• Mia Rakic, Natasa Pejcic, Neda Perunovic, and Danilo Vojvodic.
• ETEP (Etiology and Therapy of Periodontal Diseases) Research Group, Faculty of Dentistry, University Complutense of Madrid, Pza. Ramón y Cajal s/n, 28040 Madrid, Spain.
• Medicina (Kaunas). 2021 Mar 3; 57 (3).

AbstractPeriodontitis is among the most common health conditions and represents a major public health issue related to increasing prevalence and seriously negative socioeconomic impacts. Periodontitis-associated low-grade systemic inflammation and its pathological interplay with systemic conditions additionally raises awareness on the necessity for highly performant strategies for the prevention and management of periodontitis. Periodontal diagnosis is the backbone of a successful periodontal strategy, since prevention and treatment plans depend on the accuracy and precision of the respective diagnostics. Periodontal diagnostics is still founded on clinical and radiological parameters that provide limited therapeutic guidance due to the multifactorial complexity of periodontal pathology, which is why biomarkers have been introduced for the first time in the new classification of periodontal and peri-implant conditions as a first step towards precision periodontics. Since the driving forces of precision medicine are represented by biomarkers and machine learning algorithms, with the lack of periodontal markers validated for diagnostic use, the implementation of a precision medicine approach in periodontology remains in the very initial stage. This narrative review elaborates the unmet diagnostic needs in periodontal diagnostics, the concept of precision periodontics, periodontal biomarkers, and a roadmap toward the implementation of a precision medicine approach in periodontal practice.

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