Metastatic Giant Cell Tumor of Bone: A Case Report
Bibliographic record
Abstract
Giant cell tumor of bone is a relatively rare primary bone neoplasm. It was originally classified as benign tumor; however, it rarely presents as aggressive disease with the potential to distant metastasis mainly in lung. The objective of this study was to present and discuss a case of metastatic giant cell tumor. A young female patient with a recent history of resected bone lesion, hospitalized with dyspnea, was investigated and extensive lung metastasis was found. She received one cycle of chemotherapy until availability of molecular targeted therapy; however, she died due to disease complications 1 day after introduction of denosumab. This rare neoplasm is slightly predominant in females, typically occurring during the third or fourth decades of life, when bone maturity is reached. Accurate diagnosis is given by histopathological analysis. Microscopically the neoplasm is characterized by the presence of multinucleated giant cells of osteoclast type amid a richly vascular stroma of mononuclear cells. The standard treatment is curettage, filling with cement (polymethylmethacrylate) or bone graft. The possibility of recurrence is significant, and 15-50% of cases are treated with simple curettage. In cases where surgery is not possible, the systemic treatment can be attempted. The choice of the treatment regimen is based on case reports or series of cases. Recently a promising targeted therapy emerged, denosumab, a monoclonal antibody directed to the RANK ligand-L. In our case, besides the severity of the disease, inadequate follow-up after surgery and delayed access to specialized services may have contributed to the outcome. J Med Cases. 2014;5(11):557-560 doi: http://dx.doi.org/10.14740/jmc1947w
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.010 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".