Diagnostic Criteria for the Classification of Cancer-Associated Weight Loss
Bibliographic record
Abstract
PURPOSE: Existing definitions of clinically important weight loss (WL) in patients with cancer are unclear and heterogeneous and do not consider current trends toward obesity. METHODS: Canadian and European patients with cancer (n = 8,160) formed a population-based data set. Body mass index (BMI) and percent WL (%WL) were recorded, and patients were observed prospectively until death. Data were entered into a multivariable analysis controlling for age, sex, cancer site, stage, and performance status. Relationships for BMI and %WL to overall survival were examined to develop a grading system. RESULTS: Mean overall %WL was -9.7% ± 8.4% and BMI was 24.4 ± 5.1 kg/m(2), and both %WL and BMI independently predicted survival (P < .01). Differences in survival were observed across five categories of BMI (< 20.0, 20.0 to 21.9, 22.0 to 24.9, 25.0 to 27.9, and ≥ 28.0 kg/m(2); P < .001) and five categories of %WL (-2.5% to -5.9%, -6.0% to -10.9%, -11.0% to -14.9%, ≥ -15.0%, and weight stable (± 2.4%); P < .001). A 5 × 5 matrix representing the five %WL categories within each of the five BMI categories was graded based on median survival and prognostic significance. Weight-stable patients with BMI ≥ 25.0 kg/m(2) (grade 0) had the longest survival (20.9 months; 95% CI, 17.9 to 23.9 months), and %WL values associated with lowered categories of BMI were related to shorter survival (P < .001), as follows: grade 1, 14.6 months (95% CI, 12.9 to 16.2 months); grade 2, 10.8 months (95% CI, 9.7 to 11.9 months); grade 3, 7.6 months (95% CI, 7.0 to 8.2 months); and grade 4, 4.3 months (95% CI, 4.1 to 4.6 months). Survival discrimination by grade was observed within specific cancers, stages, ages, and performance status and in an independent validation sample (n = 2,963). CONCLUSION: A robust grading system incorporating the independent prognostic significance of both BMI and %WL was developed.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".