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Prognostic nomogram for proliferative verrucous leukoplakia.

Yanning Zhang1,2, Xinning Zhang1,3, Zhiming Qin1,3

  • 1Department of Oral Pathology, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, PR China.

Journal of Dental Sciences
|January 28, 2025
PubMed
Summary
This summary is machine-generated.

This study developed accurate predictive models for proliferative verrucous leukoplakia (PVL) canceration risk and prognosis. These models aid in individualized clinical decisions for managing PVL and preventing oral squamous cell carcinoma (OSCC).

Keywords:
Early diagnosisNomogramPredictive modelPrognosisProliferative verrucous leukoplakia

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Area of Science:

  • Oral pathology
  • Oncology
  • Medical diagnostics

Background:

  • Proliferative verrucous leukoplakia (PVL) has a high malignant transformation rate into oral squamous cell carcinoma (OSCC).
  • Understanding PVL canceration risk and prognostic factors is crucial for effective management.
  • Current diagnostic and prognostic tools for PVL require enhancement.

Purpose of the Study:

  • To analyze canceration risk and prognostic factors of PVL.
  • To establish effective diagnostic and prognostic predictive models for PVL.
  • To improve clinical decision-making for PVL patients.

Main Methods:

  • Analysis of 467 patients, including 170 with PVL.
  • Univariable and multivariable logistic regression for risk and prognostic factor identification.
  • Construction and validation of nomogram models using ROC curves, calibration plots, and decision curve analysis.

Main Results:

  • Identified key risk factors for PVL canceration: sex, lesion site, clinical presentation, non-smoker status, and oral epithelial dysplasia (OED).
  • Identified independent prognostic factors: sex, clinical presentation, local irritants, and OED.
  • Developed accurate diagnostic and prognostic nomogram models with high predictive power (AUCs of 0.945 and 0.893).

Conclusions:

  • Established and validated nomogram models accurately predict PVL canceration risk and prognosis.
  • These models offer individualized clinical decisions, enhancing patient care.
  • The validated models demonstrate significant clinical utility in managing PVL.