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Record W3194929515 · doi:10.1002/jcsm.12756

Diagnostic criteria for cancer cachexia: reduced food intake and inflammation predict weight loss and survival in an international, multi‐cohort analysis

2021· article· en· W3194929515 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2021
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsJewish General HospitalUniversity of TorontoUniversité LavalUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta InnovatesKillam Trusts
KeywordsMedicineInternal medicineWeight lossConfidence intervalCachexiaProportional hazards modelCancerCohortBiomarkerClinical endpointHazard ratioGastroenterologyObesityClinical trial

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer-associated weight loss (WL) associates with increased mortality. International consensus suggests that WL is driven by a variable combination of reduced food intake and/or altered metabolism, the latter often represented by the inflammatory biomarker C-reactive protein (CRP). We aggregated data from Canadian and European research studies to evaluate the associations of reduced food intake and CRP with cancer-associated WL (primary endpoint) and overall survival (OS, secondary endpoint). METHODS: The data set included a total of 12,253 patients at risk for cancer-associated WL. Patient-reported WL history (% in 6 months) and food intake (normal, moderately, or severely reduced) were measured in all patients; CRP (mg/L) and OS were measured in N = 4960 and N = 9952 patients, respectively. All measures were from a baseline assessment. Clinical variables potentially associated with WL and overall survival (OS) including age, sex, cancer diagnosis, disease stage, and performance status were evaluated using multinomial logistic regression MLR and Cox proportional hazards models, respectively. RESULTS: Patients had a mean weight change of -7.3% (±7.1), which was categorized as: ±2.4% (stable weight; 30.4%), 2.5-5.9% (19.7%), 6.0-10.0% (23.2%), 11.0-14.9% (12.0%), ≥15.0% (14.6%). Normal food intake, moderately, and severely reduced food intake occurred in 37.9%, 42.8%, and 19.4%, respectively. In MLR, severe WL (≥15%) (vs. stable weight) was more likely (P < 0.0001) if food intake was moderately [OR 6.28, 95% confidence interval (CI 5.28-7.47)] or severely reduced [OR 18.98 (95% CI 15.30-23.56)]. In subset analysis, adjusted for food intake, CRP was independently associated (P < 0.0001) with ≥15% WL [CRP 10-100 mg/L: OR 2.00, (95% CI 1.58-2.53)] and [CRP > 100 mg/L: OR 2.30 (95% CI 1.62-3.26)]. Diagnosis, stage, and performance status, but not age or sex, were significantly associated with WL. Median OS was 9.9 months (95% CI 9.5-10.3), with median follow-up of 39.7 months (95% CI 38.8-40.6). Moderately and severely reduced food intake and CRP independently predicted OS (P < 0.0001). CONCLUSIONS: Modelling WL as the dependent variable is an approach that can help to identify clinical features and biomarkers associated with WL. Here, we identify criterion values for food intake impairment and CRP that may improve the diagnosis and classification of cancer-associated cachexia.

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)0.000
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 score0.023
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.048
GPT teacher head0.373
Teacher spread0.326 · 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