Treatment and Follow-Up Strategies in Desmoid Tumours: A Practice Guideline
Bibliographic record
Abstract
OBJECTIVES: We set out to determine the optimal treatment options-surgery, radiation therapy (rt), systemic therapy, or any combinations thereof-for patients with desmoid tumours once the decision to undergo active treatment has been made (that is, monitoring and observation have been determined to be inadequate).provide clinical-expert consensus opinions on follow-up strategies in patients with desmoid tumours after primary interventional management. METHODS: This guideline was developed by Cancer Care Ontario's Program in Evidence-Based Care and the Sarcoma Disease Site Group. The medline, embase, and Cochrane Library databases, main guideline Web sites, and abstracts of relevant annual meetings (1990 to September 2012) were searched. Internal and external reviews were conducted, with final approval by the Program in Evidence-Based Care and the Sarcoma Disease Site Group. RECOMMENDATIONS TREATMENTS: Surgery with or without rt can be a reasonable treatment option for patients with desmoid tumours whose surgical morbidity is deemed to be low.The decision about whether rt should be offered in conjunction with surgery should be made by clinicians and patients after weighing the potential benefit of improved local control against the potential harms and toxicity associated with rt.Depending on individual patient preferences, systemic therapy alone or rt alone might also be reasonable treatment options, regardless of whether the desmoid umours are deemed to be resectable. RECOMMENDATIONS FOLLOW-UP STRATEGIES: Undergo evaluation for rehabilitation (occupational therapy or physical therapy, or both).Continue with rehabilitation until maximal function is achieved.Undergo history and physical examinations with appropriate imaging every 3-6 months for 2-3 years, and then annually.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".