Correlation Between Anthropometric Measures and Biomarker Changes After Neoadjuvant Therapy With Tamoxifen or Anastrozole in Postmenopausal Women With Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Epidemiological studies have reported positive associations between anthropometric measures and risk for developing breast cancers that express hormone receptors and associated mortality. However, the impact of nutritional status on the molecular response to endocrine therapy has yet to be described. METHODS: Body mass index (BMI), waist circumference (WC), hip circumference (HP), and waist-to-hip ratio (WHR) were measured in patients with invasive ductal carcinoma (IDC) before and after neoadjuvant treatment with either tamoxifen or anastrozole, and a possible correlation with prognostic factors, as estrogen receptor (ER), progesterone receptor (PgR), and proliferative index (Ki-67), was analyzed. Fifty-seven patients with palpable ER-positive IDC were randomized into three neoadjuvant treatment groups and received anastrozole or placebo or tamoxifen for twenty-one days. Biomarker status was obtained by comparing the immunohistochemical evaluation of samples collected before and after treatment, using the Allred scoring system. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS). RESULTS AND CONCLUSIONS: After treatment, the anastrozole group showed reduced ER and PgR expression (p < 0.05), and both the anastrozole and tamoxifen groups showed lower Ki-67 status. A significant reduction in PgR positivity (p < 0.05) was found in women with large WC and HC who were treated with anastrozole. Reduction in PgR positivity also tended to be associated with BMI (p = 0.09) in the anastrozole group. BMI, WC, HC and WHR correlated neither with biomarker levels in the tamoxifen and placebo groups nor with ER and Ki-67 status in the anastrozole group after primary endocrine treatment.
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.
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".