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1.
Blood ; 138:2520, 2021.
Article in English | EMBASE | ID: covidwho-1582169

ABSTRACT

Updated analysis confirms sustained poor prognosis of COVID-19 in patients with lymphoma in Latin America: A cohort of 160 patients from GELL. Introduction: Ongoing SARS-COV-2 pandemic has impacted the management of cancer patients worldwide. Several reports have demonstrated inferior outcomes of patients with hematological malignancies, including higher rates of intensive care unit admission, need for mechanical ventilation and death. The impact of COVID-19 is profound in resource-restricted countries, including Latin America. Most cohorts reported have not included patients from Latin America, and there is paucity of data of the outcome of cancer patients with COVID-19 in low- and middle-income countries. Grupo de Estudio De Linfoproliferativos En Latino-America (GELL )is a collaborative network of hematological centers in 13 countries in Latin America. We report updated outcomes of lymphoma patients diagnosed with COVID-19 in Latin America. Methods: We conducted a retrospective study including patients with a diagnosis of lymphoma and COVID-19 infection. Patients with chronic lymphocytic leukemia/small lymphocytic lymphoma were excluded from the analysis We defined active disease as follow: (1) patients with detectable disease either prior to initiating therapy or upon relapse, and/or (2) patients undergoing active cancer treatment. The primary outcome was overall survival at 100 days. Survival curves were estimated using the Kaplan Meier method. Uni and multivariable analysis were carried out with Cox model. Results: A total of 160 patients were available for analysis. Median age was 60 years old. Hypertension was the most common comorbidity (33%). Most patients had aggressive lymphomas (62%), including 43% of patients with diffuse large B-Cell lymphoma (DLBCL). Follicular lymphomas were observed in 13% of patients and Hodgkin lymphoma in 12.5% of patients. With a median follow-up of 37 days, the 100-day OS was 64% (95CI 56-74%, fig. 1). In univariate analysis, age (HR 1.03, p=0.0025), hypertension (HR 2.01, p=0.017), >1 number of prior lines (HR 2.78, p=0.011), patients currently on treatment (HR 1.83, p=0.043), ferritin >2000 ng/mL (HR 4.74 p=0.00047) were associated with inferior OS. In multivariate analysis, age (HR 1.03, p=0.0026) and patients currently on treatment (HR 1.82, p=0.04) had inferior OS. There was a trend towards inferior outcomes in patients receiving monoclonal antibodies in univariate analysis (HR 1.82, p=0.081) but not in multivariable analysis (HR=1.29, p=0.48). Use of steroids was not statistically related to mortality (HR 1.79, p=0.074). Finally, contrary to other cohorts, no improvement in OS was observed in patients diagnosed later on the pandemic (fig. 2). Conclusion: In this large cohort of Latin American patients with lymphoma malignancies, our updated analysis showed a maintained dismal prognosis with COVID-19 infection. With a median follow up of 37 days, the 100-day OS was 64%. Older age and ongoing active cancer treatment were significantly associated with mortality. The use of monoclonal antibodies and systemic corticosteroids were not statistically associated to poor survival. Current efforts are focused on improving immunization in the Latin American population. There is an unmet need for improving survival in patients with hematologic malignancies and COVID-19 infection. [Formula presented] Disclosures: Perini: Janssen: Honoraria, Speakers Bureau;Takeda: Honoraria, Speakers Bureau;Astra Zeneca: Honoraria, Speakers Bureau;MSD: Honoraria, Speakers Bureau. Otero: ASTRA ZENECA: Current Employment. Abello: Dr Reddy's: Research Funding;Amgen: Honoraria;Janssen: Honoraria. Castillo: Abbvie: Consultancy, Research Funding;BeiGene: Consultancy, Research Funding;Pharmacyclics: Consultancy, Research Funding;Janssen: Consultancy;Roche: Consultancy;TG Therapeutics: Research Funding.

3.
Statistics and Its Interface ; 14(1):49-57, 2021.
Article in English | Web of Science | ID: covidwho-1008504

ABSTRACT

The analysis of complex longitudinal data such as COVID-19 deaths is challenging due to several inherent features: (i) similarly-shaped profiles with different decay patterns;(ii) unexplained variation among repeated measurements within each country, possibly interpreted as clustered data since they are obtained from the same country at roughly the same time;and (iii) skewness, outliers or skewed heavy-tailed noises possibly embodied within response variables. This article formulates a robust nonlinear mixed-effects model based on the class of scale mixtures of skew-normal distributions to model COVID-19 deaths, which allows analysts to model such data in the presence of the above described features simultaneously. An efficient EM-type algorithm is proposed to carry out maximum likelihood estimation of model parameters. The bootstrap method is used to determine inherent characteristics of the individual nonlinear profiles, such as confidence intervals of the predicted deaths and fitted curves. The specific target is to model COVID-19 death curves from some Latin American countries since this region is the new epicenter of the disease. Moreover, since a mixed-effect framework borrows information from the population-average effects, in our analysis we include some countries from Europe and North America that are in a more advanced stage of the COVID-19 death curve.

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