The role of oxidative stress biomarkers in the development of peri-implant disease: a systematic review and meta-analysis

Objectives To analyse the role of oxidative stress (OS) biomarkers in peri-implant diseases using a systematic review and meta-analysis approach. Date The review incorporated cross-sectional studies, randomized controlled trials, and case-control trials to evaluate the differences in OS biomarkers of peri-implant disease. Sources A comprehensive literature search was conducted in electronic databases such as PubMed, Scopus, Embase, Web of Science, and CNKI, and no restrictions were applied during the search process. Study selection A total of 452 studies were identified, of which 18 were eligible for inclusion. Risk of bias and sensitivity analysis were assessed using Egger's test and funnel plots. Results We found that the levels of glutathione peroxidase (GSH-Px) in the peri-implant sulcus fluid (PISF) of patients with peri-implant diseases were significantly reduced (SMD=-1.40; 95% CI=1.70, -1.11; p<0.001), while the levels of total myeloperoxidase (MPO) and malondialdehyde (MDA) were significantly increased (SMD=0.46; 95% CI=0.12, 0.80; p=0.008; SMD=0.28; 95% CI=0.000, 0.56; p=0.043). However, there were no significant differences of MPO concentration (SMD = 0.38; 95%CI = -0.39, 1.15; p = 0.331) and superoxide dismutase (SOD)(SMD = -0.43; 95%CI = -1.94, 1.07; p = 0.572) in PISF between peri-implant disease group and control group. Similarly, salivary MPO did not show significant differences (SMD = 1.62; 95%CI = -1.01, 4.24; p = 0.227). Conclusions Our results supported that the level of local OS biomarkers was closely related to peri-implant diseases. GSH-Px, total MPO and MDA may be PISF biomarkers with good capability to monitor the development of peri-implant disease. Clinical Significance This study found significant differences in the levels of local OS biomarkers (GSH Px, total MPO, and MDA) between patients with peri-implant diseases and healthy subjects, which may be ideal candidate biomarkers for predicting and diagnosing peri-implant diseases.