Differential Expression of Immunohistochemical Markers in Ameloblastoma & Ameloblastic Carcinoma: A Systematic Review and Meta-analysis of observational studies
Bibliographic record
Abstract
Background: Differentiating between ameloblastoma (AB) and ameloblastic carcinoma (AC) is difficult, especially when AB has atypical cytological characteristics or an uncommon clinical history. This systematic review and meta-analysis aimed to elucidate the differential expression of immunohistochemical markers between AB and AC. Methods: We conducted a thorough search of PUBMED and SCOPUS according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify cross-sectional studies that compared the expression of immunohistochemical markers in AB and AC. We used a random-effects model to analyze the risk ratios and their corresponding 95% confidence intervals (CIs). The quality of the included studies was assessed using the Newcastle-Ottawa scale. The Egger's test was used to assess publication bias. Results: In total, 301 articles were identified. After excluding irrelevant titles and abstracts, 86 articles were selected for full-text review. We categorized the 41 markers into proliferative and non-proliferative markers. Among non-proliferative markers, nuclear markers were differentially expressed in AB and AC. SOX2 was the only marker that significantly differentiated AB and AC, with an RR of -0.19 (CI 0.10-0.36, I2=0). Conclusion: The current evidence suggests the significance of SOX2 in differentiating between AB and AC, warranting prospective confirmation in well-defined extensive studies. We highlight the paucity of high-quality replicated studies of other markers in this field. Collaborative efforts with standardized techniques are necessary to generate clinically useful immunohistochemical markers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".