Topoisomerase-IIα expression as a predictive marker in a population of advanced breast cancer patients randomly treated either with single-agent doxorubicin or single-agent docetaxel
Bibliographic record
Abstract
Abstract Purpose: The predictive value of topoisomerase-IIα (topo-II) has been evaluated in advanced breast cancer patients randomly treated with single-agent doxorubicin or docetaxel. Experimental design: Primary tumor samples from patients enrolled in a randomized, phase III clinical trial comparing single-agent doxorubicin (75 mg/m2 q3wks) with docetaxel (100 mg/m2 q3wks) were collected and topo-II status was evaluated by immunohistochemistry (clone KiS1). Results: Topo-II status was evaluated in 108 samples, 55 (51%) in the doxorubicin arm and 53 (49%) in the docetaxel arm. An increment of 10% in cells expressing topo-II is associated with a statistically significant odds ratio (OR; 95% confidence interval) of 1.09 (1.03–1.15; P = 0.002) for overall response to doxorubicin versus 1.002 (0.94–1.07; P = 0.95) in the docetaxel arm. With increasing topo-II, the favorable OR for overall response to docetaxel compared with doxorubicin decreases to become not significant in patients with topo-II tumor content >10%. In a multivariate analysis, (a) HER-2 status seems positively correlated with overall response to chemotherapy (OR, 2.34; 95% confidence interval, 0.87–6.27; P = 0.09). (b) Overall response to doxorubicin is significantly lower than overall response to docetaxel (OR, 0.17; 95% confidence interval, 0.04–0.64; P = 0.009) but with a significant interaction term for doxorubicin-treated patients with topo-II tumor content >10% (OR, 8.31; 95% confidence interval, 1.86–37.03; P = 0.05). Conclusions: (a) Topo-II overexpression confers a higher probability of response in the doxorubicin arm only. (b) Despite being a small retrospective study, this study is in line with previously reported studies and the hypotheses raised are now being tested in a prospective neoadjuvant trial.
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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 | 0.002 |
| 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 | 0.001 |
| 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".