Systematic review of wound healing biomarkers in peri-implant crevicular fluid during osseointegration

To quantify and characterize the role of biomarkers in peri-implant crevicular fluid (PICF) at each stage of healing during osseointegration.

This systematic review was performed in accordance with PRISMA guidelines using several databases: MedLine (PubMed), Embase, ISI Web of Science, Scopus, and Cochrane Library. Medical subject headings and their indexers were used with no other limitations until December 2017. The dataset was extended with relevant papers from the reference lists of selected papers and from the gray literature. Data was summarized for study objectives, patient demographics, methods used to analyze PICF, biomarker concentrations, results and main findings. Methodologic quality of each included study was assessed using the checklist created by Downs and Black.

Electronic search resulted in 1698 articles. After excluding the duplicates, reading titles, abstracts and reference list reviews 30 prospective studies with longitudinal follow-up were selected. In total, 52 different biomarkers were identified. The most studied cytokines were interleukin (IL)-1, IL-1β, tumor necrosis factor alpha (TNF-α), and nitric oxide (NO). The earliest PICF specimens were collected immediately after implantation, and the latest at 16 weeks prior to occlusal loading. 36 biomarkers were quantified during week 1, 49 between day 10 and week 6, and 49 between weeks 8 and 12. Only 5 articles received good quality ratings.

The mechanism by which inflammatory and bone biomarkers are released during osseointegration has not yet been identified. However, some hypotheses based on immune-modulated reactions are being explored to investigate early and asymptomatic implant failures. Given the available clinical studies, it was not possible to further explore the performance of all biomarkers already analyzed and to extrapolate their results to propose a consultable data system based on release volume or concentration because of clinical study and data heterogeneity.