Muscle wasting associated with the long-term use of mTOR inhibitors
Bibliographic record
Abstract
Some targeted therapies alter muscle mass due to interference with pathways of muscle metabolism. The effects of mammalian target of ra pamycin (mTOR) inhibitors on muscle mass have yet to be fully elucidated. In the present study, the computerized tomography (CT) scans of patients receiving mTOR inhibitors for at least 6 months taken at baseline and post‑therapy were retrospectively retrieved, and body composition analyses were performed using the software, sliceOmatic version 5.0 (TomoVision, Inc., Magog, QC, Canada). The difference in body composition parameters was evaluated for significance. The time to treatment (TTF) failure was also compared between the sarcopenic and non-sarcopenic patients at the baseline. Of the 75 patients studied, 20 matched the inclusion criteria (including 16 males). The mean duration between the CT scans was 14.4±2.0 months. A total of 12 (60%) patients were sarcopenic at the baseline, whereas three more (75% in total) became sarcopenic following treatment. The use of mTOR inhibitors significantly decreased the skeletal muscle area (P=0.011) and lean body mass (P=0.007), although it had no effect on adipose tissue (P=0.163) or body weight (P=0.262). The rate of skeletal muscle wasting was 2.6 cm2/m2, or 2.3 kg in 6 months. The TTF did not differ between sarcopenic and non‑sarcopenic patients, and was not significantly associated with any other parameter. To the best of our knowledge, this is the first study to demonstrate that the long‑term use of mTOR inhibitors induces a marked loss of muscle mass. Due to the predictive and prognostic role of sarcopenia in cancer patients, these findings may have important clinical implications.
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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 | 0.001 | 0.001 |
| 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".