Cancer Cachexia: Beyond Weight Loss
Bibliographic record
Abstract
Cancer cachexia is a multifactorial syndrome characterized by skeletal muscle loss leading to progressive functional impairment. Despite the ubiquity of cachexia in clinical practice, prevention, early identification, and intervention remain challenging. The impact of cancer cachexia on quality of life, treatment-related toxicity, physical function, and mortality are well established; however, establishing a clinically meaningful definition has proven challenging because of the focus on weight loss alone. Attempts to more comprehensively define cachexia through body composition, physical functioning, and molecular biomarkers, while promising, are yet to be routinely incorporated into clinical practice. Pharmacologic agents that have not been approved by the US Food and Drug Administration but that are currently used in cancer cachexia (ie, megestrol, dronabinol) may improve weight but not outcomes of interest such as muscle mass, physical activity, or mortality. Their routine use is limited by adverse effects. For the practicing oncologist, early identification and management of cachexia is critical. Oncologists must recognize cachexia beyond weight loss alone, focusing instead on body composition and physical functioning. In fact, becoming emaciated is a late sign of cachexia that characterizes its refractory stage. Given that cachexia is a multifactorial syndrome, it requires early identification and polymodal intervention, including optimal cancer therapy, symptom management, nutrition, exercise, and psychosocial support. Consequently, oncologists have a role in ensuring that these resources are available to their patients. In addition, in light of the promising investigational agents, it remains imperative to refer patients with cachexia to clinical trials so that available options can be expanded to effectively treat this pervasive problem.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".