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Review
. 2025 Jan 20;17(2):329.
doi: 10.3390/cancers17020329.

Predictive Value of the Loss of pRb Expression in the Malignant Transformation Risk of Oral Potentially Malignant Disorders: A Systematic Review and Meta-Analysis

Affiliations
Review

Predictive Value of the Loss of pRb Expression in the Malignant Transformation Risk of Oral Potentially Malignant Disorders: A Systematic Review and Meta-Analysis

María López-Ansio et al. Cancers (Basel). .

Abstract

Objective: The aim of this systematic review and meta-analysis was to qualitatively and quantitatively evaluate the current evidence on the significance of the loss of early stages of oral carcinogenesis in lesions diagnosed according to clinical and/or histopathological criteria and their evolution to oral cancer.

Materials and methods: We searched MEDLINE (through PubMed), Embase, Scopus and Web of Science for primary-level studies published before November 2024, designed as prospective or retrospective longitudinal cohorts, and not restricted by language or publication date. The risk of bias was critically assessed using the QUIPS tool. Meta-analyses, heterogeneity exploration, sensitivity and small-study effect analyses were conducted.

Results: The inclusion criteria were met by six primary-level studies, which recruited 330 patients with OPMDs with follow-up data. The loss of pRb expression, assessed through immunohistochemistry, was significantly associated with a higher malignant transformation risk of OPMDs (RR = 1.92, 95%CI = 1.25-2.94, p = 0.003). The leukoplakia subgroup retained this significant association (p = 0.006), being the OPMD where the loss of pRb expression showed the best predictive value for malignant transformation (RR = 2.00, 95%CI = 1.22-3.29). Regarding the immunohistochemical technique and scoring methods, better performance and results were achieved by applying a cutoff point > 10% pRb-positive cells with nuclear staining (RR = 2.10, 95%CI = 1.30-3.38, 95%CI = 0.002).

Conclussion: The present systematic review and meta-analysis supports that the loss of expression of the tumor suppressor pRb, assessed through immunohistochemistry, is a predictor of the malignant transformation risk of oral leukoplakias. Future studies are needed in other OPMDs following the recommendations provided based on current evidence gaps.

Keywords: malignant transformation; meta-analysis; oral cancer; oral leukoplakia; oral potentially malignant disorders; pRb; retinoblastoma protein; systematic review.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Flow diagram of the process of identification and selection of primary-level studies offering scientific information on the loss of pRb expression and oral potentially malignant disorders malignant transformation risk.
Figure 2
Figure 2
Quality plot graphically depicting the methodological quality and potential risk of bias across primary-level studies [38,39,40,41,42,43], critically verified by applying the QUIPS tool, developed by the Cochrane Prognosis Methods Group, which considers the following domains: (D1) study participation, (D2) study attrition, (D3) prognostic factor measurement, (D4) outcome measurement, (D5) study confounding, and (D6) statistical analysis and reporting. Risk of bias was qualified as low (green), moderate (yellow), or high (red) for each domain.
Figure 3
Figure 3
Forest plot graphically representing the meta-analysis on the association between the loss of pRb expression and malignant transformation. An RR > 1 suggests that the loss of pRb expression is associated with a higher malignant transformation risk. Diamonds indicate the pooled RR with their corresponding 95% CIs. Six primary-level studies were included in this meta-analysis [38,39,40,41,42,43]. RR, relative risk; CIs, confidence intervals; mt, malignant transformation; na, not applicable; DerSimonian and Laird, DL. Random-effect model, inverse-variance weighting based on the DL method; * Effect size was directly extracted and computed from multivariate regression analysis; ** Effect size was directly extracted and computed from univariate regression analysis.

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