Updated Guidelines for the Diagnosis and Treatment of Endometrial Carcinoma: The Polish Society of Gynecological Oncology (2025v)
Bibliographic record
Abstract
In 2023, the Polish Society of Gynecologic Oncology (PSGO) published clinical recommendations for the diagnosis, treatment, and care of women with endometrial cancer (EC), developed using the AGREE II (Appraisal of Guidelines for Research and Evaluation) tool. A 2025 update was initiated in response to new evidence, particularly regarding systemic therapies for metastatic, advanced, or recurrent EC, and the introduction of an updated FIGO classification. A targeted literature review identified relevant phase III clinical trials and systematic reviews, including RUBY, GY-018, AtTend, and DUO-E. These trials were critically assessed by an Expert Panel in accordance with the AGREE II methodology. Updated recommendations were formulated based on this evidence, with a comparative analysis of the old and new FIGO staging systems and visual updates to treatment pathways. Key changes include the addition of immunotherapy (I/O) plus chemotherapy (CHTH) as first-line treatment for all molecular subtypes of high-grade endometrioid and non-endometrioid carcinomas, replacing chemotherapy alone. For MMRp-positive cases, the 2025 version introduces the use of Olaparib alongside Durvalumab and CHTH. HER2-positive MMRp serous carcinoma remains eligible for trastuzumab in combination with CHTH. Second-line treatment guidance remains unchanged for patients who did not receive I/O plus CHTH initially. However, options for those previously treated with this combination are still under evaluation. This update ensures alignment with the latest international standards and reinforces evidence-based, personalized care for EC patients.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.010 |
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".