In this retrospective international multicenter study, we describe the clinical characteristics and outcomes of patients with chronic lymphocytic leukemia (CLL) and related disorders (small lymphocytic lymphoma and high-count monoclonal B lymphocytosis) infected by SARS-CoV-2, including the development of post-COVID condition. Data from 1540 patients with CLL infected by SARS-CoV-2 from January 2020 to May 2022 were included in the analysis and assigned to four phases based on cases disposition and SARS-CoV-2 variants emergence. Post-COVID condition was defined according to the WHO criteria. Patients infected during the most recent phases of the pandemic, though carrying a higher comorbidity burden, were less often hospitalized, rarely needed intensive care unit admission, or died compared to patients infected during the initial phases. The 4-month overall survival (OS) improved through the phases, from 68% to 83%, p = .0015. Age, comorbidity, CLL-directed treatment, but not vaccination status, emerged as risk factors for mortality. Among survivors, 6.65% patients had a reinfection, usually milder than the initial one, and 16.5% developed post-COVID condition. The latter was characterized by fatigue, dyspnea, lasting cough, and impaired concentration. Infection severity was the only risk factor for developing post-COVID. The median time to resolution of the post-COVID condition was 4.7 months. OS in patients with CLL improved during the different phases of the pandemic, likely due to the improvement of prophylactic and therapeutic measures against SARS-CoV-2 as well as the emergence of milder variants. However, mortality remained relevant and a significant number of patients developed post-COVID conditions, warranting further investigations.
BACKGROUND: Increasingly large and complex biomedical data sets challenge conventional hypothesis-driven analytical approaches, however, data-driven unsupervised learning can detect inherent patterns in such data sets. METHODS: While unsupervised analysis in the medical literature commonly only utilizes a single clustering algorithm for a given data set, we developed a large-scale model with 605 different combinations of target dimensionalities as well as transformation and clustering algorithms and subsequent meta-clustering of individual results. With this model, we investigated a large cohort of 1383 patients from 59 centers in Germany with newly diagnosed acute myeloid leukemia for whom 212 clinical, laboratory, cytogenetic and molecular genetic parameters were available. RESULTS: Unsupervised learning identifies four distinct patient clusters, and statistical analysis shows significant differences in rate of complete remissions, event-free, relapse-free and overall survival between the four clusters. In comparison to the standard-of-care hypothesis-driven European Leukemia Net (ELN2017) risk stratification model, we find all three ELN2017 risk categories being represented in all four clusters in varying proportions indicating unappreciated complexity of AML biology in current established risk stratification models. Further, by using assigned clusters as labels we subsequently train a supervised model to validate cluster assignments on a large external multicenter cohort of 664 intensively treated AML patients. CONCLUSIONS: Dynamic data-driven models are likely more suitable for risk stratification in the context of increasingly complex medical data than rigid hypothesis-driven models to allow for a more personalized treatment allocation and gain novel insights into disease biology.
- Publication type
- Journal Article MeSH
BACKGROUND: Patients with chronic lymphocytic leukemia (CLL) may be more susceptible to COVID-19 related poor outcomes, including thrombosis and death, due to the advanced age, the presence of comorbidities, and the disease and treatment-related immune deficiency. The aim of this study was to assess the risk of thrombosis and bleeding in patients with CLL affected by severe COVID-19. METHODS: This is a retrospective multicenter study conducted by ERIC, the European Research Initiative on CLL, including patients from 79 centers across 22 countries. Data collection was conducted between April and May 2021. The COVID-19 diagnosis was confirmed by the real-time polymerase chain reaction (RT-PCR) assay for SARS-CoV-2 on nasal or pharyngeal swabs. Severe cases of COVID-19 were defined by hospitalization and the need of oxygen or admission into ICU. Development and type of thrombotic events, presence and severity of bleeding complications were reported during treatment for COVID-19. Bleeding events were classified using ISTH definition. STROBE recommendations were used in order to enhance reporting. RESULTS: A total of 793 patients from 79 centers were included in the study with 593 being hospitalized (74.8%). Among these, 511 were defined as having severe COVID: 162 were admitted to the ICU while 349 received oxygen supplementation outside the ICU. Most patients (90.5%) were receiving thromboprophylaxis. During COVID-19 treatment, 11.1% developed a thromboembolic event, while 5.0% experienced bleeding. Thrombosis developed in 21.6% of patients who were not receiving thromboprophylaxis, in contrast to 10.6% of patients who were on thromboprophylaxis. Bleeding episodes were more frequent in patients receiving intermediate/therapeutic versus prophylactic doses of low-molecular-weight heparin (LWMH) (8.1% vs. 3.8%, respectively) and in elderly. In multivariate analysis, peak D-dimer level and C-reactive protein to albumin ratio were poor prognostic factors for thrombosis occurrence (OR = 1.022, 95%CI 1.007‒1.038 and OR = 1.025, 95%CI 1.001‒1.051, respectively), while thromboprophylaxis use was protective (OR = 0.199, 95%CI 0.061‒0.645). Age and LMWH intermediate/therapeutic dose administration were prognostic factors in multivariate model for bleeding (OR = 1.062, 95%CI 1.017-1.109 and OR = 2.438, 95%CI 1.023-5.813, respectively). CONCLUSIONS: Patients with CLL affected by severe COVID-19 are at a high risk of thrombosis if thromboprophylaxis is not used, but also at increased risk of bleeding under the LMWH intermediate/therapeutic dose administration.
