Controversies in the Management of Endometrial Cancer
Bibliographic record
Abstract
Endometrial cancer is the most common gynecologic malignancy among women in developed countries. Most are diagnosed at stage I and their probability of surviving the disease is excellent. Most women at diagnosis are older, obese, and have multiple comorbidities. These factors need to be considered when treating patients with this highly curable disease. When recurrences occur at the vaginal apex, almost 50% are salvaged with radiation therapy with or without surgical excision. However, treatment of nodal or distant recurrences or of advanced disease at diagnosis is more challenging. One of the challenges faced by those treating this disease is how to identify those women who are at risk of having occult metastatic disease at initial diagnosis and to provide effective adjuvant therapy that would prevent recurrences in this select group of patients while minimizing therapy-induced morbidity. In this special issue on endometrial cancer, the authors tackle some of these issues. The articles accurately and succinctly summarize the current approach to the treatment of this disease and looks at the future by discussing possible novel interventions for the treatment of advanced or recurrent disease. The controversies in the surgical management of endometrial cancer are discussed, as are the minimally invasive surgical techniques. The international group of authors and editors provide a worldwide perspective about areas of agreement, topics of controversies, and issues that need yet to be clearly defined. Authors from The Netherlands discuss the controversies in evaluating women with postmenopausal bleeding. They weight the convenience, but possible decreased accuracy, of transvaginal ultrasound against the invasiveness of endometrial biopsy, hysteroscopy, and DC Utrecht, The Netherlands; and the University of Florence, Italy discuss possible novel approaches to the treatment of advanced or recurrent endometrial adenocarcinoma. And finally, authors from Greece and the United Kingdom summarize the evidence for adjuvant and molecularly targeted therapy of endometrial cancer. In this special issue of Obstetrics and Gynecology International, the reader will conveniently find a comprehensive summary of the state-of-the-art diagnostic strategies, biology, and evidence-based treatment of endometrial cancer from an international perspective. Enrique Hernandez Andreas Obermair Paul J. Hoskins Javier F. Magrina Robert Mclellan
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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 | 0.015 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".