Objective Response to Chemotherapy As a Potential Surrogate End Point of Survival in Metastatic Breast Cancer Patients
Bibliographic record
Abstract
PURPOSE: To assess the validity of objective response to chemotherapy as a surrogate end point for survival in metastatic breast cancer. PATIENTS AND METHODS: We carried out a meta-analysis on individual data from 2,126 metastatic breast cancer patients who were enrolled onto 10 randomized trials comparing standard versus intensified epirubicin-containing chemotherapy. RESULTS: The intensified chemotherapy was associated with a significantly higher tumor response rate compared with standard chemotherapy (pooled odds ratio for nonresponse, 0.60; 95% CI, 0.51 to 0.72). The intensified regimens also led to better (although not significant) survival (pooled odds ratio, 0.94; 95% CI, 0.86 to 1.04; P = .22). Tumor response was a highly significant predictor of survival (P < .0001). When tumor response was introduced in the Cox model, the hazard ratio in favor of experimental treatment changed from 0.94 to 1.005 (95% CI, 0.91 to 1.11; P = .92), indicating that no residual effect of the experimental treatment on survival was present once tumor response was adjusted for. This suggests that the overall survival benefit of intensified epirubicin was a result of the increase in response rate. The median survival time of patients with complete response and partial response was 28.8 months (95% CI, 25.4 to 45.3 months) and 21.3 months (95% CI, 19.2 to 22.4 months), respectively; whereas, the median survival time of patients with no response was 14.6 months (95% CI, 13.9 to 15.4 months). CONCLUSION: These results support the hypothesis that the achievement of an objective response to chemotherapy in metastatic breast cancer is associated with a true survival benefit. The potential role of objective response as a surrogate end point for survival in chemotherapy trials of metastatic breast cancer warrants further investigation.
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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 | 0.034 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".