Systematic review of adjuvant care for women with Stage I ovarian carcinoma
Bibliographic record
Abstract
BACKGROUND: Several adjuvant care interventions to treat women with Stage I ovarian carcinoma have been studied. The aim of the current systematic review was to determine the optimal strategy for adjuvant care for women with Stage I ovarian carcinoma. METHODS: A systematic search was conducted to find randomized controlled trials published between 1965 and April 2004 that examined adjuvant therapy (e.g., chemotherapy and radiotherapy) for women with Stage I ovarian carcinoma. RESULTS: Thirteen randomized controlled trials were identified that compared adjuvant therapies for women with Stage I ovarian carcinoma. Eight of these trials reported results only for patients with Stage I disease. The majority of patients in the five randomized trials that compared adjuvant chemotherapy with no chemotherapy did not receive lymphadenectomy as part of their surgical staging. The pooled results for Stage I patients indicated a survival benefit (relative risk [RR], 0.74; 95% confidence interval [CI], 0.58-0.94; P = 0.01), and a benefit in terms of a reduced risk of developing disease recurrence (RR, 0.70; 95% CI, 0.58-0.86; P = 0.0004) favoring adjuvant chemotherapy. Platinum-based adjuvant chemotherapy was reported to improve overall 5-year survival (absolute survival difference 8%; 95% CI, 2-12%; hazard ratio, 0.67; 95% CI, 0.50-0.90; P = 0.008). CONCLUSIONS: Adjuvant platinum-based chemotherapy for women with Stage I ovarian carcinoma improved survival and reduced the risk of recurrent disease. The optimally staged group accounted for approximately 10% of women with Stage I disease. The role of adjuvant chemotherapy in optimally staged patients (especially those with good prognostic factors) has not been assessed adequately.
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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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".