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Evaluation of Salivary Biomarkers for the Diagnosis of Periodontitis
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Abstract
Background: To investigate the diagnostic potential of salivary biomarkers and built a prediction panel for diagnosing periodontal disease. Methods: In a cross-sectional study, a total of 85 participants were enrolled in the study and divided into healthy, gingivitis and periodontitis groups based on their periodontal examine results, a full mouth periodontal examination were received and unstimulated saliva were collected. Salivary IL-1β, MMP-8, ICTP and Pg were assessed and their potential of diagnosing periodontal disease were analyzed, the combinational prediction panels of periodontal disease were evaluated. Results: The periodontitis group showed significantly higher level of IL-1β, MMP-8, ICTP and Pg compared to healthy group and higher level of IL-1β, ICTP and Pg compared to gingivitis group, the gingivitis group showed higher level of IL-1β, MMP-8 and Pg compared to healthy group. As a single marker, IL-1β showed the best diagnostic value of four markers and exhibited an AUC value of 0.88 with 94% sensitivity and 71% specificity to discriminate periodontitis from healthy subjects, an AUC value of 0.81 with 82% sensitivity and 76% specificity to discriminate gingivitis from healthy subjects and an AUC value of 0.67 with 69% sensitivity and 64% specificity to discriminate periodontitis from gingivitis subjects. The combination of IL-1, ICTP and Pg exhibited the highest value to discriminate periodontitis from healthy (AUC=0.94) and gingivitis (AUC=0.78) subjects, the combination of IL-1 and MMP-8 exhibited the best value to discriminate gingivitis from healthy subjects (AUC=0.85). Conclusions: Salivary IL-1β, MMP-8, ICTP and Pg showed discriminate efficiency for diagnosing periodontal disease, the combination of IL-1, ICTP and Pg can be used to discriminate periodontitis from healthy and gingivitis subjects and the combination of IL-1 and MMP-8 can be used to discriminate gingivitis from healthy subjects.
Springer Science and Business Media LLC
Title: Evaluation of Salivary Biomarkers for the Diagnosis of Periodontitis
Description:
Abstract
Background: To investigate the diagnostic potential of salivary biomarkers and built a prediction panel for diagnosing periodontal disease.
Methods: In a cross-sectional study, a total of 85 participants were enrolled in the study and divided into healthy, gingivitis and periodontitis groups based on their periodontal examine results, a full mouth periodontal examination were received and unstimulated saliva were collected.
Salivary IL-1β, MMP-8, ICTP and Pg were assessed and their potential of diagnosing periodontal disease were analyzed, the combinational prediction panels of periodontal disease were evaluated.
Results: The periodontitis group showed significantly higher level of IL-1β, MMP-8, ICTP and Pg compared to healthy group and higher level of IL-1β, ICTP and Pg compared to gingivitis group, the gingivitis group showed higher level of IL-1β, MMP-8 and Pg compared to healthy group.
As a single marker, IL-1β showed the best diagnostic value of four markers and exhibited an AUC value of 0.
88 with 94% sensitivity and 71% specificity to discriminate periodontitis from healthy subjects, an AUC value of 0.
81 with 82% sensitivity and 76% specificity to discriminate gingivitis from healthy subjects and an AUC value of 0.
67 with 69% sensitivity and 64% specificity to discriminate periodontitis from gingivitis subjects.
The combination of IL-1, ICTP and Pg exhibited the highest value to discriminate periodontitis from healthy (AUC=0.
94) and gingivitis (AUC=0.
78) subjects, the combination of IL-1 and MMP-8 exhibited the best value to discriminate gingivitis from healthy subjects (AUC=0.
85).
Conclusions: Salivary IL-1β, MMP-8, ICTP and Pg showed discriminate efficiency for diagnosing periodontal disease, the combination of IL-1, ICTP and Pg can be used to discriminate periodontitis from healthy and gingivitis subjects and the combination of IL-1 and MMP-8 can be used to discriminate gingivitis from healthy subjects.
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