Abstract P3-08-73: Muscle measures, body composition, and function in patients with early breast cancer
Bibliographic record
Abstract
Abstract Introduction: Sarcopenia and muscle composition are associated with treatment-related toxicities and adverse events in women with EBC (Shachar 2017). We investigated the relationship of muscle mass with other measures of body composition as well as comorbidities, physical function, fatigue, and quality of life. Methods: Women age 21 or older were enrolled in intervention studies (NCT02167932, NCT02328313) investigating home-based walking during chemotherapy for early breast cancer (stage I-III). Prior to the start of chemotherapy, patients completed the Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG) test. When available from staging, transverse views of computed tomography (CT) through L3 lumbar segments were analyzed using Slice-O-Matic software (Tomovision Quebec, Canada) to ascertain skeletal muscle area (SMA= -29 to +150 Hounsfield Units), skeletal muscle density (SMD= average attenuation of skeletal muscle in HU), skeletal muscle index (SMI= SMA/height2), and skeletal muscle gauge (SMG= SMI x SMD). BSA and BMI were calculated using standard formulas. Descriptive statistics (mean and standard deviation (SD)) were estimated and simple linear regression models were used to evaluate associations of body composition, function and quality of life and continuous muscle measures. Pearson correlation coefficients were estimated to assess the relationship between muscle metrics. Results: In 99 patients, mean age was 56 (SD 13), BMI was 30 (SD 7), 47% were obese (≥30 kg/m2), and 54% had stage III breast cancer. Mean SMI was 45.3 (SD. 8.5), 26% were sarcopenic (SMI <40cm2/m2), mean SMD was 31.2 (SD 9.8), 77% had low SMD (HU <37.8), and mean SMG was 1413.8 (SD 71.2) [normal SMG is >1512 Arbitrary Units]. For each additional comorbidity, mean SMD decreased by 1.91 (p=.003), mean BSA increased by 0.035 (p=.02), and mean BMI increased by 1.31 (p=.005). Lower SMD and SMG were seen for patients with TUG >14 seconds (-5.70, p=.04 and -325.4, p=.02, respectively). The mean SMD increased by 1.22 (p=.02) for each additional point on the SPPB scale. For the correlation between BMI and muscle matrices, there was a strong positive correlation for SMI (+0.648 p<.0001) and a moderate negative correlation for SMD (-0.490 p<.0001). Between BSA and muscle matrices, there was a moderate positive correlation for SMI (+0.433 p<.0001), a strong negative correlation for SMD (-0.572 p <.0001), and a low negative correlation for SMG (-0.282 p=.004). Conclusion: Our study showed that sub-optimal muscle metrics, especially lower muscle mass and density, were correlated worse physical function in women with EBC. We also show that muscle metrics are associated with conventional measures of body composition. Citation Format: Gabriel F. P. Aleixo, Allison M Deal, Grant R Williams, Hyman B Muss, Kirsten A Nyrop, Ji Hye Park, Hyeon Yu, Shlomit S Shachar. Muscle measures, body composition, and function in patients with early breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-73.
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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 | 0.001 |
| 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) | 0.003 | 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".