The effect of surgical synovectomy and radiotherapy on the rate of recurrence of pigmented villonodular synovitis of the knee
Bibliographic record
Abstract
Pigmented villonodular synovitis (PVNS) is a rare proliferative process of the synovium which most commonly affects the knee and occurs in either a localised (LPVNS) or a diffuse form (DPVNS). The effect of different methods of surgical synovectomy and adjuvant radiotherapy on the rate of recurrence is unclear. We conducted a systematic review and identified 35 observational studies in English which reported the use of surgical synovectomy to treat PVNS of the knee. A meta-analysis included 630 patients, 137 (21.8%) of whom had a recurrence after synovectomy. For patients with DPVNS, low-quality evidence found that the rate of recurrence was reduced by both open synovectomy (odds ration (OR) = 0.47; 95% CI 0.25 to 0.90; p = 0.024) and combined open and arthroscopic synovectomy (OR = 0.19, 95% CI = 0.06 to 0.58; p = 0.003) compared with arthroscopic surgery. Very low-quality evidence found that the rate of recurrence of DPVNS was reduced by peri-operative radiotherapy (OR = 0.31, 95% CI 0.14 to 0.70; p = 0.01). Very low-quality evidence suggested that the rate of recurrence of LPVNS was not related to the surgical approach. This meta-analysis suggests that open synovectomy or synovectomy combined with peri-operative radiotherapy for DPVNS is associated with a reduced rate of recurrence. Large long-term prospective multicentre observational studies, with a focus on both rate of recurrence and function, are required to confirm these findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.019 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".