Local control of extra-abdominal desmoid tumors: systematic review and meta-analysis
Bibliographic record
Abstract
The local control of desmoid tumors constitutes a continuing treatment dilemma due to its high recurrence rates. The purpose of this systematic review was to critically examine the current treatment of these rare tumors and to specifically evaluate the local failure and response rates of surgery, radiation and systemic therapy. We comprehensively searched the literature for relevant studies across Cinahl, Embase, Medline and the Cochrane databases. Articles were categorized as surgery, radiation, surgery + radiation and systemic therapy (including cytotoxic and non cytotoxic). Methodological quality of included studies was assessed using the Newcastle-Ottawa Scale. Pooled odd ratios (OR) for comparative studies and weighted proportions with 95% confidence intervals (CI) are reported. Thirty-five articles were included in the final analysis. Weighted mean local failure rates were 22% [95% CI (16-28%)], 35% [95% CI (26-44%)] and 28% [95% CI (18-39%)] for radiation alone, surgery alone and surgery + radiation respectively. In the analysis of comparative studies, surgery and radiation in combination had lower local failure rates than radiation alone [OR 0.7 (0.4, 1.2)] and surgery alone [OR 0.7 (0.4, 1.0)]. Weighted mean stable disease rates were 91% [95% CI (85-96%)] and 52% [95% CI (38-65%)] for non cytotoxic and cytotoxic chemotherapy respectively. The current evidence suggests that surgery alone has a consistently high rate of local recurrence in managing extra-abdominal desmoid tumors. Radiation therapy in combination with surgery improves local control rates. However, the limited data on systemic therapy for this rare tumor suggests the benefit of using both cytotoxic and non cytotoxic chemotherapy to achieve stable disease.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.027 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".