RT Journal Article
T1 Cytokine-based Predictive Models to Estimate the Probability of Chronic Periodontitis: Development of Diagnostic Nomograms
A1 Tomás Carmona, Inmaculada
A1 Arias Bujanda, Nora Adriana
A1 Alonso Sampedro, Manuela
A1 Casares de Cal, María de los Ángeles
A1 Sánchez Sellero, César
A1 Suárez Quintanilla, David
A1 Balsa Castro, Carlos
K1 Diagnostic markers
K1 Predictive markers
AB Although a distinct cytokine profile has been described in the gingival crevicular fluid (GCF) of patients with chronic periodontitis, there is no evidence of GCF cytokine-based predictive models being used to diagnose the disease. Our objectives were: to obtain GCF cytokine-based predictive models; and develop nomograms derived from them. A sample of 150 participants was recruited: 75 periodontally healthy controls and 75 subjects affected by chronic periodontitis. Sixteen mediators were measured in 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 using multivariate binary logistic regression. Models were selected for their ability to predict chronic periodontitis, considering the different role of the cytokines involved in the inflammatory process. The outstanding predictive accuracy of the resulting smoking-adjusted models showed that IL1alpha, IL1beta and IL17A in GCF are very good biomarkers for distinguishing patients with chronic periodontitis from periodontally healthy individuals. The predictive ability of these pro-inflammatory cytokines was increased by incorporating IFN gamma and IL10. The nomograms revealed the amount of periodontitis-associated imbalances between these cytokines with pro-inflammatory and anti-inflammatory effects in terms of a particular probability of having chronic periodontitis
PB Springer Nature
YR 2017
FD 2017-10-14
LK http://hdl.handle.net/10347/18401
UL http://hdl.handle.net/10347/18401
LA eng
NO Tomás, I., Arias-Bujanda, N., Alonso-Sampedro, M., Casares-de-Cal, M., Sánchez-Sellero, C., Suárez-Quintanilla, D., & Balsa-Castro, C. (2017). Cytokine-based Predictive Models to Estimate the Probability of Chronic Periodontitis: Development of Diagnostic Nomograms. Scientific Reports, 7(1). doi: 10.1038/s41598-017-06674-2
NO This work was supported by project EM2014/025 from Regional Ministry of Culture, Education and University (regional government of Galicia, Spain), which is integrated in Regional Plan of Research, Innovation and Development 2011–2015
DS Minerva
RD 26 abr 2026