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Record W3214084938 · doi:10.1182/blood-2021-154283

Risks for Hospitalization and Death Among Patients with Blood Disorders from the ASH RC COVID-19 Registry for Hematology

2021· article· en· W3214084938 on OpenAlexaff
Lisa K. Hicks, Robert Redd, Kenneth C. Anderson, Pinkal Desai, Brendan Dolan, Aaron D. Goldberg, Varun Narendra, Donna Neuberg, Vivek Radhakrishnan, Laurie H. Sehn, Mikkael A. Sekeres, Maximilian Stahl, Martin S. Tallman, John Colton Thompson, Emily Tucker, William A. Wood

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsBC Cancer AgencySt. Michael's Hospital
Fundersnot available
KeywordsMedicineComorbidityInternal medicineLogistic regressionCancerHematologyCancer registry

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.344
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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