TY - JOUR T1 - Mining social media data to investigate patient perceptions regarding DMARD pharmacotherapy for rheumatoid arthritis JF - Annals of the Rheumatic Diseases JO - Ann Rheum Dis SP - 1432 LP - 1437 DO - 10.1136/annrheumdis-2020-217333 VL - 79 IS - 11 AU - Chanakya Sharma AU - Samuel Whittle AU - Pari Delir Haghighi AU - Frada Burstein AU - Roee Sa'adon AU - Helen Isobel Keen Y1 - 2020/11/01 UR - http://ard.bmj.com/content/79/11/1432.abstract N2 - Objectives We hypothesise that patients have a positive sentiment regarding biological/targeted synthetic disease modifying anti-rheumatic drugs (b/tsDMARDs) and a negative sentiment towards conventional synthetic agents (csDMARDs). We analysed discussions on social media platforms regarding DMARDs to understand the collective sentiment expressed towards these medications.Methods Treato analytics were used to download all available posts on social media about DMARDs in the context of rheumatoid arthritis. Strict filters ensured that user generated content was downloaded. The sentiment (positive or negative) expressed in these posts was analysed for each DMARD using sentiment analysis. We also analysed the reason(s) for this sentiment for each DMARD, looking specifically at efficacy and side effects.Results Computer algorithms analysed millions of social media posts and included 54 742 posts about DMARDs. We found that both classes had an overall positive sentiment. The ratio of positive to negative posts was higher for b/tsDMARDs (1.210) than for csDMARDs (1.048). Efficacy was the most commonly mentioned reason in posts with a positive sentiment and lack of efficacy was the most commonly mentioned reason for a negative sentiment. These were followed by the presence/absence of side effects in negative or positive posts, respectively.Conclusions Public opinion on social media is generally positive about DMARDs. Lack of efficacy followed by side effects were the most common themes in posts with a negative sentiment. There are clear reasons why a DMARD generates a positive or negative sentiment, as the sentiment analysis technology becomes more refined, targeted studies could be done to analyse these reasons and allow clinicians to tailor DMARDs to match patient needs. ER -