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Record W4392023112 · doi:10.1016/j.clnu.2024.02.020

Quantifying the severity of sarcopenia in patients with cancer of the head and neck

2024· article· en· W4392023112 on OpenAlexafffund
Catherine Kubrak, Lisa Martin, Aaron J. Grossberg, Brennan Olson, Faith D. Ottery, Merran Findlay, Judith Bauer, Naresh Jha, Rufus Scrimger, Brock Debenham, Neil Chua, John Walker, Vickie E. Baracos

Bibliographic record

VenueClinical Nutrition · 2024
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsAlberta Health ServicesAlberta HealthUniversity of Alberta
FundersCanadian Institutes of Health ResearchBaxter International
KeywordsMedicineSarcopeniaHead and neck cancerHead and neckOncologyInternal medicineCancerSurgery

Abstract

fetched live from OpenAlex

BACKGROUND & AIMS: Existing skeletal muscle index (SMI) thresholds for sarcopenia are inconsistent, and do not reflect severity of depletion. In this study we aimed to define criterion values for moderate and severe skeletal muscle depletion based on the risk of mortality in a population of patients with head and neck cancer (HNC). Additionally, we aimed to identify clinical and demographic predictors of skeletal muscle depletion, evaluate the survival impact of skeletal muscle depletion in patients with minimal nutritional risk or good performance status, and finally, benchmarking SMI values of patients with HNC against healthy young adults. METHODS: Population cohort of 1231 consecutive patients and external validation cohorts with HNC had lumbar SMI measured by cross-sectional imaging. Optimal stratification determined sex-specific thresholds for 2-levels of SMI depletion (Class I and II) based on overall survival (OS). Adjusted multivariable regression analyses (tumor site, stage, performance status, age, sex, dietary intake, weight loss) determined relationships between 2-levels of SMI depletion and OS. RESULTS: ) depletion thresholds for 2-levels of muscle depletion determined by optimal stratification for males and females, respectively (male: 45.2-37.5, and <37.5; female: 40.9-34.2, and <34.2). In the overall population, Normal SMI, Class I and II SMI depletion occurred in 65.0%, 24.0%, and 11.0%, respectively. Median OS was: Normal SMI (114 months, 95% CI, 97.1-130.8); Class I SMI Depletion (42 months, 95% CI, 28.5-55.4), and Class II SMI Depletion (15 months, 95% CI, 9.8-20.1). Adjusted multivariable analysis compared with Normal SMI (reference), Class I SMI Depletion (HR, 1.49; 95% CI, 1.18-1.88; P < .001), Class II SMI Depletion (HR, 1.91; 95% CI, 1.42-2.58; P < .001). CONCLUSIONS: Moderate and severe SMI depletion demonstrate discrimination in OS in patients with HNC. Moderate and severe SMI depletion is prevalent in patients with minimal nutrition risk and good performance status. Benchmarking SMI values against healthy young adults exemplifies the magnitude of SMI depletion in patients with HNC and may be a useful method in standardizing SMI assessment.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.009
Threshold uncertainty score0.110

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.118
GPT teacher head0.449
Teacher spread0.331 · 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 teacher head, 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".

Quick stats

Citations25
Published2024
Admission routes2
Has abstractyes

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