Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331681

ABSTRACT

Patients with hematologic malignancies have poor outcomes from COVID infection and are less likely to mount an antibody response after COVID infection. There is limited data on the efficacy of the COVID vaccines in lymphoma patients, and to suggest the optimal timing of vaccination to elicit immunity in patients receiving immunochemotherapy. This is a retrospective study of adult lymphoma patients who received the COVID vaccine between 12/1/2020 and 11/30/2021. The primary endpoint was a positive anti-COVID spike protein antibody titer following the primary COVID vaccination series. The primary series was defined as 2 doses of the COVID mRNA vaccines or 1 dose of the COVID adenovirus vaccine. Subgroups were compared using Fisher’s exact test, and unadjusted and adjusted logistic regression models were used for univariate (UVA) and multivariate (MVA) analyses. A total of 243 patients were included in this study;72 patients (30%) with indolent lymphomas;56 patients (23%) with Burkitt’s, diffuse large B-cell lymphoma (DLBCL), and primary mediastinal B-cell lymphoma (PMBL) combined;55 patients (22%) with chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL);and 44 patients (18%) with Hodgkin and T-cell lymphomas (HL/TCL) combined. One-hundred fifty-eight patients (65%) developed anti-COVID spike protein antibodies after completing the primary COVID vaccination series. Thirty-eight of 46 (83%) patients who received an additional primary shot and had resultant levels produced anti-COVID spike protein antibodies. When compared to other lymphoma types, patients with CLL/SLL had a numerically lower seroconversion rate of 51% following the primary series whereas patients with HL/TCL appeared to have a robust antibody response with a seropositivity rate of 77% (p=0.04). Lymphoma patients are capable of mounting a humoral response to the COVID mRNA vaccines. Further studies are required to confirm our findings, including whether T-cell immunity would be of clinical relevance in this patient population.

