Advancements in Predicting Periodontal Disease Evolution: A Narrative Review of Contemporary Clinical Risk Prediction Systems

Periodontal diseases are multifactorial chronic inflammatory disorders characterised by progressive destruction of the tooth-supporting apparatus. Predicting the evolution of these diseases remains a significant clinical challenge because microbial, host, behavioral, and systemic determinants interact to produce substantial inter-individual variability. In recent decades, periodontal care has transitioned from a reactive model toward a preventive, risk-oriented approach supported by structured prediction systems. Various clinical risk assessment tools, including the hexagonal periodontal risk assessment (PRA), modified PRA (MPRA), UniFe/PerioRisk, SmartRisk, DentoRisk, and the Periodontal Risk Calculator (PRC/PreViser), have been designed to quantify and visualise an individual's susceptibility to disease progression. These models integrate multiple parameters such as probing depth, bleeding on probing, bone loss, smoking, diabetes, and host-response markers to generate patient- or tooth-level prognoses. Recent developments have incorporated artificial intelligence-driven algorithms and real-time digital data capture to enhance predictive accuracy and facilitate personalised maintenance strategies. This narrative review critically analyses the evolution, structure, validation evidence, and clinical applicability of major periodontal risk prediction systems and explores future directions for integrating biological, behavioral, and digital determinants to achieve precision periodontics.