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Record W4212905602 · doi:10.1016/s2666-7568(22)00009-5

Geriatric risk factors for serious COVID-19 outcomes among older adults with cancer: a cohort study from the COVID-19 and Cancer Consortium

2022· article· en· W4212905602 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

VenueThe Lancet Healthy Longevity · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcGill UniversityJewish General HospitalMcGill University Health Centre
FundersNational Center for Advancing Translational SciencesBeatrice and Samuel A. Seaver FoundationCanadian Institutes of Health ResearchVanderbilt Institute for Clinical and Translational ResearchNational Institute on AgingNational Cancer InstituteNational Institutes of Health
KeywordsMedicineComorbidityOdds ratioCohortCancerGeriatric oncologyInternal medicineLogistic regressionCohort studyCoronavirus disease 2019 (COVID-19)Disease

Abstract

fetched live from OpenAlex

BACKGROUND: Older age is associated with poorer outcomes of SARS-CoV-2 infection, although the heterogeneity of ageing results in some older adults being at greater risk than others. The objective of this study was to quantify the association of a novel geriatric risk index, comprising age, modified Charlson comorbidity index, and Eastern Cooperative Oncology Group performance status, with COVID-19 severity and 30-day mortality among older adults with cancer. METHODS: In this cohort study, we enrolled patients aged 60 years and older with a current or previous cancer diagnosis (excluding those with non-invasive cancers and premalignant or non-malignant conditions) and a current or previous laboratory-confirmed COVID-19 diagnosis who reported to the COVID-19 and Cancer Consortium (CCC19) multinational, multicentre, registry between March 17, 2020, and June 6, 2021. Patients were also excluded for unknown age, missing data resulting in unknown geriatric risk measure, inadequate data quality, or incomplete follow-up resulting in unknown COVID-19 severity. The exposure of interest was the CCC19 geriatric risk index. The primary outcome was COVID-19 severity and the secondary outcome was 30-day all-cause mortality; both were assessed in the full dataset. Adjusted odds ratios (ORs) and 95% CIs were estimated from ordinal and binary logistic regression models. FINDINGS: 5671 patients with cancer and COVID-19 were included in the analysis. Median follow-up time was 56 days (IQR 22-120), and median age was 72 years (IQR 66-79). The CCC19 geriatric risk index identified 2365 (41·7%) patients as standard risk, 2217 (39·1%) patients as intermediate risk, and 1089 (19·2%) as high risk. 36 (0·6%) patients were excluded due to non-calculable geriatric risk index. Compared with standard-risk patients, high-risk patients had significantly higher COVID-19 severity (adjusted OR 7·24; 95% CI 6·20-8·45). 920 (16·2%) of 5671 patients died within 30 days of a COVID-19 diagnosis, including 161 (6·8%) of 2365 standard-risk patients, 409 (18·5%) of 2217 intermediate-risk patients, and 350 (32·1%) of 1089 high-risk patients. High-risk patients had higher adjusted odds of 30-day mortality (adjusted OR 10·7; 95% CI 8·54-13·5) than standard-risk patients. INTERPRETATION: The CCC19 geriatric risk index was strongly associated with COVID-19 severity and 30-day mortality. Our CCC19 geriatric risk index, based on readily available clinical factors, might provide clinicians with an easy-to-use risk stratification method to identify older adults most at risk for severe COVID-19 as well as mortality. FUNDING: US National Institutes of Health National Cancer Institute Cancer Center.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.398
Teacher spread0.333 · 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