccine series now includes a third dose of the COVID19 vaccine (3V) for immunocompromised Pts. The objective of this study was to explore the characteristics of HM patients who had no change in SARS-CoV-2 spike protein titer levels post 3V (-/-) to gain a better understanding of the drivers of serostatus. Methods: This retrospective cohort study analyzed Pt data on SARS-CoV-2 spike IgG antibody titers pre- and post- 3V across the healthcare system. This study included 268 fully vaccinated HM Pts diagnosed with HM between October 31, 2019 and January 31, 2022 and had a negative serostatus prior to 3V. Post 3V titers were obtained 21 days after 3V. Demographics, association between characteristics and seroconversion status, and odds ratios were all assessed (table). Results: Pts with Non-Hodgkin lymphoma (NHL) had 6 times the odds of not seroconverting compared to multiple myeloma (MM) (CI 1.88 - 19.12, P = .0010). NHL also have about 14 times the odds of not seroconverting compared to Pts diagnosed with other HM conditions, which included: neoplasms of uncertain behavior and disorders of white blood cells (CI 1.72 - 112.44, P = .0021). 90% of seronegative Pts showed no spike IgG antibody reaction to 3V as indicated by pre- and post- 3V index values. Demographics, previous COVID19 infection, and vaccine type were not significantly associated with seroconversion. Conclusions: HM patients who are not seroconverting after 3V, suggest a prioritized population for continued increased behavioral precautions, additional vaccination efforts, including a fourth dose of an mRNA COVID19 vaccine, as well as passive immunity boosting through monoclonal and polyclonal antibodies.

Identification of Early Features to Differentiate Hospitalized Children Admitted for Suspected MIS-C from Alternative Diagnoses

Background. Multi-system inflammatory syndrome in children (MIS-C) is a rare consequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MIS-C shares features with common infectious and inflammatory syndromes and differentiation early in the course is difficult. Identification of early features specific to MIS-C may lead to faster diagnosis and treatment. We aimed to determine clinical, laboratory, and cardiac features distinguishing MIS-C patients within the first 24 hours of admission to the hospital from those who present with similar features but ultimately diagnosed with an alternative etiology. Methods. We performed retrospective chart reviews of children (0-20 years) who were admitted to Vanderbilt Children's Hospital and evaluated under our institutional MIS-C algorithm between June 10, 2020-April 8, 2021. Subjects were identified by review of infectious disease (ID) consults during the study period as all children with possible MIS-C require an ID consult per our institutional algorithm. Clinical, lab, and cardiac characteristics were compared between children with and without MIS-C. The diagnosis of MIS-C was determined by the treating team and available consultants. P-values were calculated using two-sample t-tests allowing unequal variances for continuous and Pearson's chi-squared test for categorical variables, alpha set at < 0.05. Results. There were 128 children admitted with concern for MIS-C. Of these, 45 (35.2%) were diagnosed with MIS-C and 83 (64.8%) were not. Patients with MIS-C had significantly higher rates of SARS-CoV-2 exposure, hypotension, conjunctival injection, abdominal pain, and abnormal cardiac exam (Table 1). Laboratory evaluation showed that patients with MIS-C had lower platelet count, lymphocyte count and sodium level, with higher c-reactive protein, fibrinogen, B-type natriuretic peptide, and neutrophil percentage (Table 2). Patients with MIS-C also had lower ejection fraction and were more likely to have abnormal electrocardiogram. Conclusion. We identified early features that differed between patients with MIS-C from those without. Development of a diagnostic prediction model based on these early distinguishing features is currently in progress.

LBA71 Systemic cancer treatment-related outcomes in patients with SARS-CoV-2 infection: A CCC19 registry analysis

