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Background This study tests the feasibility of a network analysis approach to examine associations between clinical variables and mental health symptoms in rheumatoid arthritis (RA). Methods Over 1,000 patients completed patient reported outcomes. A sub-sample of 211 was extracted where psychological screening (using two-item versions of the Patient Health Questionnaire (PHQ2) and the Generalised Anxiety Disorder scale (GAD2)) and inflammatory markers were recorded concurrently (&amp;lt;14days). Inflammatory markers, joint counts, pain, fatigue, and global disease activity were also recorded. Network analysis was conducted based on egularised correlations between variables. Results The network highlights pain and PHQ2 (low mood) as having the highest degree (3.9 &amp; 3.8) and betweenness centrality (22 &amp; 10), indicating that they have the highest number of connections and provide the shortest pathway between symptoms, therefore act as key variables linking inflammation and mental health. Pain and global disease activity had the highest closeness centrality (0.033 &amp; 0.032), illustrating that they have the shortest path with other symptoms, and capture the influence of both inflammation and mental health. Tender and swollen joints have weak connections with mental health variables, suggesting that extra-articular aspects of pain may be important. Conclusion Inflammation in RA does not have a strong influence on mental health, but pain appears to be the biggest influencing factor. Symptoms of mental health were all strongly connected, but low mood provides the main connection between clinical and psychological variables. This indicates mood as potentially a key variable, which is easy to monitor in routine care. Disclosures H. Tung None. S. Norton None. J. Galloway None. F. Matcham None. M. Hotopf None.

P241 Associations between clinical variables and psychological symptoms in RA: a network science perspective