Local recurrence of giant cell tumour of bone after intralesional treatment with and without adjuvant therapy, a single institution case series.
Bibliographic record
Abstract
BACKGROUND: Giant cell tumour (GCT) of bone is generally a benign tumour composed of mononuclear stromal cells and characteristic multinucleated giant cells that exhibit osteoclastic activity. It usually develops in long bones but can occur in unusual locations. The typical appearance is a lytic lesion with a well-defined but non-sclerotic margin that is eccentric in location, extends near the articular surface, and occurs in patients with closed physes. OBJECTIVE: The current study was planned to summarise our experiences with GCTB, and to evaluate individual effect of bone cement, high-speed burring and hydrogen per oxide (H2O2) on local recurrence. GCT can mimic or be mimicked by other benign or malignant lesions at both radiological evaluation and histological analysis. In the past, the mainstay of treatment was surgical, primarily consisting of curettage with cement placement, with recurrence rates of 15%-25%. Recurrence is suggested by development of progressive lucency at the cement-bone interface. RESULTS: Of the 21 patients who started the study, 4(19%) were lost to follow-up, and 17(81%) represented the final study sample. Of them, 16(94.11%) patients underwent the curettage procedure with adjuvant therapy and reconstruction with bone grafts taken from iliac crest. In 3(26.3%) patients, no adjuvant was used. Total of 6 (42.1%) patients had local recurrence and 3(50%) of them were those who were treated without any adjuvant; 2(33.3%) with phenol and 1(16.6%) with PMMA. CONCLUSIONS: The results of the present study suggest that an "aggressive curettage" with the use of adjuvant reduces the recurrence rate in a disease whose aggressiveness is not easy to predict.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".