Premium
Molecular and Structural Biomarkers of Inflammation at Two Years After Acute Anterior Cruciate Ligament Injury Do Not Predict Structural Knee Osteoarthritis at Five Years
Author(s) -
Roemer Frank W.,
Englund Martin,
Turkiewicz Aleksandra,
Struglics André,
Guermazi Ali,
Lohmander L. Stefan,
Larsson Staffan,
Frobell Richard
Publication year - 2019
Publication title -
arthritis and rheumatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.106
H-Index - 314
eISSN - 2326-5205
pISSN - 2326-5191
DOI - 10.1002/art.40687
Subject(s) - medicine , osteoarthritis , anterior cruciate ligament , magnetic resonance imaging , confidence interval , acl injury , receiver operating characteristic , synovitis , synovial fluid , biomarker , area under the curve , gastroenterology , radiology , nuclear medicine , pathology , arthritis , biochemistry , chemistry , alternative medicine
Objective To determine the role of inflammatory biomarkers at 2 years post–anterior cruciate ligament ( ACL ) injury to predict radiographic knee osteoarthritis ( OA ) and magnetic resonance imaging ( MRI )–defined knee OA at 5 years postinjury, with a secondary aim of estimating the concordance of inflammatory biomarkers assessed by MRI and synovial fluid ( SF ) analysis. Methods We studied 113 patients with acute ACL injury. Knee scans using 1.5T MRI s were read for Hoffa‐ and effusion‐synovitis. Biomarkers of inflammation that we assessed included interleukin‐6 ( IL ‐6), IL ‐8, IL ‐10, tumor necrosis factor, and interferon‐ɣ in serum and SF , and IL ‐12p70 in serum. We defined the outcome as radiographic knee OA ( ROA ) or MRI ‐defined OA ( MROA ) at 5 years. The area under the receiver operating characteristic curve ( AUC ), sensitivity, and specificity were evaluated in models that included MRI features only (model 1), inflammation biomarkers only (serum [model 2a] or SF [model 2b]), both MRI features and serum biomarkers (model 3a), or both MRI features and SF (model 3b) biomarkers. Linear regression analysis was used to evaluate the association between MRI features and SF biomarkers. Results At 5 years postinjury, ROA was present in 26% of the injured knees, and MROA was present in 32%. The AUC s for ROA in each model were 0.44 (95% confidence interval [95% CI ] 0.42, 0.47) for model 1, 0.62 (95% CI 0.59, 0.65) for model 2a, 0.53 (95% CI 0.50, 0.56) for model 2b, 0.58 (95% CI 0.55, 0.61) for model 3a, and 0.50 (95% CI 0.46, 0.53) for model 3b. The AUC s for MROA in each model were 0.67 (95% CI 0.64, 0.70) for model 1, 0.49 (95% CI 0.47, 0.52) for model 2a, 0.56 (95% CI 0.52, 0.59) for model 2b, 0.65 (95% CI 0.61, 0.68) for model 3a, and 0.69 (95% CI 0.66, 0.72) for model 3b. The concordance between MRI and SF biomarkers was statistically significant only for effusion‐synovitis and IL ‐8. Conclusion Neither MRI ‐detected inflammation nor selected SF /serum inflammation biomarkers at 2 years postinjury predicted ROA or MROA at 5 years postinjury. Concordance between MRI and SF inflammatory biomarkers was weak.