2.
Roeker, Lindsey E.; Scarfo, Lydia, Chatzikonstantinou, Thomas, Abrisqueta, Pau, Eyre, Toby A.; Cordoba, Raul, Muntañola Prat, Ana, Villacampa, Guillermo, Leslie, Lori A.; Koropsak, Michael, Quaresmini, Giulia, Allan, John N.; Furman, Richard R.; Bhavsar, Erica B.; Pagel, John M.; Hernandez-Rivas, Jose Angel, Patel, Krish, Motta, Marina, Bailey, Neil, Miras, Fatima, Lamanna, Nicole, Alonso, Rosalia, Osorio-Prendes, Santiago, Vitale, Candida, Kamdar, Manali, Baltasar, Patricia, Österborg, Anders, Hanson, Lotta, Baile, Mónica, Rodríguez-Hernández, Ines, Valenciano, Susana, Popov, Viola Maria, Barez Garcia, Abelardo, Alfayate, Ana, Oliveira, Ana C.; Eichhorst, Barbara, Quaglia, Francesca M.; Reda, Gianluigi, Lopez Jimenez, Javier, Varettoni, Marzia, Marchetti, Monia, Romero, Pilar, Riaza Grau, Rosalía, Munir, Talha, Zabalza, Amaya, Janssens, Ann, Niemann, Carsten U.; Perini, Guilherme Fleury, Delgado, Julio, Yanez San Segundo, Lucrecia, Gómez Roncero, Ma Isabel, Wilson, Matthew, Patten, Piers, Marasca, Roberto, Iyengar, Sunil, Seddon, Amanda, Torres, Ana, Ferrari, Angela, Cuéllar-García, Carolina, Wojenski, Daniel, El-Sharkawi, Dima, Itchaki, Gilad, Parry, Helen, Mateos-Mazón, Juan José, Martinez-Calle, Nicolas, Ma, Shuo, Naya, Daniel, Van Der Spek, Ellen, Seymour, Erlene K.; Gimeno Vázquez, Eva, Rigolin, Gian Matteo, Mauro, Francesca Romana, Walter, Harriet S.; Labrador, Jorge, De Paoli, Lorenzo, Laurenti, Luca, Ruiz, Elena, Levin, Mark-David, Šimkovič, Martin, Špaček, Martin, Andreu, Rafa, Walewska, Renata, Perez-Gonzalez, Sonia, Sundaram, Suchitra, Wiestner, Adrian, Cuesta, Amalia, Broom, Angus, Kater, Arnon P.; Muiña, Begoña, Velasquez, César A.; Ujjani, Chaitra S.; Seri, Cristina, Antic, Darko, Bron, Dominique, Vandenberghe, Elisabeth, Chong, Elise A.; Lista, Enrico, García, Fiz Campoy, Del Poeta, Giovanni, Ahn, Inhye, Pu, Jeffrey J.; Brown, Jennifer R.; Soler Campos, Juan Alfonso, Malerba, Lara, Trentin, Livio, Orsucci, Lorella, Farina, Lucia, Villalon, Lucia, Vidal, Maria Jesus, Sanchez, Maria Jose, Terol, Maria Jose, De Paolis, Maria Rosaria, Gentile, Massimo, Davids, Matthew S.; Shadman, Mazyar, Yassin, Mohamed A.; Foglietta, Myriam, Jaksic, Ozren, Sportoletti, Paolo, Barr, Paul M.; Ramos, Rafael, Santiago, Raquel, Ruchlemer, Rosa, Kersting, Sabina, Huntington, Scott F.; Herold, Tobias, Herishanu, Yair, Thompson, Meghan C.; Lebowitz, Sonia, Ryan, Christine, Jacobs, Ryan W.; Portell, Craig A.; Isaac, Krista, Rambaldi, Alessandro, Nabhan, Chadi, Brander, Danielle M.; Montserrat, Emili, Rossi, Giuseppe, Garcia-Marco, Jose A.; Coscia, Marta, Malakhov, Nikita, Fernandez-Escalada, Noemi, Skånland, Sigrid Strand, Coombs, Callie C.; Ghione, Paola, Schuster, Stephen J.; Foà, Robin, Cuneo, Antonio, Bosch, Francesc, Stamatopoulos, Kostas, Ghia, Paolo, Mato, Anthony R.; Patel, Meera.
Blood ; 136(Supplement 1):45-49, 2020.
Article in English | PMC | ID: covidwho-1338959

