Associations between severe co‐morbidity and muscle measures in advanced non‐small cell lung cancer patients
Bibliographic record
Abstract
Abstract Background Studies show that low skeletal muscle index (SMI) and low skeletal muscle density (SMD) are negative prognostic factors and associated with more toxicity from systemic therapy in cancer patients. However, muscle depletion can be caused by a range of diseases, and many cancer patients have significant co‐morbidity. The aim of this study was to investigate whether there were associations between co‐morbidity and muscle measures in patients with advanced non‐small cell lung cancer. Methods Patients in a Phase III trial comparing two chemotherapy regimens in advanced non‐small cell lung cancer were analysed ( n = 436). Co‐morbidity was assessed using the Cumulative Illness Rating Scale for Geriatrics (CIRS‐G), which rates co‐morbidity from 0 to 4 on 14 different organ scales. Severe co‐morbidity was defined as having any grades 3 and 4 CIRS‐G score. Muscle measures were assessed from baseline computed tomography slides at the L3 level using the SliceOMatic software. Results Complete data were available for 263 patients (60%). Median age was 66, 57.0% were men, 78.7% had performance status 0–1, 25.9% Stage IIIB, 11.4% appetite loss, 92.4% were current/former smokers, 22.8% were underweight, 43.7% had normal weight, 26.6% were overweight, and 6.8% obese. The median total CIRS‐G score was 7 (range: 0–16), and 48.2% had severe co‐morbidity. Mean SMI was 44.7 cm 2 /m 2 (range: 27–71), and the mean SMD was 37.3 Hounsfield units (HU) (range: 16–60). When comparing patients with and without severe co‐morbidity, there were no significant differences in median SMI (44.5 vs. 44.1 cm 2 /m 2 ; 0.70), but patients with severe co‐morbidity had a significantly lower median SMD (36 HU vs. 39 HU; 0.001), mainly due to a significant difference in SMD between those with severe heart disease and those without (32.5 vs. 37.9 HU; 0.002). Linear regression analyses confirmed the association between severe co‐morbidity and SMD both in the simple analysis (0.001) and the multiple analysis (0.037) adjusting for baseline characteristics. Stage of disease, gender, and body mass index (BMI) were significantly associated with SMI in both the simple and multiple analyses. Age and BMI were significantly associated with SMD in the simple analysis; and age, gender, and BMI were significantly associated in the multiple analysis. Conclusions There were no significant differences in SMI between patients with and patients without severe co‐morbidity, but patients with severe co‐morbidity had lower SMD than other patients, mainly due to severe heart disease. Co‐morbidity might be a confounder in studies of the clinical role of SMD in cancer patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".