Risks for Hospitalization and Death Among Patients with Blood Disorders from the ASH RC COVID-19 Registry for Hematology
Notice bibliographique
Résumé
Abstract INTRODUCTION: Patients (pts) with blood disorders are at particular risk for severe infection and death from COVID-19. Factors that contribute to this risk, including cancer treatment, have not been clearly delineated. The ASH RC COVID-19 Registry for Hematology is a public-facing, volunteer registry reporting outcomes of COVID-19 infection in pts with underlying blood disorders. We report a multivariable analysis of the impact of cancer treatment and other key variables on COVID-19 mortality and hospitalization among pts with blood cancer. METHODS: Data were collected between April 1, 2020, and July 2, 2021. All analyses were performed using R version 4.0.2. Multivariable logistic regression explored associations between mortality and seven patient/disease factors previously reported as important to COVID-19 outcome. Independent variables included: age (>60); sex; presence of a major comorbidity (defined as any of heart disease, hypertension, pulmonary disease and/or diabetes); type of hematologic malignancy; estimated prognosis of < 6 months prior to COVID-19; deferral of ICU care; and administration of cancer treatment in the previous year (excluding single agent hydroxyurea). A secondary multivariable logistic regression explored associations between the same variables and hospitalization with COVID-19. RESULTS: We included all pts in the registry with a malignant diagnosis except for 3 patients excluded based on a data sharing agreement (N=1029). Median age category was 50-59y (range <5y to > 90y). The sample was 42% female and 28% had major comorbidities. Types of hematologic malignancies were 354 (34%) acute leukemia/MDS, 255 (25%) lymphoma, 206 (20%) plasma cell dyscrasia (myeloma/amyloid/POEMS), 116 (11%) CLL, 98 (10%) myeloproliferative neoplasm (MPN). Most pts (73%) received cancer treatment during the previous year, 9% had a pre-COVID-19 prognosis of <6months, and 10% deferred ICU care. COVID-19 mortality in the entire cohort was 17%. In multivariable analyses, age > 60 (OR 2.03, 1.31-3.18), male sex (OR 1.69, 1.11 - 2.61), estimated pre-COVID-19 prognosis of less than 6 months (OR 6.16, 3.26 - 11.70) and ICU deferral (OR 10.87, 6.36 - 18.96) were all independently associated with an increased risk of death. Receiving cancer treatment in the year prior to COVID-19 diagnosis and type of hematologic malignancy were not significantly associated with death. In multivariable analyses, age > 60 (OR 2.46, 1.83 - 3.31), male sex (OR 1.34, 1.02 - 1.76), estimated pre-COVID-19 prognosis of < 6 months (OR 4.81, 2.45 - 10.50), presence of a major comorbidity (OR 1.57, 1.15 - 2.16), and cancer treatment in the previous year (OR 1.50, 1.10 - 2.06) were all independently associated with an increased risk of a severe COVID-19 requiring hospitalization. Pts with a MPN or plasma cell dyscrasia and COVID-19 were less likely to require hospitalization for COVID-19 compared to patients with CLL, leukemia/MDS, or lymphoma. CONCLUSIONS: These analyses confirm the negative impact of age > 60, male sex, pre-COVID-19 prognosis of < 6 months, and deferral of ICU care on mortality among patients with hematologic malignancy and COVID-19. We did not observe an increased risk of COVID-19 mortality among pts with COVID-19 who received blood cancer treatment in the previous year, although rate of hospitalization was higher. Pts with some hematologic malignancies (MPN, plasma cell dyscrasias), may experience less severe COVID-19 infections than others. Disclosures Anderson: Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees. Desai: Janssen R&D: Research Funding; Astex: Research Funding; Kura Oncology: Consultancy; Agios: Consultancy; Bristol Myers Squibb: Consultancy; Takeda: Consultancy. Goldberg: Celularity: Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Aptose: Consultancy, Research Funding; Prelude Therapeutics: Research Funding; DAVA Oncology: Honoraria; Pfizer: Research Funding; Arog: Research Funding; Aprea: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Neuberg: Madrigal Pharmaceuticals: Other: Stock ownership; Pharmacyclics: Research Funding. Radhakrishnan: Janssen India: Honoraria; Dr Reddy's Laboratories: Honoraria, Membership on an entity's Board of Directors or advisory committees; Aurigene: Speakers Bureau; Novartis: Honoraria; Johnson and Johnson: Honoraria; Pfizer: Consultancy, Honoraria; Astrazeneca: Consultancy, Honoraria; Emcure Pharmaceuticals: Other: payment to institute; Cipla Pharmaceuticals: Honoraria, Other: payment to institute; Bristol Myers Squibb: Other: payment to institute; Roche: Honoraria, Other: payment to institute; Intas Pharmaceutical: Other: payment to institute; NATCO Pharmaceuticals: Research Funding. Sehn: Genmab: Consultancy; Debiopharm: Consultancy; Novartis: Consultancy. Sekeres: Novartis: Membership on an entity's Board of Directors or advisory committees; Takeda/Millenium: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Tallman: Kura: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Biosight: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Oncolyze: Membership on an entity's Board of Directors or advisory committees; KAHR: Membership on an entity's Board of Directors or advisory committees; Orsenix: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Rafael Pharmaceuticals: Research Funding; Glycomimetics: Research Funding; Biosight: Research Funding; Orsenix: Research Funding; Abbvie: Research Funding; NYU Grand Rounds: Honoraria; Mayo Clinic: Honoraria; UC DAVIS: Honoraria; Northwell Grand Rounds: Honoraria; NYU Grand Rounds: Honoraria; Danbury Hospital Tumor Board: Honoraria; Acute Leukemia Forum: Honoraria; Miami Leukemia Symposium: Honoraria; New Orleans Cancer Symposium: Honoraria; ASH: Honoraria; NCCN: Honoraria.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».