A Systematic Review and Meta-Analysis of En-Bloc vs Intralesional Resection for Giant Cell Tumor of Bone of the Distal Radius
Bibliographic record
Abstract
INTRODUCTION: Surgical management of Giant Cell Tumor of Bone of the distal radius (GCTDR) remains controversial due to risk of local recurrence (LR) offset by functional limitations which result from en-bloc resection. This study aims to determine the oncologic and functional outcomes of wide excision (WE) vs intralesional curettage (IC) of GCTDR. METHODS: A complete search of the applicable literature was done. Included studies reported on patients from the same cohort who were surgically treated for GCTDR with WE or IC. Two reviewers independently assessed all papers. The primary outcome measure was LR. RESULTS: One-hundred-forty-one patients from six studies were included: 60 treated with WE, and 81 with IC. Five WE patients (8%) suffered LR whereas 25 IC patients (31%) did. The odds of LR were three times less in the WE group vs the IC group. MSTS1993 scores, where available, were on average 'good' with WE and 'excellent' with IC. CONCLUSIONS: Within statistical limitations the data support an attempt, where feasible, at wrist joint preservation and superior function with IC. Intralesional curettage is reasonable when the functional benefit outweighs the risk of recurrence as is the case in many cases of GCT of the distal radius.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.017 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".