Ten recommendations for sarcoma surgery: consensus of the surgical societies based on the German S3 guideline “Adult Soft Tissue Sarcomas”
Bibliographic record
Abstract
PURPOSE: The evidence-based (S3) guideline "Adult Soft Tissue Sarcomas" (AWMF Registry No. 032/044OL) published by the German Guideline Program in Oncology (GGPO) covers all aspects of sarcoma treatment with 229 recommendations. Representatives of all medical specialties involved in sarcoma treatment contributed to the guideline. This paper compiles the most important recommendations for surgeons selected by delegates from the surgical societies. METHODS: A Delphi process was used. Delegates from the surgical societies involved in guideline process selected the 15 recommendations that were most important to them. Votes for similar recommendations were tallied. From the resulting ranked list, the 10 most frequently voted recommendations were selected and confirmed by consensus in the next step. RESULTS: The statement "Resection of primary soft tissue sarcomas of the extremities should be performed as a wide resection. The goal is an R0 resection" was selected as the most important term. The next highest ranked recommendations were the need for a preoperative biopsy, performing preoperative MRI imaging with contrast, and discussing all cases before surgery in a multidisciplinary sarcoma committee. CONCLUSION: The evidence-based guideline "Adult Soft Tissue Sarcomas" is a milestone to improve the care of sarcoma patients in Germany. The selection of the top ten recommendations by surgeons for surgeons has the potential to improve the dissemination and acceptance of the guideline and thus improve the overall outcome of sarcoma 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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".