key: cord-0730221-qg7wpb3n authors: Martínez Cordero, Humberto; Peña, Camila; Fantl, Dorotea; Riva, Eloisa; Schutz, Natalia Paola; Abello, Virginia; Ruiz Arguelles, Guillermo; Ramirez Alvarado, Aline; Moreno Gómez, Lina; Von Glasenapp, Alana; Noboa, Andrea; Idrobo, Henry; Ospina Idarraga, Juan; Rojas, Christine; Pineda, Judith; Seehaus, Cristian; Remaggi, Guillermina; Sanchez, Sofia; Espinoza, Ramiro; Alvarado, Martha; De la Peña-Celaya, Jose Antonio; Perez, Juan Manuel; Arana-Luna, Luara L.; Espitia, María Eugenia; Hernandez, Eleazar; David Salas, Lourdes; Herrera, Evelyn title: Sars Cov-2/COVID-19 in Multiple Myeloma Latin-American Patients COVID-Lamm Study on Behalf of Gelamm (Grupo de Estudio Latino- Americano de Mieloma Múltiple) date: 2020-11-05 journal: Blood DOI: 10.1182/blood-2020-142823 sha: 03ef20828a9fc2ff98b489b3f8e8f251222ebd07 doc_id: 730221 cord_uid: qg7wpb3n Background The SARS CoV-2 / COVID 19 pandemic has challenged the world's health systems, especially services that treat cancer. The first studies in China showed that cancer patients had a higher risk of becoming infected and dying. Other risk factors for mortality were age over 65 years, male sex, the presence of comorbidity, hypertension, cardiovascular disease, diabetes, and obesity. Data on the specific behavior of patients with multiple myeloma (MM) in the pandemic are scarce. The mechanisms by which MM patients may have a higher mortality are multiple, derived both from the disease itself due to cellular and humoral immunity deficiency as well as from anti-myeloma treatment. The present study aims to establish the behavior of the disease in the pandemic period in Latin America. Methods This is a retrospective case series of in and outpatients with a diagnosis of MM and COVID-19 reported from centers from Latin America between March and July 31, 2020. The analysis of demographic, clinical, laboratory, complications and therapy variables were done using descriptive statistics. A Kaplan Meier survival analysis was performed, with Log Rank statistic. Finally, a Cox regression was performed to identify independent risk factors of worse outcome. Pre-admission characteristics, MM status, and comorbidities constituted the reference model and were used to adjust the association of relevant MM characteristics with mortality. Program used for analysis was SPSS statistics 25. Results Fifty-two patients with COVID-19 and MM from 7 countries were included. Demographic characteristics, comorbidities, infection baseline clinical conditions, treatment, and outcomes are shown in Table 1. The characteristics in terms of MM status are shown in Table 2. When performing the survival analysis, it is evidenced that the survival of the entire cohort at day 49 was 67% Figure 1. When we focus on patients with comorbidities, survival drops to 53.5% +/- 10.6 (CI 95% 53.4 - 99.4 and p value of 0.041) for the same day Figure 2. When performing the obesity analysis, a drop in survival of up to 39% was observed (95% CI 24.448 - 56.76, with p = 0.00001) Figure 3. Adjusted HR for obesity is 5,078 (95% CI 1,389-18,558, α0.014) and mechanical ventilation with a HR of 3,943 (95% CI - 1,296 - 11,998, α0.016) When comparing patients with controlled MM (> PR) versus uncontrolled, the mortality rate was 84% versus 58% respectively (p = 0.109). Comorbidities (presence of either diabetes, arterial hypertension, cardiovascular disease, or “others”), obesity, need of mechanical ventilation, and PR) versus uncontrolled, the mortality rate was 84% versus 58% respectively (p = 0.109). Comorbidities (presence of either diabetes, arterial hypertension, cardiovascular disease, or "others"), obesity, need of mechanical ventilation, and