| Literature DB >> 33921148 |
Ismo T Räisänen1, Hanna Lähteenmäki1, Shipra Gupta2, Andreas Grigoriadis3,4, Vaibhav Sahni5, Juho Suojanen6,7, Hanna Seppänen8,9, Taina Tervahartiala1, Dimitra Sakellari4, Timo Sorsa1,10.
Abstract
The aim of this cross-sectional study is to propose an efficient strategy based on biomarkers adjunct with an interview/questionnaire covering risk factors for periodontitis for the identification of undiagnosed periodontitis by medical professionals. Active matrix metalloproteinase (aMMP)-8 levels in mouthrinse were analyzed by a point-of-care (PoC)/chairside lateral-flow immunotest, and salivary total MMP-8, total MMP-9 and calprotectin levels were analyzed by enzyme-linked immunosorbent assays (ELISAs) and active MMP-9 by gelatin zymography for 149 Greek patients. Patients underwent a full-mouth oral health examination for diagnosis according to the 2018 classification system of periodontal diseases. In addition, patient characteristics (risk factors: age, gender, education level, smoking and body mass index) were recorded. Receiver operating curve (ROC) analysis indicated better diagnostic precision to identify undiagnosed periodontitis for oral fluid biomarkers in adjunct with an interview/questionnaire compared with a plain questionnaire (i.e., risk factors): aMMP-8 AUC (95% confidence interval) = 0.834 (0.761-0.906), total MMP-8 = 0.800 (0.722-0.878), active MMP-9 = 0.787 (0.704-0.870), total MMP-9 = 0.773 (0.687-0.858) and calprotectin = 0.773 (0.687-0.858) vs. questionnaire = 0.764 (0.676-0.851). The findings of this study suggest that oral fluid biomarker analysis, such as a rapid aMMP-8 PoC immunotest, could be used as an adjunct to an interview/questionnaire to improve the precision of timely identification of asymptomatic, undiagnosed periodontitis patients by medical professionals. This strategy appears to be viable for referring patients to a dentist for diagnosis and treatment need assessment.Entities:
Keywords: biomarkers; diagnostics; matrix metalloproteinase 8; oral health; periodontitis; point-of-care systems; preventive medicine
Year: 2021 PMID: 33921148 PMCID: PMC8071538 DOI: 10.3390/diagnostics11040711
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418
Figure 1Receiver operating curve (ROC) analysis regarding using questionnaire and biomarkers (aMMP-8, total MMP-8, active MMP-9, total MMP-9 and calprotectin) to identify undiagnosed periodontitis (Stages II–III) (n = 149 Greek patients, as described previously [2,3,24]). (A) A plain questionnaire vs. a questionnaire adjunct with aMMP-8, total MMP-8, or calprotectin, and (B) a plain questionnaire vs. a questionnaire adjunct with aMMP-8, active MMP-9, or total MMP-9. Questionnaire includes patient’s gender, age, education level, smoking and body mass index (BMI).
Diagnostic potential of a questionnaire and biomarkers (aMMP-8, total MMP-8, active MMP-9, total MMP-9 and calprotectin) to identify periodontitis (Stages II–III). The Youden index was used defining the optimal cut-offs for each logistic regression model from the ROC curves.
| Model | AUC (95% CI) | Cut-off Point | Se (%) | Sp (%) | FN (%) | FP (%) | Acc (%) | MCC | F1 Score | |
|---|---|---|---|---|---|---|---|---|---|---|
| Questionnaire | 0.764 (0.676–0.851) | <0.001 | 0.656 | 76.0 | 73.3 | 43.1 | 13.2 | 75.2 | 0.464 | 0.810 |
| aMMP-8 PoC test and Questionnaire | 0.834 (0.761–0.906) | <0.001 | 0.574 | 86.5 | 73.3 | 29.8 | 11.8 | 82.6 | 0.592 | 0.874 |
| Total MMP-8 and Questionnaire | 0.800 (0.722–0.878) | <0.001 | 0.570 | 88.5 | 64.4 | 29.3 | 14.8 | 81.2 | 0.544 | 0.868 |
| Active MMP-9 and Questionnaire | 0.787 (0.704–0.870) | <0.001 | 0.692 | 74.0 | 75.6 | 44.3 | 12.5 | 74.5 | 0.463 | 0.802 |
| Total MMP-9 and Questionnaire | 0.767 (0.680–0.855) | <0.001 | 0.625 | 79.8 | 68.9 | 40.4 | 14.4 | 76.5 | 0.469 | 0.826 |
| Calprotectin and Questionnaire | 0.773 (0.687–0.858) | <0.001 | 0.666 | 76.9 | 73.3 | 42.1 | 13.0 | 75.8 | 0.475 | 0.816 |
Questionnaire: gender, age, education level, smoking, body mass index (BMI). AUC: Area Under the ROC Curve; CI: confidence interval; Se: sensitivity; Sp: specificity; FN: false negatives; FP: false positives; Acc: accuracy; MCC: Matthews correlation coefficient; POC: point of care; F1 score: the harmonic mean of the precision and recall. values calculated by the Mann-Whitney U test.