{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T21:36:23Z","timestamp":1788212183287,"version":"build-2803163510"},"reference-count":79,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T00:00:00Z","timestamp":1742256000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Oral Pathology Medicine"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Several biomarkers in peri\u2010implant crevicular fluid have been studied to diagnose peri\u2010implant diseases with inconclusive results. This systematic review and meta\u2010analysis aimed to comprehensively compare data on the levels of biological components in peri\u2010implant crevicular fluid collected from healthy and diseased implants to identify reliable biomarkers for diagnosing and monitoring peri\u2010implant disease.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>The search strategy included studies comparing biomarker levels in peri\u2010implant crevicular fluid between healthy and diseased implants through electronic databases (MEDLINE\/PubMed, Embase, Cochrane Library), grey literature, and hand\u2010searching relevant journals and reference lists of pertinent papers. A two\u2010stage screening was performed in duplicate and independently. In the first stage, titles and abstracts that fulfilled eligibility criteria were screened. In the second stage, a full\u2010text analysis was conducted to verify eligibility. All articles meeting the inclusion criteria underwent data extraction and quality assessment. Meta\u2010analyses were conducted on studies with similar comparisons and outcome measures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>After screening the titles and abstracts, out of 100 potentially relevant papers identified for full\u2010text evaluation, 49 were excluded, 51 were included in the qualitative analysis, and 18 were included in the quantitative synthesis. Among 96 biomarkers assessed, the most studied were pro\u2010inflammatory cytokines (IL\u20101\u00df, IL\u20106, TNF\u2010\u03b1, and IL\u201017), osteoclastogenic\u2010related factors (RANK, RANKL, and OPG), anti\u2010inflammatory cytokines (IL\u201010), chemokines (IL\u20108, MIP\u20101\u03b1\/CCL3, and MIP\u20103\u03b1\/CCL\u201020), and enzymes (MMP\u20108, Cat\u2010K, AST, and ALT).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Meta\u2010analyses comparing data from healthy patients and those with peri\u2010implantitis or mucositis and between patients with mucositis and those with peri\u2010implantitis showed a moderate predictive value of IL\u20101\u00df, VEGF, cortisol, and sRANKL\/OPG for peri\u2010implantitis.<\/jats:p>\n                  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