Capecitabine dosing using skeletal muscle index (SMI) compared to body surface area (BSA).
Bibliographic record
Abstract
722 Background: Capecitabine dose used to treat colorectal (CRC) and breast cancer (BC) is calculated using BSA. Capecitabine dose is 1250 mg/m2 in CRC and 1000 mg/m2 in BC. Using BSA to calculate dose does not consider body composition. We hypothesize that differences in capecitabine dose between CRC and BC patients (pts) is due to body composition differences between men and women, not cancer type. We hypothesize females starting treatment at 1250 mg/m2 have a higher capecitabine dose/SMI than males, and dose reductions for dose-limiting toxicity (DLT) would lead to male and female CRC pts receiving the same capecitabine dose/SMI. Methods: This is a retrospective study of early stage CRC pts treated with adjuvant capecitabine from 2008-2012. Collected demographic data included age, stage, gender, height, weight, and performance status. Capecitabine doses at cycles 1 and 3 were documented. SMI was calculated using pre-treatment CT scans. Results: 183 pts (101 males, 82 females) were identified. Females received a higher starting capecitabine dose compared to males based on SMI. Mean capecitabine/SMI dose was 5107.4 mg/cm2/m2 (SD 1113.8) for females compared to 4711.9 mg/cm2/m2 (SD 870.6) for males (p = 0.009). At cycle 3, females still had a higher dose of 3875.1 mg/cm2/m2 (SD 1663.5), although it was not statistically significant from their male counterparts at 3691.6 mg/cm2/m2 (SD 1629.5) (p = 0.4580). Conclusions: Females received higher capecitabine doses/SMI than males at the CRC 1250 mg/m2 dose. This is in keeping with our previous study that showed female CRC pts on adjuvant capecitabine experience more DLTs compared to males. After adjusting capecitabine doses for DLTs, male and female CRC pts received the same cape dose/SMI. This suggests SMI may be more useful than BSA when adjusting capecitabine doses.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".