Radiation therapy with concomitant and adjuvant cisplatin and paclitaxel in high-risk cervical cancer: long-term follow-up.
Bibliographic record
Abstract
INTRODUCTION: Chemo-potentiation of radiation improves survival in women with cervical cancer. Our group has previously demonstrated the tolerability of weekly paclitaxel combined with cisplatin during radiation therapy. We sought to determine the efficacy of this regimen in patients with "high risk" cervical cancer, and to determine the short- and long-term toxicity of this approach. METHODS: We prospectively enrolled surgically staged patients with positive peritoneal cytology, resectable nodal metastases, or primary tumor > 6 cm. Patients were treated using external beam radiation with concomitant cisplatin (50 mg/m2) during weeks 1, 4, and 7, and weekly paclitaxel (50 mg/m2), followed by four courses of adjuvant cisplatin (50 mg/m2) and paclitaxel (135 mg/m2). Toxicity, overall, and disease-free survival were evaluated. RESULTS: Twenty-three patients were enrolled, and 21 were evaluable. Patient allotment by FIGO stage was: IB1 - seven, IB2 - five, IIA - two, IIB - four, IIIB - two, IV - three. Twenty patients (95%) completed radiation treatment (median dose to point A was 8278 cGy). Seventeen patients (81%) completed all chemotherapy. At a median follow-up of 58 months the overall survival was 68%. Overall survival for patients with clinical Stage I and II disease was 82% at a median of 64 months. Hematologic toxicity was common but rarely resulted in treatment delays. Late complications requiring intervention (obstruction, fistula, significant lymphocyst) occurred in 11 patients (52%). CONCLUSION: The combination of paclitaxel and cisplatin appears efficacious in "high-risk" cervical cancer patients. Hematologic toxicity was common but tolerable. Long-term survival was common in these patients, however late toxicity was significant. This regimen should be investigated in collaborative phase III trials.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".