Efficacy of third-line chemotherapy for recurrent ovarian, peritoneal and fallopian tube carcinoma
Bibliographic record
Abstract
5136 Background: Various types of chemotherapy have been studied in patients with refractory/relapsing ovarian carcinoma. However there is very limited information regarding the usefulness of chemotherapy in ovarian cancer patients who have received several lines of treatment. Methods: All patients with ovarian epithelial, primary peritoneal or fallopian tube carcinoma who received at least three different types of chemotherapy in our institution were evaluated retrospectively. Those included in the analysis had to have received at least one platin-based regimen as their 1st line treatment and Topotecan as their 2nd line. The primary endpoint was response rate (RR). Responses were analysed according to the RECIST criteria for measurable disease, and the CA-125 criteria defined by the Gynecologic Cancer Intergroup (GCIG). Secondary endpoints were time to progression (TTP), disease stabilization, and overall survival (OS). Results: Fifty-two patients met our entry criteria. Ten (19.2%) had responded to Topotecan as their 2nd line treatment. Liposomal doxorubicin was the most often used third-line therapy (40.4%). The overall RR was 13.5% for third-line agent (1 CR and 6 PR). Median TTP was 50.7 weeks (95% CI 30 to 86 weeks) and disease stabilization was noted in 23% of patients with a median duration of 17.7 weeks. The median OS from the start of 3rd line therapy was 11.7 months (95% CI 7.7 to 15.3 months). It was significantly better for patients who responded to 3rd line treatment compared to non-responders (24.6 vs 7.3 months, p=0.0017). The only prognostic factor that strongly influenced the OS was the type of response to previous Topotecan (p = 0.0596) with a median OS from the start of 3rd line of 19.5 months for Topotecan responders compared to 10.3 months for the others. Conclusions: Disease response or stabilization occurs in about a third of patients receiving 3rd line treatment. The type of response to 2nd line therapy (Topotecan in this study) can help predict the responsiveness and perhaps usefulness of subsequent chemotherapy. This is the first study to show that median OS is significantly improved in responders compared to non-responders in women receiving 3rd line therapy for ovarian carcinoma. No significant financial relationships to disclose.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".