Strategies for managing EMA/CO resistant in gestational trophoblastic neoplasia a systematic review and meta analysis
Bibliographic record
Abstract
OBJECTIVE: This systematic review and meta-analysis evaluate the efficacy and safety of salvage regimens in managing EMA/CO-resistant GTN, providing evidence to inform optimal treatment strategies. METHODS: A literature search was conducted in PubMed, ScienceDirect, Cochrane Library, Google Scholar, and Wiley Online Library until December 27, 2024. Studies on EMA/CO chemoresistance in gestational trophoblastic neoplasia (GTN) were included, and alternative regimens and surgical interventions were also considered. Exclusion applied to non-human studies and those unrelated to EMA/CO chemoresistance. Data extraction and quality assessment followed PRISMA, Cochrane ROB-2, and the Newcastle-Ottawa Scale. A meta-analysis was performed using a random-effects model, with heterogeneity (I²) and publication bias assessed. The study was registered with PROSPERO (CRD42024574582). RESULTS: Eight studies met the inclusion criteria, encompassing patients predominantly with advanced-stage (FIGO III-IV) and high-risk GTN. EMA/EP and EP/EMA were the most frequently evaluated salvage regimens, with a pooled complete remission rate of 78.7% (95% CI: 67.4–88.1%) across 84 patients. No significant heterogeneity (I² = 27.05%) or publication bias was detected. Alternative regimens, including BEP, FAEV, and TP/TE, demonstrated favourable remission rates in small cohorts but lacked generalizability. Neutropenia (68%), thrombocytopenia (41%), and anaemia (30%) were the most commonly reported toxicities with EP/EMA. Safety data for other regimens were limited. CONCLUSION: EMA/EP and EP/EMA remain the most effective and well-studied salvage regimens for EMA/CO-resistant GTN, demonstrating high remission rates with manageable toxicity. While alternative regimens such as BEP, FAEV, and TP/TE show encouraging results, their limited evidence base precludes definitive comparison. Further prospective studies are needed to establish optimal salvage strategies and refine toxicity management.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".