Background: SARS-CoV-2 is associated with diverse clinical presentations ranging from asymptomatic infection to lethal complications. Small studies have suggested inferior outcomes in patients (pts) on active cancer treatment. This finding was not independently validated in our prior report on 928 pts, which included treatments administered within 4 weeks of COVID-19 diagnosis. Here, we examine outcomes related to systemic cancer treatment within one year of lab-confirmed SARS-CoV-2 infection in an expanded cohort. Method(s): The COVID-19 and Cancer Consortium (CCC19) registry (NCT04354701) was queried for pts ever receiving systemic treatment. Treatment type, cancer type, stage, and COVID-19 outcomes were examined. Pts were stratified by time from last treatment administration: <2 wk, 2-4 wk, 1-3 mo, or 3-12 mo. Standardized incidence ratios (SIR) of mortality by treatment type and timing were calculated. Result(s): As of 31 July 2020, we analyzed 3920 pts;42% received systemic anti-cancer treatment within 12 mo (Table). 159 distinct medications were administered. The highest rate of COVID-19-associated complications were observed in pts treated within 1-3 months prior to COVID-19;all-cause mortality in this group was 26%. 30-day mortality by most recent treatment type was 20% for chemotherapy, 18% for immunotherapy, 17% for chemoradiotherapy, 29% for chemoimmunotherapy, 20% for targeted therapy, and 11% for endocrine therapy. SIR of mortality was highest for chemoimmunotherapy or chemotherapy <2 wks, and lowest for endocrine treatments. A high SIR was also found for targeted agents within 3-12 mo. Pts untreated in the year prior to COVID-19 diagnosis had a mortality of 14%. [Formula presented] Conclusion(s): 30-day mortality was highest amongst cancer pts treated 1-3 months prior to COVID-19 diagnosis and those treated with chemoimmunotherapy. Except for endocrine therapy, mortality for subgroups was numerically higher than in pts untreated within a year prior to COVID-19 diagnosis. Clinical trial identification: NCT04354701. Legal entity responsible for the study: The COVID-19 and Cancer Consortium (CCC19). Funding(s): National Cancer Institute (P30 CA068485). Disclosure: T.M. Wise-Draper: Research grant/Funding (self), Travel/Accommodation/Expenses: AstraZeneca;Research grant/Funding (self): BMS;Research grant/Funding (self): Tesaro/GSK;Advisory/Consultancy: Shattuck Labs;Leadership role, Travel/Accommodation/Expenses, HNC POA Lead: Caris Life Sciences;Research grant/Funding (self), Travel/Accommodation/Expenses: Merck;Travel/Accommodation/Expenses: Eli Lilly;Travel/Accommodation/Expenses: Bexion. A. Elkrief: Research grant/Funding (self): AstraZeneca. B.I. Rini: Advisory/Consultancy, Research grant/Funding (self), Travel/Accommodation/Expenses: Merck;Advisory/Consultancy, Research grant/Funding (self): Roche;Advisory/Consultancy, Research grant/Funding (self), Travel/Accommodation/Expenses: Pfizer;Advisory/Consultancy, Research grant/Funding (self): AVEO;Advisory/Consultancy, Research grant/Funding (self), Travel/Accommodation/Expenses: BMS;Advisory/Consultancy: arravive;Advisory/Consultancy: 3D medicines;Advisory/Consultancy: Synthorx;Advisory/Consultancy: Surface Oncology;Shareholder/Stockholder/Stock options: PTC Therapeutics;Research grant/Funding (self): AstraZeneca. D.B. Johnson: Advisory/Consultancy: Array Biopharma;Advisory/Consultancy, Research grant/Funding (self): BMS;Advisory/Consultancy: Janssen;Advisory/Consultancy: Merck;Advisory/Consultancy: Novartis;Research grant/Funding (self): Incyte;Leadership role: ASCO melanoma scientific committee chair;Leadership role: NCCN Melanoma committee. G. Lopes: Honoraria (self), Travel/Accommodation/Expenses: Boehringer Ingelheim;Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Pfizer;Advisory/Consultancy, Research grant/Funding (self), Research grant/Funding (institution): AstraZeneca;Research grant/Funding (institution): Merck;Research grant/Funding (institution): EMD Serono;Research gr

Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium.

BACKGROUND: Patients with cancer may be at high risk of adverse outcomes from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed a cohort of patients with cancer and coronavirus 2019 (COVID-19) reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anticancer therapies. PATIENTS AND METHODS: Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between 17 March and 18 November 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anticancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients). RESULTS: A total of 4966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic black race, Hispanic ethnicity, worse Eastern Cooperative Oncology Group performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count; high absolute neutrophil count; low platelet count; abnormal creatinine; troponin; lactate dehydrogenase; and C-reactive protein were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anticancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality. CONCLUSIONS: Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anticancer therapies. CLINICAL TRIAL IDENTIFIER: NCT04354701.

