Bibliographic record
Abstract
Desmoid tumors are benign fibrous neoplasms originating from the musculoaponeurotic structures throughout the body. These rare neoplasms have been shown to account in 0.03% of all cancers. Twenty-five percent of all desmoid tumors occur in children under 15 years of age. The infrequency of these tumors has limited studies to case reports and retrospective reviews dictating the authors recommended treatments and management. We present a case report of desmoid tumor involving the left mandible in a 14-month-old infant. His treatment course included 2 excisions, removal of the free rib graft secondary to persistence of the tumor, and wound dehiscence, and later a free fibular osteomyocutaneous flap for reconstruction. We then retrospectively reviewed all published data of desmoid tumor involving the pediatric mandible since 1950 to 2007 in the PubMed database. Forty cases have been reported, which had a M:F ratio of 1:1 with an average age of 5.3 (standard deviation [SD] +/- 4.5) years. There appeared to be left-sided predominance of desmoid tumors in the pediatric mandible with a ratio of 3:1. The mean size of the tumors was 4.6 cm (SD +/- 2.1) at the largest diameter. We have tabulated the relevant data of all the cases including the methods of treatment and recurrence. It is found that when compared with conservative management, radiation therapy, chemotherapy, and curettage or surgical local excisions as treatment options the most efficient treatment was partial mandiblectomy, which resulted in complete tumor dissipation with no tumor recurrence. In summary, this is the largest review of the pediatric desmoid tumor of the mandible to date where we provide for the first time an algorithm for the management and treatment of the pediatric desmoid tumor of the mandible.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".