Chemotherapy (Gemcitabine, Docetaxel Plus Gemcitabine, Doxorubicin, or Trabectedin) in Inoperable, Locally Advanced, Recurrent, or Metastatic Uterine Leiomyosarcoma: A Clinical Practice Guideline
Bibliographic record
Abstract
QUESTIONS: Does chemotherapy-that is, gemcitabine, gemcitabine plus docetaxel, doxorubicin, or trabectedin-improve clinical outcomes in women with inoperable, locally advanced, recurrent, or metastatic uterine leiomyosarcoma (lms)? Is there a difference in the tumour response rate to chemotherapy between recurrent pelvic disease and extrapelvic metastases in the target patients? METHODS: This guideline was developed by Cancer Care Ontario's Program in Evidence-Based Care, the Sarcoma Disease Site Group (dsg), and the Gynecologic Cancer dsg. The core methodology was the systematic review. The medline and embase databases (2004 to June 2011), the Cochrane Library, main guideline Web sites, and relevant annual meeting abstracts (2005-2010) were searched. Internal and external reviews were conducted, with final approval by the dsgs and the Program in Evidence-Based Care. CLINICAL PRACTICE GUIDELINE: Based on currently available evidence from the medical literature (four single-arm phase ii studies, one arm of a randomized controlled trial, and one abstract), doxorubicin alone, gemcitabine alone, or gemcitabine plus docetaxel may be treatment options in first- or second-line therapy (or both) for women with inoperable, locally advanced, recurrent, or metastatic uterine lms. Hematologic toxicity is common and should be monitored, and granulocyte colony-stimulating factor should be considered when gemcitabine plus docetaxel is used. Other toxicities, such as neurotoxicity, pulmonary toxicity, and cardiovascular toxicity should be monitored. No recommendation is made for or against the use of trabectedin in the targeted patients. No data were available concerning differences in response in recurrent pelvic disease or extrapelvic metastases, or concerning quality of life.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".