Body Composition, Symptoms, and Survival in Advanced Cancer Patients Referred to a Phase I Service
Bibliographic record
Abstract
BACKGROUND: Body weight and body composition are relevant to the outcomes of cancer and antineoplastic therapy. However, their role in Phase I clinical trial patients is unknown. METHODS: We reviewed symptom burden, body composition, and survival in 104 patients with advanced cancer referred to a Phase I oncology service. Symptom burden was analyzed using the MD Anderson Symptom Assessment Inventory(MDASI); body composition was evaluated utilizing computerized tomography(CT) images. A body mass index (BMI)≥25 kg/m² was considered overweight. Sarcopenia, severe muscle depletion, was assessed using CT-based criteria. RESULTS: Most patients were overweight (n = 65, 63%); 53 patients were sarcopenic (51%), including 79% of patients with a BMI<25 kg/m² and 34% of those with BMI≥25 kg/m². Sarcopenic patients were older and less frequently African-American. Symptom burden did not differ among patients classified according to BMI and presence of sarcopenia. Median (95% confidence interval) survival (days) varied according to body composition: 215 (71-358) (BMI<25 kg/m²; sarcopenic), 271 (99-443) (BMI<25 kg/m²; non-sarcopenic), 484 (286-681) (BMI≥25 kg/m²; sarcopenic); 501 d (309-693) (BMI≥25 kg/m²; non-sarcopenic). Higher muscle index and gastrointestinal cancer diagnosis predicted longer survival in multivariate analysis after controlling for age, gender, performance status, and fat index. CONCLUSIONS: Patients referred to a Phase I clinic had a high frequency of sarcopenia and a BMI≥25 kg/m², independent of symptom burden. Body composition variables were predictive of clinically relevant survival differences, which is potentially important in developing Phase I studies.
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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".