Paclitaxel and Carboplatin, Alone or With Irradiation, in Advanced or Recurrent Endometrial Cancer: A Phase II Study
Bibliographic record
Abstract
PURPOSE: To evaluate the efficacy of carboplatin plus paclitaxel in primarily advanced or recurrent endometrial cancers. PATIENTS AND METHODS: Four distinct patient groups received carboplatin (area under the curve, 5 to 7) plus paclitaxel 175 mg/m(2) for 3 hours at 4-week intervals: group 1 (n = 21), patients with primarily advanced, nonpapillary serous cancers; group 2 (n = 20), the same as group 1 but with papillary serous cancers; group 3 (n = 18), recurrent, nonpapillary serous cancers; and group 4 (n = 4), recurrent, papillary serous cancers. Involved-field irradiation was used in groups 1 and 2 for those with radioencompassable disease. RESULTS: Sixty-three patients were treated. Response rates to chemotherapy in the assessable patients in the four groups were 78% (95% confidence interval [CI], 51% to 100%); 60% (95% CI, 35% to 85%), 56% (95% CI, 34% to 78%), and 50%, respectively. Nineteen patients (90%) in group 1 also were irradiated, and the median failure-free survival time for all 21 patients was 23 months, with a 62% 3-year overall survival rate. Eleven patients (55%) in group 2 were irradiated, and the median failure-free survival time for all 18 patients was 18 months, with a 39% 3-year overall survival rate. The median failure-free interval in the patients in group 3 was 6 months, with a 15-month median overall survival time. Toxicity was manageable, reversible, and predominantly hematologic. Two patients developed neutropenic fever, and three patients, including these two, were hospitalized for complications. CONCLUSION: Carboplatin-paclitaxel is an efficacious, low-toxicity regimen for managing primarily advanced or recurrent endometrial cancers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".