Association of skeletal muscle quantity and quality with mortality in women with nonmetastatic breast cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Women with breast cancer are predisposed to muscle mass loss, to compromised muscle quality, and to decreased strength, and these abnormalities may serve as important predictors of adverse outcomes, including mortality. The aim of this study was to evaluate the possible associations between muscle mass markers, assessed by computed tomography with the phase angle (PhA) obtained by Bioelectrical impedance analysis (BIA), and health outcomes in women with breast cancer. METHODS: retrospective study with 54 women newly diagnosed with breast cancer, aged ≥ 18 years and < 65 years; histologically confirmed diagnosis of early breast cancer (stage I-III range), and in the first chemotherapy-cycled treatment. Measurements performed: anthropometric assessments, BIA, third lumbar vertebra by computed tomography (CT) and physical function (handgrip strength, gait speed test 4 m, fatigue assessment), and blood biochemical analysis. RESULTS: Lower skeletal muscle index were correlated with reduced PhA values (R² = 0.222, p = 0.0047), suggesting a worse prognosis. Logistic regression analysis showed that individuals with low muscle mass had a significantly lower likelihood of survival compared to those with normal muscle mass regardless of age and cancer stage. CONCLUSION: low muscle mass negatively affected patient survival and was associated with lower PhA values. Phase angle emerges as a promising marker of overall health and could be a valuable clinical tool in assessing prognosis.
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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 | 0.000 |
| 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 it