The Role of Denosumab in the Modern Treatment of Giant Cell Tumor of Bone
Bibliographic record
Abstract
➢ Giant cell tumor of bone (GCTB) is a benign, locally aggressive, osteolytic lesion. Typical treatment involves extended intralesional curettage or en bloc resection. ➢ Denosumab is a fully human monoclonal antibody with inhibitory effects on RANKL (receptor activator of nuclear factor-κB ligand) that has shown early promise as a possible treatment adjuvant for GCTB. ➢ Current clinical trials of denosumab for GCTB have shown >85% clinical, radiographic, and histological responses. ➢ Case reports have demonstrated complete response or tumor stabilization with denosumab, allowing for less invasive surgical procedures. Current indications for denosumab in GCTB include lesions in the spine, sacrum, pelvis, and challenging lesions in upper and lower-extremity locations. ➢ Denosumab may be a therapeutic option in patients with unresectable or metastatic GCTB, but optimal length and dosing of treatment and long-term effects are unknown. Most concerning, potential rates of rapid recurrence post-treatment or pseudo-sarcomatous transformation following treatment cessation are still uncertain.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".