ABSTRACT

Introduction: Patients (pts) with CLL may be at particular risk of severe COVID-19 given advanced age and immune dysregulation. Two large series with limited follow-up have reported outcomes for pts with CLL and COVID-19 (Scarfò, et al. Leukemia 2020;Mato, et al. Blood 2020). To provide maximal clarity on outcomes for pts with CLL and COVID-19, we partnered in a worldwide effort to describe the clinical experience and validate predictors of survival, including potential treatment effects.Methods: This international collaboration represents a partnership between investigators at 141 centers. Data are presented in two cohorts. Cohort 1 (Co1) includes pts captured through efforts by European Research Initiative on CLL (ERIC), Italian CAMPUS CLL Program, and Grupo Español de Leucemia Linfática Crónica. The validation cohort, Cohort 2 (Co2), includes pts from US (66%), UK (23%), EU (7%), and other countries (4%). There is no overlap in cases between cohorts.CLL pts were included if COVID-19 was diagnosed by PCR detection of SARS-CoV-2 and they required inpatient hospitalization. Data were collected retrospectively 2/2020 - 5/2020 using standardized case report forms. Baseline characteristics, preexisting comorbidities (including cumulative illness rating scale (CIRS) score ≥6 vs. <6), CLL treatment history, details regarding COVID-19 course, management, and therapy, and vital status were collected.The primary endpoint of this study was to estimate the case fatality rate (CFR), defined as the proportion of pts who died among all pts hospitalized with COVID-19. Chi-squared test was used to compare frequencies;univariable and multivariable analyses utilized Cox regression. Predictors of inferior OS in both Co1 and Co2 were included in multivariable analyses. Kaplan-Meier method was used to estimate overall survival (OS) from time of COVID-19 diagnosis (dx).Results: 411 hospitalized, COVID-19 positive CLL pts were analyzed (Co1 n=281, Co2 n=130). Table 1 describes baseline characteristics. At COVID-19 dx, median age was 72 in Co1 (range 37-94) and 68 in Co2 (range 41-98);31% (Co1) and 45% (Co2) had CIRS ≥6. In Co1, 48% were treatment-naïve and 26% were receiving CLL-directed therapy at COVID-19 dx (66% BTKi ± anti-CD20, 19% Venetoclax ± anti-CD20, 9.6% chemo/chemoimmunotherapy (CIT), 1.4% PI3Ki, 4% other). In Co2, 36% were never treated and 49% were receiving CLL-directed therapy (65% BTKi ± anti-CD20, 19% Venetoclax ± anti-CD20, 9.4% multi-novel agent combinations, 1.6% CIT, 1.6% PI3Ki, 1.6% anti-CD20 monotherapy, 1.6% other). Most pts receiving CLL-directed therapy had it held at COVID-19 diagnosis (93% in Co1 and 81% in Co2).Frequency of most COVID-19 symptoms/laboratory abnormalities were similar in the two cohorts including fever (88% in both), lymphocytosis (ALC ≥30 x 109/L;27% vs. 21%), and lymphocytopenia (ALC <1.0 x 109/L;18% vs. 28%), while others varied between Co1 and Co2 (p<0.0001), including cough (61% vs. 93%), dyspnea (60% vs. 84%), fatigue (13% vs. 77%).Median follow-up was 24 days (range 2-86) in Co1 and 17 days (1-43) in Co2. CFRs were similar in Co1 and Co2, 30% and 34% (p=0.45). 54% and 43% were discharged while 16% and 23% remained admitted at last follow-up in Co1 and Co2, respectively. The proportion of pts requiring supplemental oxygen was similar (89% vs. 92%) while rate of ICU admission was higher in Co2 (20% vs. 48%, p<0.0001). Figure 1 depicts OS in each cohort. Univariable analyses demonstrated that age and CIRS ≥6 significantly predicted inferior OS in both cohorts, while only age remained an independent predictor of inferior OS in multivariable analyses (Table 2). Prior treatment for CLL (vs. observation) predicted inferior OS in Co1 but not Co2.Conclusions : In the largest cancer dx-specific cohort reported, pts with CLL hospitalized for COVID-19 had a CFR of 30-34%. Advanced patient age at COVID-19 diagnosis was an independent predictor of OS in two large cohorts. This CFR will serve as a benchmark for mortality for future outcomes studies, including thera eutic interventions for COVID-19 in this population. The effect of CLL treatment on OS was inconsistent across cohorts;COVID-19 may be severe regardless of treatment status. While there were no significant differences in distribution of current lines of therapy between cohorts, prior chemo exposure was more common in Co1 vs. Co2, which may account for difference in OS. Extended follow-up will be presented.

