Skeletal muscle anabolism is a side effect of therapy with the MEK inhibitor: selumetinib in patients with cholangiocarcinoma
Bibliographic record
Abstract
BACKGROUND: Cancer cachexia is characterised by skeletal muscle wasting; however, potential for muscle anabolism in patients with advanced cancer is unproven. METHODS: Quantitative analysis of computed tomography images for loss/gain of muscle in cholangiocarcinoma patients receiving selumetinib (AZD6244; ARRY-142886) in a Phase II study, compared with a separate standard therapy group. Selumetinib is an inhibitor of mitogen-activated protein/extracellular signal-regulated kinase and of interleukin-6 secretion, a putative mediator of muscle wasting. RESULTS: Overall, 84.2% of patients gained muscle after initiating selumetinib; mean overall gain of total lumbar muscle cross-sectional area was 13.6 cm(2)/100 days (∼2.3 kg on a whole-body basis). Cholangiocarcinoma patients who began standard treatment were markedly catabolic, with overall muscle loss of -7.3 cm(2)/100 days (∼1.2 kg) and by contrast only 16.7% of these patients gained muscle. CONCLUSION: Our findings suggest that selumetinib promotes muscle gain in patients with cholangiocarcinoma. Specific mechanisms and relevance for cachexia therapy remain to be investigated.
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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 | 0.000 | 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) | 0.001 | 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".