Long‐term outcome of the treatment of high‐risk tenosynovial giant cell tumor/pigmented villonodular synovitis with radiotherapy and surgery
Bibliographic record
Abstract
BACKGROUND: The treatment of diffuse tenosynovial giant cell tumor (TGCT) requires extensive surgical resection of the hypertrophic synovium and multiple soft tissue masses yet still may result in high rates of local failure. The authors of this report examined their experience in treating patients with advanced/multiply recurrent TGCT with a combination of surgery and external-beam radiotherapy. METHODS: Fifty patients who were treated for TGCT with radiotherapy and surgery from 1972 to 2006 were identified. Patient demographics, radiotherapy treatment parameters, surgical treatment, and oncologic and functional outcomes were evaluated. All patients had pathologic review at presentation and required at least 1 year follow-up. RESULTS: Forty-nine patients had diffuse TGCT with both intra-articular and extra-articular disease (1 had malignant TGCT). Twenty-eight patients (56%) were referred after at least 1 local recurrence. Thirty patients (60%) underwent at least 2 operations before radiotherapy. The mean dose of radiation delivered was 39.8 gray. At a mean follow-up of 94 months (range, 19-330 months), 47 patients (94%) had not developed a recurrence or had stable disease/signal characteristics on serial cross-sectional imaging (for those patients who had gross residual disease at the time of radiotherapy). Two patients required subsequent total hip arthroplasty because of progressive osteoarthritis, and there were 4 cases of avascular necrosis (only 1 post-treatment). Forty-one patients had good/excellent function. CONCLUSIONS: For patients with extensive or multiple local relapses or when surgery alone would result in a large burden of residual disease or major functional loss, the addition of moderate-dose adjuvant radiotherapy provided excellent local control while maintaining good function with low treatment-related morbidity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".