3.
PLoS One ; 16(7): e0255228, 2021.
Article in English | MEDLINE | ID: covidwho-1334774

ABSTRACT

OBJECTIVES: The development of a prognostic mortality risk model for hospitalized COVID-19 patients may facilitate patient treatment planning, comparisons of therapeutic strategies, and public health preparations. METHODS: We retrospectively reviewed the electronic health records of patients hospitalized within a 13-hospital New Jersey USA network between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2, with follow-up through May 29, 2020. With death or hospital discharge by day 40 as the primary endpoint, we used univariate followed by stepwise multivariate proportional hazard models to develop a risk score on one-half the data set, validated on the remainder, and converted the risk score into a patient-level predictive probability of 40-day mortality based on the combined dataset. RESULTS: The study population consisted of 3123 hospitalized COVID-19 patients; median age 63 years; 60% were men; 42% had >3 coexisting conditions. 713 (23%) patients died within 40 days of hospitalization for COVID-19. From 22 potential candidate factors 6 were found to be independent predictors of mortality and were included in the risk score model: age, respiratory rate ≥25/minute upon hospital presentation, oxygenation <94% on hospital presentation, and pre-hospital comorbidities of hypertension, coronary artery disease, or chronic renal disease. The risk score was highly prognostic of mortality in a training set and confirmatory set yielding in the combined dataset a hazard ratio of 1.80 (95% CI, 1.72, 1.87) for one unit increases. Using observed mortality within 20 equally sized bins of risk scores, a predictive model for an individual's 40-day risk of mortality was generated as -14.258 + 13.460*RS + 1.585*(RS-2.524)^2-0.403*(RS-2.524)^3. An online calculator of this 40-day COVID-19 mortality risk score is available at www.HackensackMeridianHealth.org/CovidRS. CONCLUSIONS: A risk score using six variables is able to prognosticate mortality within 40-days of hospitalization for COVID-19. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT04347993.


Subject(s)
COVID-19/mortality , Hospital Mortality , Hospitalization , Models, Biological , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19 Nucleic Acid Testing , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Time Factors
4.
Blood ; 136(10): 1134-1143, 2020 09 03.
Article in English | MEDLINE | ID: covidwho-656981

ABSTRACT

Given advanced age, comorbidities, and immune dysfunction, chronic lymphocytic leukemia (CLL) patients may be at particularly high risk of infection and poor outcomes related to coronavirus disease 2019 (COVID-19). Robust analysis of outcomes for CLL patients, particularly examining effects of baseline characteristics and CLL-directed therapy, is critical to optimally manage CLL patients through this evolving pandemic. CLL patients diagnosed with symptomatic COVID-19 across 43 international centers (n = 198) were included. Hospital admission occurred in 90%. Median age at COVID-19 diagnosis was 70.5 years. Median Cumulative Illness Rating Scale score was 8 (range, 4-32). Thirty-nine percent were treatment naive ("watch and wait"), while 61% had received ≥1 CLL-directed therapy (median, 2; range, 1-8). Ninety patients (45%) were receiving active CLL therapy at COVID-19 diagnosis, most commonly Bruton tyrosine kinase inhibitors (BTKi's; n = 68/90 [76%]). At a median follow-up of 16 days, the overall case fatality rate was 33%, though 25% remain admitted. Watch-and-wait and treated cohorts had similar rates of admission (89% vs 90%), intensive care unit admission (35% vs 36%), intubation (33% vs 25%), and mortality (37% vs 32%). CLL-directed treatment with BTKi's at COVID-19 diagnosis did not impact survival (case fatality rate, 34% vs 35%), though the BTKi was held during the COVID-19 course for most patients. These data suggest that the subgroup of CLL patients admitted with COVID-19, regardless of disease phase or treatment status, are at high risk of death. Future epidemiologic studies are needed to assess severe acute respiratory syndrome coronavirus 2 infection risk, these data should be validated independently, and randomized studies of BTKi's in COVID-19 are needed to provide definitive evidence of benefit.


Subject(s)
Coronavirus Infections/complications , Leukemia, Lymphocytic, Chronic, B-Cell/complications , Pneumonia, Viral/complications , Adult , Agammaglobulinaemia Tyrosine Kinase/antagonists & inhibitors , Aged , Aged, 80 and over , Anti-Inflammatory Agents/therapeutic use , Antiviral Agents/therapeutic use , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/therapy , Female , Humans , Immunization, Passive , Leukemia, Lymphocytic, Chronic, B-Cell/therapy , Male , Middle Aged , Pandemics , Pneumonia, Viral/therapy , Protein Kinase Inhibitors/therapeutic use , SARS-CoV-2 , Survival Analysis , Treatment Outcome
SELECTION OF CITATIONS
SEARCH DETAIL