JP1.3 Utility of Biomarkers for Femoroacetabular Impingement: A Systematic Review

Early diagnosis is crucial for effectively treating femoroacetabular impingement (FAI). Molecular biomarkers could improve the diagnosis and prognostication of patients with FAI at risk of developing hip osteoarthritis. This systematic review aimed to assess the utility of biomarkers associated with FAI for diagnostic purposes and as tools for predicting disease progression. The research questions addressed were: (1) which biomarkers are effective for the diagnosis or screening of FAI? and (2) which biomarkers can predict disease progression in FAI?

A systematic review using the PRISMA guidelines was conducted to investigate the relationship between biomarkers and FAI. The protocol for the review has been published in PROSPERO. Literature search was performed using three databases: Embase, MEDLINE, and Cochrane Library. The initial search yielded 683 articles of which 16 articles were included for final analysis.

Data from a total of 2,134 participants were analyzed. Sixty-eight unique biomarkers associated with FAI were identified and measured. Diagnostically, 19 biomarkers were identified of which 12 could significantly detect a difference between patients with FAI and healthy controls. 42 biomarkers predicting the association of FAI with hip osteoarthritis or late FAI were identified, of which 16 biomarkers were statistically significant. Only, 4-aminobutyrate aminotransferase promoter (ABAT) and peroxisome proliferator-activated receptor gamma (PPARγ) were associated with both diagnosis and prognosis.

Biomarkers can help with the diagnosis and identifying disease progression of FAI. A total of 12 biomarkers are useful for detecting early changes in FAI and there are 16 biomarkers which could help with predicting progression to osteoarthritis. However further characterization is required to narrow down the number of biomarkers in each group to demonstrate utility in routine clinical practice. ABAT and PPARγ are associated with both diagnosis and predicting disease progression of FAI.