ArticleJournal of dental sciences2025
Prognostic nomogram for proliferative verrucous leukoplakia.
Article in Journal of dental sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Proliferative verrucous leukoplakia (PVL) is a special type of leukoplakia characterized by high rate of malignant transformation into oral squamous cell carcinoma (OSCC). This study aimed to analyze the canceration risk and prognostic factors of PVL and establish effective diagnostic and prognostic predictive models. Materials and methods: A total of 467 patients were enrolled, including 170 cases of PVL. The independent risk and prognostic factors of PVL were analyzed by univariable and multivariable logistic regression. Nomogram models were constructed to predict the canceration risk and prognosis of PVL. The predictive power was evaluated by Hosmer-Lemeshow test, receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis. Results: Multivariable logistic regression analyses identified that canceration risk factors of PVL included sex, lesion sites, clinical presentation, non-smoker and oral epithelial dysplasia (OED). The independent prognostic factors of PVL were sex, clinical presentation, local irritants and OED. Diagnosis and prognostic nomogram models were constructed. The areas under the ROC curve were 0.945 and 0.893, respectively. The calibration plots showed strong agreement between the prediction and observation. Decision curve analysis indicated that the models provided significant clinical benefits for patients. Conclusion: Our study established and validated the diagnosis and prognostic predictive nomogram models, which were accurate to predict the canceration risk and prognostic factors of PVL, providing individualized clinical decisions for clinical work.
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