Impact of Sars-CoV2 Infection on 491 Hematological Patients: The Ecovidehe Multicenter Study

[Image: see text] INTRODUCTION Coronavirus disease 2019 (COVID-19) caused by SARS-CoV2 virus is thought to be more severe in patients with prior hematological diseases. There is evidence suggesting that hematological patients are particularly vulnerable and have a higher risk of developing severe events, with higher mortality rate than general population. However, the available data are limited, and prognostic factors at admission still remain unclear. With this background, our aims were to analyze the impact of hematological diseases and their therapy on the COVID-19 severity and to identify clinical and biological risk factors to predict the outcome in these patients. METHODS We carried out a multicenter retrospective observational study with data collection from 19 Spanish centers. A total of 491 patients with hematological diseases who developed COVID-19 (HEMATOCOVID patients) from March 8(th) to June 9(th) were included in the study. Clinical and biological data were collected at the time of emergency room assistance or hospital admission. For statistical analysis, chi-square test and Mann-Whitney U-test were used to identify differences between groups. The effects of multiple predictor variables on COVID-19 outcomes were assessed by logistic binary regression. RESULTS The geographic distribution of the studied HEMATOCOVID patients was similar to the national geographic spread of the COVID-19 (Figure 1). Most patients (94,3%) were confirmed cases of COVID-19 with a positive result on SARS-CoV2 RT-PCR on a nasopharyngeal swab or serologic testing, and 15% were nosocomial infections. The mean age was 71 years with 57% males, and 70% had at least one associated comorbidity. The most frequent hematological diseases among COVID-19 patients were Lymphoid Malignancies (53,8%), and 51,7% of patients were on active treatment. Most common symptoms were fever (59%), cough (54%) and dyspnea (46%), with associated pneumonia in 70% of cases. Hospital admission was required in 89% of patients and 6,3% were admitted to intensive care units. Mortality rate was about 36%. Non-survival patients were older and had a higher Charlson comorbidity index and ECOG performance status. Furthermore, patients with acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS), and those with an active or progressive hematological disease at the diagnosis of COVID-19 had higher mortality. Patients who had undergone hematopoietic stem cell transplantation (autologous, allogeneic, and both) had better outcomes. Other factors such as low lymphocyte and platelets counts, or high lactate dehydrogenase (LDH), C-reactive protein (CRP) and procalcitonin values were also associated with poorer outcomes (Table 1). In addition, COVID-19 therapy had no impact on survival, except for corticosteroids, that correlated with a negative impact (p < 0,001) probably because they were not administrated to patients with less severe COVID-19. Multivariate regression analysis showed the following risk factors for death: age >70 years, ECOG ≥2, absolute lymphocyte count ≤0.6·10(9)/L, platelet count ≤40·10(9)/L, high LDH (higher than upper normal limit) and CRP >11 mg/dL (Table 2). CONCLUSIONS SARS-CoV2 infection causes more severe disease and higher mortality rates in hematological patients, especially those with AML/MDS or active/progression status disease. In addition, advanced age, co-morbidities, poor performance status, low lymphocyte and platelet counts and high LDH and CRP at admission are associated with poorer survival. This worse disease evolution could be explained by the immunosuppression state induced by underlying disease and treatments received. These particular features should be taken into account for a population that is highly exposed to SARS-CoV2 contagion due to high number of hospital visits for treatment. [Figure: see text] DISCLOSURES: Hernandez-Rivas:Janssen: Membership on an entity’s Board of Directors or advisory committees; Abbvie: Membership on an entity’s Board of Directors or advisory committees; Roche: Membership on an entity’s Board of Directors or advisory committees; AstraZeneca: Membership on an entity’s Board of Directors or advisory committees; Gilead: Membership on an entity’s Board of Directors or advisory committees; Celgene/BMS: Membership on an entity’s Board of Directors or advisory committees; Rovi: Membership on an entity’s Board of Directors or advisory committees. Ocio:MDS: Honoraria; Asofarma: Honoraria; Takeda: Honoraria; GSK: Consultancy; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Secura-Bio: Consultancy; Oncopeptides: Consultancy. López Jiménez:Gilead: Research Funding, Speakers Bureau; Janssen: Research Funding, Speakers Bureau; Roche: Research Funding, Speakers Bureau; MSD: Speakers Bureau; Takeda: Speakers Bureau; Abbvie: Research Funding, Speakers Bureau. Córdoba:Takeda Farmacéutica España S.A.: Speakers Bureau; Janssen: Honoraria, Other: travel and accommodation; Abbvie: Honoraria, Other: travel and accommodation; Roche: Honoraria, Other: travel and accommodation; Gilead: Honoraria, Other: travel and accommodation. Moraleda:Takeda: Consultancy, Other: Travel Expenses; Sandoz: Consultancy, Other: Travel Expenses; Novartis: Consultancy, Other: Travel Expenses; Gilead: Consultancy, Other: Travel Expenses; Jazz Pharmaceuticals: Consultancy, Research Funding. Garcia-Sanz:Takeda: Consultancy, Research Funding; Pharmacyclics: Honoraria; Novartis: Honoraria; Janssen: Honoraria, Research Funding; Incyte: Research Funding; Gilead: Honoraria, Research Funding; BMS: Honoraria; Amgen: Membership on an entity’s Board of Directors or advisory committees.