Lean body mass as an independent determinant of dose‐limiting toxicity and neuropathy in patients with colon cancer treated with FOLFOX regimens
Bibliographic record
Abstract
Evidence suggests that lean body mass (LBM) may be useful to normalize chemotherapy doses. Data from one prospective and one retrospective study were used to determine if the highest doses of oxaliplatin/kg LBM within FOLFOX regimens would be associated with dose-limiting toxicity (DLT) in colon cancer patients. Toxicity over four cycles was graded according to NCI Common Toxicity Criteria V2 or V3 (Common Terminology Criteria for Adverse Events, National Cancer Institute, Bethesda, MD). Muscle tissue was measured by computerized tomography (CT) and used to evaluate the LBM compartment of the whole body. In prospective randomized clinical trials conducted in France (n = 58), for patients given FOLFOX-based regimens according to body surface area, values of oxaliplatin/kg LBM were highly variable, ranging from 2.55 to 6.6 mg/kg LBM. A cut point of 3.09 mg oxaliplatin/kg LBM for developing toxicity was determined by Receiver Operating Characteristic (ROC) analysis, below this value 0/17 (0.0%) of patients experienced DLT; in contrast above this value 18/41 (44.0%) of patients were dose reduced or had treatment terminated owing to toxicity (≥Grade 3 or neuropathy ≥Grade 2); for 9/41 the DLT was sensory neuropathy. These findings were validated in an independent cohort of colon cancer patients (n = 80) receiving FOLFOX regimens as part of standard care, in Canada. Low LBM is a significant predictor of toxicity and neuropathy in patients administered FOLFOX-based regimens using conventional body surface area (BSA) dosing.
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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) | 0.000 | 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".