Body composition metrics as a determinant of trastuzumab deruxtecan related toxicity and response
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
Body composition is an important predictor in cancer patients, with skeletal muscle loss and high adiposity associated with poorer prognosis. This study evaluated how body composition affects treatment efficacy in 48 women with metastatic breast cancer receiving trastuzumab deruxtecan. Using computed tomography, skeletal muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were assessed within 60 days before initiating treatment. High SAT and VAT areas were significantly associated with a higher likelihood of dose reductions (Odds Ratio [OR] = 5.34, p = .032 and OR = 5.52, p = 0.032, respectively). Higher SAT areas correlated with a lower objective response rate (OR = 0.22, p = 0.047). Medium SAT and low/medium VAT densities increased the risk of dose reductions. A body mass index over 25 kg/m 2 was linked to higher dose reductions (OR = 4.97, p = 0.016). These findings emphasize the need for personalized treatment strategies based on body composition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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