Capacidad predictiva de las citoquinas en el fluido crevicular gingivalPara el diagnóstico de la periodontitis crónica

Abstract

There is currently no evidence on the possible predictive capacity of cytokines in gingival crevicular fluid (GCF) for the diagnosis and prognosis of periodontal diseases using appropriate multivariate predictive modeling techniques. Consequently, in the present study, the main objectives were: To obtain predictive models based on cytokine levels in the GCF that allow periodontal patients to be discriminated against from periodontally healthy individuals; To determine the cytokine thresholds in the GCF with diagnostic value of chronic periodontitis derived from the predictive models, specifying those for non-smoker and smoker patients. A sample of 150 participants, 75 periodontally healthy controls and 75 subjects affected by chronic periodontitis was recruited. Sixteen mediators were measured at GCF using the Luminex 100 instrument: GMCSF, IFNgamma, IL1alpha, IL1beta, IL2, IL3, IL4, IL5, IL6, IL10, IL12p40, IL12p70, IL13, IL17A, IL17F and TNFalpha. Cytokine based models were obtained by multivariate binary logistic regression. Models based on cytokine levels in the GCF were selected for their biological significance, their ability to predict chronic periodontitis and their statistical validity. In order to obtain the thresholds for cytokines with diagnostic value differentiated by “smoking habit”, it was then decided to develop specific predictive models for non-smoker and smoker patients. IL1alpha, IL1beta, and IL17A are biomarkers in GCF with excellent predictive ability to distinguish chronic periodontitis patients from periodontally healthy individuals. GCF cytokine thresholds with potential for diagnosis are established, with smokers showing lower values than those obtained in nonsmokers, which justifies the less intense inflammatory reaction of periodontitis associated with tobacco.