COMPARING THE EFFECTS OF AROMATASE INHIBITORS AND SELECTIVE OESTROGEN RECEPTOR MODULATORS ON BODY COMPOSITION, EXERCISE TOLERANCE AND MARKERS OF CARDIOVASCULAR RISK IN FEMALES WITH BREAST CANCER
Bibliographic record
Abstract
INTRODUCTION Adjuvant endocrine therapy (AET) blocks the action of estrogens and is commonly prescribed in hormone receptor-positive breast cancer. Given the putative cardioprotective role of estrogens in females, AET may exacerbate the negative metabolic side-effects of anthracycline chemotherapy. This study examined the early effects of combined anthracycline chemotherapy and AET on body composition, exercise tolerance and markers of cardiovascular risk in a cohort of females with breast cancer. METHODS This was a secondary analysis of the BReast cancer EXercise InTervention (BREXIT) Trial. Females with breast cancer (n=105, aged 51 ± 8 years, BMI 27.4 ± 5.1, mean ± SD) scheduled for anthracycline chemotherapy participated in this study. Aerobic exercise capacity, body composition, physical function, and blood pressure were measured before anthracycline treatment and after 4- and 12-months follow-up. Linear mixed models assessed whether aromatase inhibitors (AI) or selective estrogen receptor modulators (SERMS) affected exercise tolerance, body composition and markers of cardiovascular risk compared to non-endocrine breast cancer treatments. RESULTS Twelve months of anthracycline treatment combined with AI or SERMs decreased total body lean mass by 1.4 kg (2%; interaction p=0.01) and 1kg (1%; interaction p=0.16) respectively, when compared to non-endocrine therapies. There were trends for AET to decrease total fat (-1.5%, interaction p=0.05) and android fat (-2.3%, interaction p=0.07) mass compared to non-endocrine therapy after 12 months. AIs significantly increased both systolic (5.8mmHg, interaction p=0.05) and diastolic (4.0mmHg, interaction p=0.05) blood pressure after 12 months of treatment compared to SERMs or non-endocrine therapies. There was no effect of either AET or SERMS on VO2peak, leg press or seated row 1RM, 30 second sit to stand or handgrip strength. DISCUSSION AND CONCLUSION Short-term treatment with adjuvant endocrine therapies may accelerate muscle loss and increase blood pressure compared to non-endocrine therapies. However, these changes were not associated with worsening of physical function.
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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) | 0.001 | 0.001 |
| 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".