Iterative Curettage is Associated with Local Control in Giant Cell Tumors Involving the Distal Tibia
Bibliographic record
Abstract
BACKGROUND: The distal tibia is an unusual location for a giant cell tumor (GCT). Treatment choices are unclear because of their rarity, the anatomy of the ankle, and difficulties associated with reconstruction. QUESTIONS/PURPOSES: We assessed: (1) the treatment modalities used by participating Canadian bone tumor centers for distal tibia GCTs; (2) the incidence of local recurrence and their management; and (3) patients' function after treatment. METHODS: A prospective tumor database served to identify all 31 patients with primarily treated distal tibia GCTs between 1991 and 2010. We extracted patients and tumor characteristics, treatment modalities for initial and recurrent tumors, and the Musculoskeletal Tumor Society (MSTS) and Toronto Extremity Salvage (TESS) scores. The median followup was 58 months (range, 24-192 months). RESULTS: Extended curettage was the only modality of treatment for all patients including all subsequent local recurrences. Nine had local recurrence, three of which had a second local recurrence; one had a third recurrence. Ultimately all patients were in remission at last followup. The local recurrence rate was 29% and appeared higher compared with recent series of all anatomic sites. The mean final MSTS and TESS scores were 91% (range, 71%-100%) and 88% (range, 35%-100%), respectively. CONCLUSIONS: Extended curettage was the unique modality of surgical treatment for all tumors. We found the incidence of local recurrence higher than that reported for other locations but recurrences were manageable with repeated curettage. Complications and function appeared better than those reported for series of ankle fusion or reconstruction for bone tumors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".