- MeSH
- Anticoagulants MeSH
- Leukemia, Lymphocytic, Chronic, B-Cell * MeSH
- COVID-19 * MeSH
- COVID-19 Drug Treatment MeSH
- Heparin, Low-Molecular-Weight MeSH
- Hemorrhage MeSH
- Humans MeSH
- SARS-CoV-2 MeSH
- Aged MeSH
- COVID-19 Testing MeSH
- Thrombosis * MeSH
- Venous Thromboembolism * MeSH
- Check Tag
- Humans MeSH
- Aged MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
Patients with chronic lymphocytic leukemia (CLL) may be more susceptible to Coronavirus disease 2019 (COVID-19) due to age, disease, and treatment-related immunosuppression. We aimed to assess risk factors of outcome and elucidate the impact of CLL-directed treatments on the course of COVID-19. We conducted a retrospective, international study, collectively including 941 patients with CLL and confirmed COVID-19. Data from the beginning of the pandemic until March 16, 2021, were collected from 91 centers. The risk factors of case fatality rate (CFR), disease severity, and overall survival (OS) were investigated. OS analysis was restricted to patients with severe COVID-19 (definition: hospitalization with need of oxygen or admission into an intensive care unit). CFR in patients with severe COVID-19 was 38.4%. OS was inferior for patients in all treatment categories compared to untreated (p < 0.001). Untreated patients had a lower risk of death (HR = 0.54, 95% CI:0.41-0.72). The risk of death was higher for older patients and those suffering from cardiac failure (HR = 1.03, 95% CI:1.02-1.04; HR = 1.79, 95% CI:1.04-3.07, respectively). Age, CLL-directed treatment, and cardiac failure were significant risk factors of OS. Untreated patients had a better chance of survival than those on treatment or recently treated.
- MeSH
- Survival Analysis MeSH
- Leukemia, Lymphocytic, Chronic, B-Cell complications mortality therapy virology MeSH
- COVID-19 complications diagnosis mortality virology MeSH
- Humans MeSH
- Mortality MeSH
- Prognosis MeSH
- Risk Factors MeSH
- SARS-CoV-2 MeSH
- Severity of Illness Index MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Chronic lymphocytic leukemia (CLL) is a disease of the elderly, characterized by immunodeficiency. Hence, patients with CLL might be considered more susceptible to severe complications from COVID-19. We undertook this retrospective international multicenter study to characterize the course of COVID-19 in patients with CLL and identify potential predictors of outcome. Of 190 patients with CLL and confirmed COVID-19 diagnosed between 28/03/2020 and 22/05/2020, 151 (79%) presented with severe COVID-19 (need of oxygen and/or intensive care admission). Severe COVID-19 was associated with more advanced age (≥65 years) (odds ratio 3.72 [95% CI 1.79-7.71]). Only 60 patients (39.7%) with severe COVID-19 were receiving or had recent (≤12 months) treatment for CLL at the time of COVID-19 versus 30/39 (76.9%) patients with mild disease. Hospitalization rate for severe COVID-19 was lower (p < 0.05) for patients on ibrutinib versus those on other regimens or off treatment. Of 151 patients with severe disease, 55 (36.4%) succumbed versus only 1/38 (2.6%) with mild disease; age and comorbidities did not impact on mortality. In CLL, (1) COVID-19 severity increases with age; (2) antileukemic treatment (particularly BTK inhibitors) appears to exert a protective effect; (3) age and comorbidities did not impact on mortality, alluding to a relevant role of CLL and immunodeficiency.
- MeSH
- Antineoplastic Agents pharmacology therapeutic use MeSH
- Betacoronavirus * MeSH
- Leukemia, Lymphocytic, Chronic, B-Cell complications drug therapy MeSH
- Protein Kinase Inhibitors pharmacology therapeutic use MeSH
- Comorbidity MeSH
- Coronavirus Infections diagnosis mortality pathology MeSH
- Middle Aged MeSH
- Humans MeSH
- Pandemics MeSH
- Prognosis MeSH
- Surveys and Questionnaires MeSH
- Pyrazoles pharmacology therapeutic use MeSH
- Pyrimidines pharmacology therapeutic use MeSH
- Retrospective Studies MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Severity of Illness Index MeSH
- Age Factors MeSH
- Pneumonia, Viral diagnosis mortality pathology MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Research Support, Non-U.S. Gov't MeSH
