Long-term consequences of ovarian ablation for premenopausal breast cancer.
Bibliographic record
Abstract
e11559 Background: According to the SOFT/TEXT trials, an aromatase inhibitor (AI) with ovarian ablation (OA) is associated with a higher 5-year disease-free survival than tamoxifen, with or without OA, in premenopausal women with ER+ early breast cancer. However, the long-term effects and costs of OA have not been evaluated. When OA is done by oophorectomy, there are long-term health consequences from premature menopause such as osteoporosis and coronary heart disease, which may occur many years later. The objective was to conduct a cost-effectiveness analysis comparing tamoxifen alone to OA with tamoxifen or OA with AI in premenopausal women. Methods: A Markov Monte Carlo simulation model estimated the costs and benefits of 3 adjuvant treatment strategies for ER+ early breast cancer in premenopausal women. Effectiveness was measured in average life expectancy gain (years), while costs were averaged over a lifetime (USD 2015). Primary outcome measure was the incremental cost-effectiveness ratio (ICER). Monte Carlo simulation estimated the number of adverse events and deaths from each strategy in the United States population over a time horizon of 40 years. Results: Tamoxifen alone for 5 years was more effective (18.18 years) and less costly ($2,838) than OA with tamoxifen (18.10 years, $12,869) or OA with an AI (17.48 years, $27,175). For 14,000 premenopausal ER+ women, the Monte Carlo simulation estimated 8,646, 8,989, and 9,643 deaths associated with tamoxifen, OA with tamoxifen, and OA with AI, respectively, including 1,966 and 1,866 deaths attributable to OA in the latter two groups. For high-risk women receiving chemotherapy, OA with tamoxifen was more costly but more effective (17.02 years, $12,380) than tamoxifen alone (16.09 years, $2,578) with an ICER of $10,537. OA with AI was less effective and more costly than OA with tamoxifen. Conclusions: Tamoxifen alone yields the highest life expectancy in premenopausal ER+ breast cancer. The risks of OA outweigh the benefits; however, there may be a role for OA in high-risk women.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".