Conservative Treatment of Campanacci Grade III Proximal Humerus Giant Cell Tumors
Bibliographic record
Abstract
UNLABELLED: Management of large giant cell tumors of the proximal humerus is controversial because wide resection with reconstruction results in a poor functional outcome for most patients. We retrospectively reviewed the cases of six patients with Campanacci Grade III giant cell tumors of the proximal humerus to determine the feasibility of avoiding en bloc resections for large giant cell tumors in this location. We evacuated the tumor through curettage and then used burring (unless the remaining cavity was thinned and at risk for fracture) and phenolization, followed by packing of the defect with allograft cancellous bone. The mean age of the patients at surgery was 30 years, and the minimum followup was 2.5 years (mean, 5.6 years; range, 2.5-9.7 years). One of the six patients had local recurrence 1.2 years postoperatively and was treated with repeat intralesional surgery with no additional recurrence 5 years later. No other patient required additional treatment, had pulmonary metastases develop, or had progression to osteoarthritis. The mean Musculoskeletal Tumor Society and Toronto Extremity Salvage Score functional scores at last followup were 26 of 30 (range, 21-30) and 95% (range, 90%-100%), respectively. These functional scores are higher than reported scores for patients with segmental resection and reconstruction of the proximal humerus. LEVEL OF EVIDENCE: Level IV, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".