Using real-world data (RWD) from anintegrated platform for rapid analysis of patients withcancer with and without COVID-19 across distinct healthsystems

Introduction: Reports suggest worsened outcomes in patients with cancer (pts) and COVID-19 (Cov), varying bygeography and local peak dynamics. We describe characteristics and clinical outcomes of pts with and without Cov. Methods: RWD at 2 Midwestern health systems from the Syapse Learning Health Network were used to identifyadults with active cancer (AC) or past history of cancer (PHC). AC pts were identified by encounters with ICD-10code for malignant neoplasm or receipt of an anticancer agent within 12 months prior to February 15, 2020;PHC pts were identified by encounters with an active cancer code from May 15, 2015 to February 15, 2019 and no receipt ofanticancer therapy within the prior 12 months. Cov was defined by diagnostic codes and laboratory results fromFebruary 15 to May 13, 2020. Comorbidities were assessed prior to February 15, 2020;hospitalizations (hosp), invasive mechanical ventilation (IMV), and all-cause mortality (M) were assessed from February 15 to May 27, 2020. Results: We identified 800 pts with Cov (0.5%) out of a total of 154,585 pts with AC or PHC. Compared to AC pts without Cov (AC WO, 39,402), AC pts with Cov (AC Cov, 388) were more likely to be non-Hispanic Black (NHB,39% vs. 9%), have renal failure (RF, 24% vs. 12%), cardiac arrhythmias (33% vs. 19%), congestive heart failure(CHF, 16% vs. 8%), obesity (19% vs. 14%), pulmonary circulation disorder (PCD, 9% vs. 4%), and a zip code withmedian annual household income (ZMI) <$30k (18% vs. 5%). Comorbidity and income were similarly distributed forPHC pts with Cov (PHC Cov, 412). Compared to PHC pts without Cov (PHC WO, 114,383), coagulopathy (coag)was more common in PHC Cov pts (10% vs. 5%). Hosp for AC Cov pts was higher than for AC WO pts (81% vs.15%). Hosp for PHC Cov pts was also higher than for PHC WO pts (68% vs. 6%). Hosp was highest for NHB pts inboth AC Cov and PHC Cov groups (88% and 72%) and for AC Cov pts in low ZMI (94% in <$30K). Pts <50 yearsold had hosp rates of 79% (AC Cov) and 49% (PHC Cov). IMV rate for AC Cov pts was higher than for PHC Cov pts(21% vs. 14%). Rates of IMV for AC Cov pts were highest in low ZMI (27%) and in pts with coag (36%). M by group was: AC Cov 16%;AC WO 1%;PHC Cov 11%;PHC WO 1%. Among AC Cov pts, M was higher for men (19% vs.13%) and pts with PCD (31%), RF (25%), or diabetes (DM, 24%);among PHC Cov pts, M was also higher for men(14% vs. 8%) and pts with coag (30%), valvular disease (27%), or PCD (24%). Increasing age, DM, RF, and PCD were associated with increased risk of M for AC Cov pts in age, race/ethnicity, and comorbidity-adjusted logisticregression;increasing age and coag were associated with M in PHC Cov pts. Conclusion: In this rapid characterization from RWD, pts with Cov have higher rates of pre-existingcardiopulmonary/vascular and renal conditions and increased risk of hospitalization, IMV, and mortality than pts without Cov. Higher Cov risk and worse outcomes in NHB and lower-income pts suggest health care disparities.Whether these outcomes are due to comorbidities or acute sequelae merits further study, as does investigation ofalternative definitions for real-world populations and outcomes.

Clinical impact of COVID-19 on patients with cancer: Data from the COVID-19 and Cancer Consortium (CCC19)

Background: There are limited data on COVID-19 in patients with cancer. We characterize the outcomes of patients with cancer and COVID-19 and identify potential prognostic factors. Methods: The COVID- 19 and Cancer Consortium (CCC19) cohort study includes patients with active or prior hematologic or invasive solid malignancies reported across academic and community sites. Results: We included 1,018 cases accrued March-April 2020. Median age was 66 years (range, 18-90). Breast (20%) and prostate (16%) cancers were most prevalent;43% of patients were on active anti-cancer treatment. At time of data analysis, 106 patients (10.4%) have died and 26% met the composite outcome of death, severe illness requiring hospitalization, and/or mechanical ventilation. In multivariable logistic regression analysis, independent factors associated with increased 30- day mortality were age, male sex, former smoking, ECOG performance status (2 versus 0/1: partially adjusted odds ratio (pAOR) 2.74, 95% CI 1.31-5.7;3/4 versus 0/1: pAOR 5.34, 95% CI 2.44-11.69), active malignancy (stable/responding, pAOR 1.93, 95% CI 1.06-3.5;progressing, pAOR 3.79, 95% CI 1.78-8.08), and receipt of azithromycin and hydroxychloroquine. Tumor type, race/ethnicity, obesity, number of comorbidities, recent surgery, and type of active cancer therapy were not significant factors for mortality. Conclusions: All-cause 30-day mortality and severe illness in this cohort were significantly higher than previously reported for the general population and were associated with general risk factors as well as those unique to patients with cancer. Cancer type and treatment were not independently associated with increased 30-day mortality. Longer follow-up is needed to better understand the impact of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments.