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Updated: Oct 22, 2026
An Improved Mechanical Testing Method to Assess Bone-implant Anchorage
Published on: February 10, 2014
Combined Host-Derived and Microbiological Biomarkers for the Detection of Peri-Implant Bone Loss: A Diagnostic
Marion Arce1,2, Cristina Lima2, Leire Virto2
1Department of Conservative Dentistry, School of Dentistry, University of Chile, Santiago, Chile.
Aim:
To evaluate the diagnostic accuracy of host-derived and microbiological biomarkers, alone and in combination with clinical parameters, for the detection of peri-implant bone loss (BL).
Methods:
A university-based cohort of subjects with dental implants was examined at baseline and after a mean follow-up of 3.9 years. Peri-implant BL served as the reference standard, defined as > 1 mm between baseline and follow-up radiographs; implants with < 0.5 mm BL served as controls. At follow-up, peri-implant crevicular fluid and submarginal-microbiological samples were collected. Bone metabolism and inflammatory biomarkers were quantified using Luminex technology. Bacterial loads were quantified by qPCR. Associations of biomarkers with BL were evaluated using multilevel logistic regression models. Diagnostic accuracy was assessed using ROC curves, with AUC, sensitivity, specificity, and predictive values reported.
Results:
Seventy-one subjects with 273 implants were included. Twenty-eight exhibited peri-implant-BL > 1.0 mm over the follow-up period. Increased levels of IL-1β, T. denticola, Fusobacterium spp., and T. forsythia were associated with BL in unadjusted analyses. However, these associations were no longer statistically significant after adjustment for clinical parameters. Individual biomarkers demonstrated limited diagnostic accuracy (maximum AUC = 0.68). In contrast, biomarker combinations with clinical parameters exhibited excellent discriminative performance (AUC > 0.95). The combination of IL-1β and BoP-or-PPD achieved the highest accuracy (AUC = 0.97).
Conclusions:
While individual biomarkers showed limited diagnostic utility, combining multiple predictors significantly improved the ability to detect peri-implant BL. Combining IL-1β with either BoP or PPD significantly outperformed individual clinical measures but did not outperform the combination of clinical parameters, highlighting the potential of integrated biomarker and clinical parameter approaches as screening tools for detecting BL.
