The Curative Effect of a Second Curettage in Low-Risk Gestational Trophoblastic Neoplasia
Bibliographic record
Abstract
Background: Gestational trophoblastic neoplasia (GTN), despite its widespread metastases, is a very common cancer in women that is curable. Although the GTN cases show a good response to chemotherapy, in an effort to reduce toxic drug exposure, the second curettage has been suggested for some patients. In the current study, we have aimed to compare the benefits of the second curettage in comparison with single-agent chemotherapy for low-risk GTN patients. Methods: This retrospective observational study was carried out on GTN patients admitted to the gynecology department of Imam Khomeini Hospital in Ahvaz. The demographic profile of all participants was extracted. Patients' hospitalization records were also extracted from the files. Patients with an endometrial thickness above 10 mm were treated with re-curettage. The β hCG clearance time was estimated by the Kaplan Meier plot. Results: In the present study, 148 patients with low-risk GTN stage 1 were studied. The time required for β-hCG clearance in patients undergoing re-curettage was significantly lower than the chemotherapy receiving group (7 months vs. 10 months, p <0.0001). More than 50% of patients treated by re- curettage without needing chemotherapy. Moreover, the other 50% cases needed chemotherapy the number of courses was significantly lower than those received single-agent chemotherapy alone (p <0.0001). The baseline β-hCG levels were significantly lower in those who did not need chemotherapy (p = 0.012). β-hCG resolution occurred more rapidly in patients undergoing re-curettage alone, while, those who received only chemotherapy had a longer duration for β-hCG clearance. Conclusion: In general, the findings of this study showed that re-curettage could be used effectively in the treatment of GTN following molar pregnancy. This treatment reduces or eliminates the need for chemotherapy. Our findings also showed that the initial level of β-hCG could be considered as a predictive factor in response to curettage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".