Meta-analysis identifies the patient classification major impact on the ACPA association with rheumatoid arthritis-associated interstitial lung disease (RA-ILD)

Background: We need screening for RA patients at high risk of RA-ILD to prevent the associated decrease in life quality and survival. The proposed screenings disagree regarding the anti-citrullinated protein antibodies (ACPA) because of their inconsistent association across recent studies. Therefore, we hypothesized that meta-analysis of the published reports should reveal clues explaining the heterogeneity of results and that knowing them could help us progress in RA-ILD early detection. Objectives: We aimed to discover the factors accounting for the variability of the ACPA association in the published reports. Methods: We searched the Web of Science and PubMed databases for studies reporting ACPA in RA-ILD and RA-control groups. The identified studies were analyzed using meta-analysis and meta-regression to identify moderators of the ACPA association. Results: We found 513 unique records, containing 31 eligible data sets. The meta-analysis preceding the search for moderators showed a remarkable heterogeneity (p Q = 5.7 x 10 -7 ). Appropriate tests showed that it was largely attributable (58.1 %) to an outlier study, which had recruited cases and controls in different place and time contexts. The exclusion of this outlier from subsequent analyses did not completely remove heterogeneity (p Q = 0.004). However, it permitted the identification of the patient classification method as a significant moderator: The 14 studies using chest CT showed stronger ACPA association with RA-ILD (OR = 3.05 [95%CI: 2.12-4.38]) than the 16 employing multifactorial criteria (1.55 [95%CI: 1.18-2.03]; p = 0.0047 for the contrast). This moderator accounted for the significant heterogeneity (p Q = 0.079), was robust in sensitivity analyses, and was the only one found. Conclusions: Our results validate the ACPA association with RA-ILD, reinforce the importance of study design, and suggest the need to consider if studies relying on chest CT for classification could be more fruitful in the search for RA-ILD biomarkers.