Effect of treatment sequence with radiotherapy and the antiestrogen EM 800 on the growth of ZR 75 1 human mammary carcinoma in nude mice
Bibliographic record
Abstract
We demonstrated previously that continuous administration of EM-800, a SERM having pure antiestrogenic activity in the mammary gland and endometrium in combination with monthly radiotherapy caused a greater inhibition of human ZR 75 1 tumor growth in nude mice than either therapy used alone. To further optimize therapy, we have now examined the effect of various treatment sequences to determine the optimal treatment regimen in the same model. EM 800 was given at the maximally effective oral dose of 300 microg daily. External beam radiation therapy (RTX) was carried out (2 Gy/tumor/day, 5 days per week for 3 weeks) for a total of 30 Gy/tumor delivered directly to the tumor while shielding the rest of the animal body. There was no evidence of RTX-related morbidity. Continuous treatment with EM 800 was initiated either 3 weeks before or at the same time as RTX, immediately after RTX, or 3 weeks before and immediately after RTX. After 156 days of treatment, EM 800 alone caused a 75% decrease in average tumor area, an effect equivalent to that achieved by ovariectomy. RTX alone, on the other hand, caused a transient 30% decrease in tumor area regardless of treatment sequence, whereas combined treatment with EM 800 and RTX was superior to either treatment alone. Combined treatment with EM 800 and RTX both started on Day 1 caused the greatest (88%), most rapid (50% in 2 weeks) and sustained decrease in tumor size. The present data indicate that optimal reduction in breast tumor size is achieved by continuous administration of EM 800 and RTX started simultaneously on Day 1.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".