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Record W3136076419 · doi:10.1016/j.annonc.2021.02.024

Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium

2021· article· en· W3136076419 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnals of Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcGill University Health Centre
FundersNational Center for Advancing Translational SciencesMerck Sharp and DohmeEMD SeronoBavarian NordicSociedad Española de Oncología MédicaSwedish Orphan BiovitrumAstellas PharmaJanssen PharmaceuticalsKorean Foundation for Cancer ResearchEisaiNateraBeiGeneDaiichi-SankyoAimmune TherapeuticsDaiichi Sankyo EuropeAgios PharmaceuticalsBayer FundMirati TherapeuticsIncyteProstate Cancer FoundationHope FoundationHalozymeClovis OncologyAmerican Society of Clinical OncologyHeron TherapeuticsSanofiTG TherapeuticsAlexion PharmaceuticalsExelixisAstellas Pharma USCastle BiosciencesDana-Farber Cancer InstitutePTC TherapeuticsTakeda Pharmaceuticals U.S.A.CelgeneIpsen BiopharmaceuticalsGenomic HealthF. Hoffmann-La RocheNational Comprehensive Cancer NetworkAmerican Cancer SocietyAmerican College of Radiology Imaging NetworkVanderbilt Institute for Clinical and Translational ResearchVanderbilt UniversityHarvard Medical SchoolIpsenPancreatic Cancer Action NetworkBristol-Myers SquibbTeva Pharmaceutical IndustriesFoundation MedicineGlaxoSmithKlineDana-Farber/Harvard Cancer CenterEli Lilly and CompanyGenentechAstraZenecaNational Cancer InstituteGenzymeKommission für Technologie und InnovationPfizerAmgenECOG-ACRIN Cancer Research GroupMerck KGaANational Institutes of HealthConquer Cancer FoundationFonds de Recherche du Québec - SantéMerck CanadaArray BioPharma
KeywordsMedicineInternal medicineCancerAbsolute neutrophil countLung cancerChemotherapyNeutropenia

Abstract

fetched live from OpenAlex

BACKGROUND: Patients with cancer may be at high risk of adverse outcomes from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed a cohort of patients with cancer and coronavirus 2019 (COVID-19) reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anticancer therapies. PATIENTS AND METHODS: Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between 17 March and 18 November 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anticancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients). RESULTS: A total of 4966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic black race, Hispanic ethnicity, worse Eastern Cooperative Oncology Group performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count; high absolute neutrophil count; low platelet count; abnormal creatinine; troponin; lactate dehydrogenase; and C-reactive protein were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anticancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality. CONCLUSIONS: Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anticancer therapies. CLINICAL TRIAL IDENTIFIER: NCT04354701.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.165
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.233
GPT teacher head0.516
Teacher spread0.283 · 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