Relationships among skeletal muscle, symptom burden, health care use, and survival in hospitalized patients with advanced cancer.
Bibliographic record
Abstract
7006 Background: Loss of skeletal muscle mass (quantity) is common in patients with advanced cancer, but little is known about muscle density (quality). Hospitalized patients with advanced cancer are a highly symptomatic population at risk for the adverse effects of muscle loss. Thus, we sought to describe associations between muscle mass and density, symptom burden, health care use, and survival in these patients. Methods: We prospectively enrolled hospitalized patients with advanced cancer from 9/2014-4/2017. Upon admission, patients reported their physical (Edmonton Symptom Assessment System [ESAS]) and psychological (Patient Health Questionnaire 4 [PHQ4]) symptoms. We used computed tomography (CT) scans performed per routine care ≤45 days prior to enrollment to evaluate muscle mass and density at the level of the third lumbar vertebral body. We categorized patients as sarcopenic using validated sex specific cutoffs. We used regression models to examine associations between muscle mass and density and patients’ symptom burden, health care use, and survival. Results: Of 1,121 patients enrolled, 677 had evaluable CT scan data (mean age = 62.86±12.95 years; 51.1% female). The most common cancer types were gastrointestinal (36.8%) and lung (16.7%) cancer. Most met criteria for sarcopenia (64.0%). Older age and female sex were associated with lower muscle mass (age: B = -0.16, p < .01; female: B = -6.89, p < .01) and density (age: B = -0.33, p < 0.01; female: B = -1.66, p = .01), while higher BMI was associated with higher muscle mass (B = 0.58, p < .01) and lower muscle density (B = -0.61, p < .01). Higher muscle mass was significantly associated with improved survival (HR = 0.97, p < .01), but not with symptom burden or health care use. Higher muscle density was significantly associated with lower ESAS physical (B = -0.17, p = .02), ESAS total (B = -0.29, p < .01), PHQ4 depression (B = -0.03, p < .01) and PHQ4 anxiety (B = -0.03, p < .01) symptoms. Higher muscle density was also associated with decreased hospital length of stay (B = -0.07, p < .01), risk of readmission or death in 90 days (OR = 0.97, p < .01), and improved survival (HR = 0.97, p < .01). Conclusions: Most hospitalized patients with advanced cancer have muscle loss consistent with sarcopenia. We found that muscle mass (quantity) correlated with survival, whereas muscle density (quality) was associated with patients’ symptoms, health care use, and survival. These findings underscore the added importance of assessing muscle quality when seeking to address the adverse effects of muscle loss in oncology.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".