Immunotherapy in the treatment of chemoresistant gestational trophoblastic neoplasia - systematic review with a presentation of the first 4 Brazilian cases
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy of immunotherapy for GTN treatment after methotrexate-resistance or in cases of multiresistant disease, through a systematic review, as well as to present the first 4 Brazilian cases of immunotherapy for GTN treatment. METHODS: Three independent researchers searched five electronic databases (EMBASE, LILACS, Medline, CENTRAL and Web of Science), for relevant articles up to February/2023 (PROSPERO CRD42023401453). The quality assessment was performed using the Newcastle Ottawa scale for case series and case reports. The primary outcome of this study was the occurrence of complete remission. The presentation of the case reports was approved by the Institutional Review Board. RESULTS: Of the 4 cases presented, the first was a low-risk GTN with methotrexate resistance unsuccessfully treated with avelumab, which achieved remission with sequential multiagent chemotherapy. The remaining 3 cases were high-risk multiagent-resistant GTN that were successfully treated with pembrolizumab, among which there were two subsequent gestations, one of them with normal pregnancy and healthy conceptus. Regarding the systematic review, 12 studies were included, only one of them on avelumab, showing a 46.7% complete remission rate. The remaining 11 studies were on pembrolizumab, showing an 86.7% complete remission rate, regardless of tumor histology. Both immunotherapies showed good tolerability, with two healthy pregnancies being recorded: one after avelumb and another after pembrolizumab. CONCLUSION: Immunotherapy showed effectiveness for GTN treatment and may be especially useful in cases of high-risk disease, where pembrolizumab achieves a high therapeutic response, regardless of the histological type, and despite prior chemoresistance to multiple lines of treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".