Cumulative use of salivary markers with an adaptive design improves detection of periodontal disease over fixed biomarker thresholds

Aim This cross‐sectional case–control study was designed to determine the association of the salivary concentration of CD9/CD81 exosome‐related tetraspanins with the periodontal clinical status. Materials and Methods Saliva samples from 104 periodontitis patients and 45 healthy controls were collected. Periodontal status was assessed based on full‐mouth clinico‐radiographical data, and salivary concentration of the analytes was calculated by ELISA. The association between the biomarkers with disease status was analysed using multivariate binary logistic regression models. Results Significantly decreased salivary levels of CD9 and CD81 exosomes were detected in periodontitis patients in comparison with healthy controls. Also, negative significant correlations between salivary concentrations of CD9/CD81 exosomes regarding clinical measurements were observed. Likewise, a significant downward trend of the concentration of these two biomarkers concerning the stage and grade of disease could be identified. Logistic regression analyses revealed a strong/independent association for decreased salivary concentration of CD81 exosomes regarding disease status. Confounding and interaction effects between age and salivary concentration of CD9 exosomes were also noted. Conclusion Reduced salivary concentration of CD9/CD81 exosomes might be of significance in the context of periodontal disease pathogenesis.

Section: Discussionmentioning

confidence: 77%

Decreased salivary concentration of CD9 and CD81 exosome‐related tetraspanins may be associated with the periodontal clinical status

Tobón‐Arroyave

Celis-Mejía

Córdoba-Hidalgo

et al. 2019

“…However, of all the articles included in the present review, only the series recently published by Gul et al () and Tomás et al () included validation analysis. On the other hand, recently, Gürsoy, Pussinen, Salomaa, Syrjäläinen, and Könonen () proposed the cumulative use of salivary biomarkers with an adaptive‐threshold design as an alternative to fixed biomarker thresholds in detection of the periodontitis.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of single molecular biomarkers in gingival crevicular fluid for the diagnosis of periodontitis: A systematic review and meta‐analysis

Arias-Bujanda

Regueira-Iglesias

Balsa-Castro

et al. 2019

Aim To analyse, by means of a meta‐analytical approach, the diagnostic accuracy of molecular biomarkers in gingival crevicular fluid (GCF) for the detection of periodontitis in systemically healthy subjects. Material and Methods Studies on GCF molecular biomarkers providing a binary classification table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. The search was performed using six electronic databases. The methodological quality of studies was assessed through the tool Quality Assessment of Diagnostic Studies. Meta‐analyses were performed using the Hierarchical Summary Receiver Operating Characteristic, which adjusts classification data using random effects logistic regression. Results The included papers identified 36 potential biomarkers for the detection of periodontitis and for four of them meta‐analyses were performed. The median sensitivity and specificity were for MMP8, 76.7% and 92.0%; for elastase, 74.6% and 81.1%; for cathepsin, 72.8% and 67.3%, respectively. The worst estimates of sensitivity and specificity were for trypsin (71.3% and 66.1%, respectively). Conclusions MMP8 showed good sensitivity and excellent specificity, which resulted in this biomarker being clinically the most useful or effective for the diagnosis of periodontitis in systemically healthy subjects, regardless of smoking condition.

“…These findings suggest that in addition to other influential factors (Gursoy, Pussinen, Salomaa, Syrjäläinen, & Könönen, 2018), the diagnostic power of the selected diagnostic threshold value is highly dependent on smoking habit.…”

Section: Discussionmentioning

confidence: 92%

Diagnostic accuracy of IL1β in saliva: The development of predictive models for estimating the probability of the occurrence of periodontitis in non‐smokers and smokers

Arias-Bujanda

Regueira-Iglesias

Blanco-Pintos

et al. 2020

Aim:To obtain salivary interleukin (IL) 1β-based models to predict the probability of the occurrence of periodontitis, differentiating by smoking habit. Materials/Methods:A total of 141 participants were recruited, 62 periodontally healthy controls and 79 subjects affected by periodontitis. Fifty of the diseased patients were given non-surgical periodontal treatment and showed significant clinical improvement in 2 months. IL1β was measured in the salivary samples using the Luminex instrument. Binary logistic regression models were obtained to differentiate untreated periodontitis from periodontal health (first modelling) and untreated periodontitis from treated periodontitis (second modelling), distinguishing between nonsmokers and smokers. The area under the curve (AUC) and classification measures were calculated. Results:In the first modelling, IL1β presented AUC values of 0.830 for non-smokers and 0.689 for smokers (accuracy = 77.6% and 70.7%, respectively). In the second, the predictive models revealed AUC values of 0.671 for non-smokers and 0.708 for smokers (accuracy = 70.0% and 75.0%, respectively). Conclusion:Salivary IL1β has an excellent diagnostic capability when it comes to distinguishing systemically healthy patients with untreated periodontitis from those who are periodontally healthy, although this discriminatory potential is reduced in smokers. The diagnostic capacity of salivary IL1β remains acceptable for differentiating between untreated and treated periodontitis. K E Y W O R D S diagnostic accuracy, interleukin 1β, periodontitis, predictive values, prevalence, saliva, sensitivity, specificity | 703 ARIAS-BUJANDA et Al.