Exploring the use and efficacy of 5-fluorouracil in the management of odontogenic keratocysts: a systematic review and meta-analysis
Bibliographic record
Abstract
Odontogenic keratocyst (OKC) is a challenging jaw lesion known for its aggressive behavior and high recurrence rate. Concerns about the safety and effectiveness of existing adjuvant treatments have encouraged the search for safer alternatives such as 5-Fluorouracil (5-FU). This systematic review and meta-analysis evaluated the efficacy of 5-FU as an adjunctive therapy for OKC. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, a comprehensive search was conducted in PubMed, Embase, Scopus, and Google Scholar up to August 1, 2024. Eligible studies included OKC cases treated with 5-FU, alone or combined with surgery. Risk of bias was assessed using the Cochrane ROB-2 tool for randomized controlled trials and the Newcastle-Ottawa Scale for cohort studies. Data were pooled using inverse variance weighting, and heterogeneity was evaluated using the I² statistic. Fourteen studies (282 lesions) were included, comprising randomized controlled trials, cohort studies, and case reports of varying quality. Moderate heterogeneity was observed (I² = 37-57%). In five comparative studies, no recurrences occurred in the 5-FU group versus 24.21% in the modified Carnoy's solution (MCS) group (p < 0.001). Postoperative paresthesia as also lower with 5-FU (18.82% vs. 37.89%, p = 0.012). Compared with segmental resection, 5-FU achieved similar recurrence prevention but with much lower morbidity, including fewer permanent sensory deficits (9.09% temporary in 5-FU vs. 100% permanent in segmental resection, p < 0.001). Bone density was significantly higher after 5-FU treatment than with enucleation alone (p < 0.001). No systemic or severe local side effects were reported. 5-FU appears to be a highly promising adjunctive therapy for OKC, offering effective recurrence prevention with minimal morbidity However, current evidence remains limited by small sample sizes, study heterogeneity, and non-randomized designs. Larger, well-designed trials with long-term follow-up are needed to confirm these findings.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.041 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".