The impact of cachexia on dietary intakes, symptoms, and quality of life in advanced cancer
Bibliographic record
Abstract
Abstract Background The relationships between cachexia stages and the Functional Assessment of Anorexia/Cachexia Therapy Anorexia Cachexia Subscale (FAACT ACS) 12‐item, 5‐item anorexia symptoms, and 4‐item anorexia concerns have not been investigated in Asian patients with advanced cancer. Methods This is a multicentre questionnaire survey conducted in palliative and supportive care settings across Japan. Consecutive patients were enrolled. Patient characteristics and anthropometric measurements were obtained. Dietary intakes and nutrition impact symptoms were also assessed. Patients evaluated their quality of life (QOL) using FAACT ACS. Subjects were divided into two groups, that is, pre‐cachexia (non‐cachexia) and cachexia and refractory cachexia (cachexia), based on cancer cachexia criteria from the international consensus. Comparisons were performed using the Mann–Whitney U test or chi‐squared test. To evaluate the relationship between cachexia stages and FAACT ACS 12‐item, 5‐item anorexia symptoms, and 4‐item anorexia concerns, adjusted odd ratios (ORs) and 95% confidence intervals (CIs) were calculated in the logistic models. Results Among 495 patients, 378 (76.4%) responded. Due to missing data, 344 patients were classified into the non‐cachexia group (n = 174) and cachexia group (n = 170), and 318 remained in the analysis of FAACT ACS. The cachexia group had a more impaired performance status, a lower body mass index, and a higher frequency of weight loss in 1 month (P = 0.021, <0.001, and <0.001, respectively). Advancing stages were associated with lack of appetite and reduced dietary intakes (P < 0.001 and P < 0.001, respectively). QOL scores were significantly worse in the cachexia group in FAACT ACS 12‐item, 5‐item anorexia symptoms, and 4‐item anorexia concerns (P < 0.001, P = 0.001, and P < 0.001, respectively). In the models of FAACT ACS 12‐item, 5‐item anorexia symptoms, and 4‐item anorexia concerns, significantly higher adjusted ORs than in the non‐cachexia group were observed in the cachexia group [2.24 (95% CI 1.34–3.77), P = 0.002; 1.77 (95% CI 1.08–2.92), P = 0.024; and 2.18 (95% CI 1.29–3.70), P = 0.004, respectively]. Conclusions FAACT ACS 12‐item, 5‐item anorexia symptoms, and 4‐item anorexia concerns are useful for identifying patients at risk of QOL that deteriorates with advancing stages in this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".