Evaluating Extended Curettage and Adjuvant Therapy Against Wide Resection and Reconstruction in the Management of Distal Radius Giant Cell Tumors: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: The management of distal radius giant cell tumors (GCTs) remains challenging, and the optimal approach is still a matter of debate. This systematic review and meta-analysis aimed to compare the outcomes of extended curettage and wide resection, the mainstays of treatment. Methods: Medline (via PubMed), Cochrane Library, Web of Science, Google Scholar, ClinicalTrials.gov, and Embase databases were searched for comparative studies that assessed extended curettage with adjuvant therapy and wide resection with reconstruction in patients with GCTs of the distal radius up to April 2023. Data were collected and analyzed on rates of local recurrence, metastasis, overall complications, and functional outcomes. The Newcastle-Ottawa scale was used to appraise the risk of bias within each study. Results: Fifteen studies (n = 373 patients) were included and analyzed. Patients who underwent curettage were more likely to develop recurrence (risk ratio [RR] = 3.02 [95% confidence interval; CI, 1.87-4.89], P < .01), showed fewer complications (RR = 0.32 [95% CI, 0.21-0.49], P < .01), and showed greater improvement in Visual Analog Scale and lower Disabilities of the Arm, Shoulder, and Hand scores ( P < .00001) than those who underwent wide resection. No significant difference was found regarding metastasis (RR = 1.03 [95% CI, 0.38-2.78], P = .95). Conclusions: Regarding the surgical approach to GCT of the distal radius, curettage with adjuvant therapy was associated with a higher likelihood of recurrence compared with wide resection with reconstruction. Nevertheless, the curettage approach resulted in significantly lower rates of operative complications, decreased pain scores, and better functional outcomes in comparison to the resection group.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.038 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".