BACKGROUND: Management of oral potentially malignant disorders (OPMDs) is still challenging. Despite the diagnostic ascertainment by bioptic examination, this method is poorly informative of the prognosis and subsequent malignant transformation. Prognosis is based on histological findings by grading of dysplasia. Immunohistochemical expression of p16(INK4a) has been investigated in different studies, with controversial results. In this scenario, we systematically revised the current evidence about p16(INK4)(a) immunohistochemical expression and the risk of malignization of OPMDs. MATERIAL AND METHODS: After a proper set of keywords combination, 5 databases were accessed and screened to select eligible studies. The protocol was previously registered on PROSPERO (Protocol ID: CRD42022355931). Data were obtained directly from the primary studies as a measure to determine the relationship between CDKN2A/P16(INK4a) expression and the malignant transformation of OPMDs. Heterogeneity and publication bias were investigated by different tools, such as Cochran's Q test, Galbraith plot and Egger and Begg Mazumdar's rank tests. RESULTS: Meta-analysis revealed a twofold increased risk to malignant development (RR = 2.01, 95% CI = 1.36-2.96 - I(2) = 0%). Subgroup analysis did not highlight any relevant heterogeneity. Galbraith plot showed that no individual study could be considered as an important outlier. CONCLUSION: Pooled analysis showed that p16(INK4a) assessment may arise adjunct tool to dysplasia grading, leading to an optimized determination of the potential progression to cancer of OPMDs. The p16(INK4a) overexpression analysis by immunohistochemistry techniques has a multitude of virtues that may facilitate its incorporation in the day-to-day prognostic study of OPMDs.
No clinical trial protocols linked to this paper
Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.PICO Elements
No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.
Paper Details
MeSH Terms
Associated Data
No associated datasets or code repositories found for this paper.
Related Papers
Related paper suggestions will be available in future updates.