Uterine Carcinosarcomas (Malignant Mixed Müllerian Tumours): A Review with Special Emphasis on the Controversies in Management
Bibliographic record
Abstract
Uterine carcinosarcomas (MMMT-malignant mixed Müllerian tumours) are highly aggressive, rare, biphasic tumours composed of epithelial and mesenchymal elements believed to arise from a monoclonal origin. While hysterectomy with bilateral salpingo-oophorectomy remains the mainstay treatment, high rates of recurrence and metastases suggest a need for lymphadenectomy and postoperative adjuvant treatment. There are no established consensus guidelines for therapeutic patient management. Though well recognized that it improves locoregional control, the role of radiation in improving overall survival outcomes remains undecided. Although various combinations of chemotherapy have been explored, an optimal therapeutic modality is yet to be determined. As overall survival rates have not improved in thirty years, it is suggested that targeted chemotherapy and/or a multimodality approach may yield better outcomes. This paper provides a summary of the aetiopathogenesis of carcinosarcomas (MMMT) limited to the uterus with special emphasis on the controversies in the management of these patients.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".