FRI0118 Clinical utility of area-under-curve (AUC) of patient-derived disease activity score (PDAS2) between clinic visits on remission, flare up and rheumatologist's decision to escalate anti-rheumatic drugs
Authors: M-HA Leung, E Choy, CS Lau
Journal: Annals of the Rheumatic Diseases (2017)

<h3>Background</h3> The standard of care in RA is treat-to-target of remission or low disease activity state (LDAS). Integral to this is the regular assessment of disease activity. Patient-derived Disease Activity Score 2 (PDAS2) was developed to allow RA patients to self-assess. Validation, corresponding disease activity statuses cut-points and response criteria had been published. PDAS2 scores &lt;3.8, 3.8–4.5, 4.6–5.0, &gt;5.0 correspond to remission, LDAS, moderate and high disease activities respectively. PDAS2 can be recorded by patients in-between clinic visits. <h3>Objectives</h3> To explore the clinical utility of PDAS2 on remission, flare and need of drug adjustment <h3>Methods</h3> A cohort of 100 consecutive RA patients was recruited to complete PDAS2 score at home fortnightly in between two consecutive rheumatology clinics. Patients would return the forms when they attended the second clinic. Rheumatologists adjusted treatment according to disease activity while blinded to the scores of PDAS2 recorded at home. AUC of PDAS2 was calculated from the mean of (PDAS2 score multiplied by the time interval between scores). They were compared with disease activity at the first and second visits. The change of PDAS2 score for those patients having SDAI flare-up (from remission/LDAS to moderate/high disease activity) was compared to those didn9t flare-up using unpaired T-test. Receiver Operator Characteristic curve was used to determine the cut-point for AUC-PDAS2 increment to predict flare-up and the cut-point of PDAS2 score for rheumatologists to escalate anti-rheumatic drugs. <h3>Results</h3> Mean age of the cohort was 60 years, mean RA duration 14 years, 90% female, 71% sero-positive and 48% in remission/low disease activity. 89 patients (89%) returned written questionnaires which were done 7.8±3.5 times (mean±standard deviation) (range 1–16) for a follow-up interval of 17.5±9.4 weeks (range 3.9–60.3). Disease activities in first and second visits are shown in Table. <i>Remission:</i> For the 14 patients in SDAI remission in both visits, 13/14 were in AUC-PDAS2 remission, and 1/14 in LDAS. There were 47, 45 and 37 out of 89 patients in SDAI, CDAI and DAS28 remission/LDAS respectively – they were all in AUC-PDAS2 remission/LDAS. <i>Flare-up:</i> There were 10/89 patients in SDAI remission/LDAS in first visit and moderate/high activity in second visit. Their AUC-PDAS2 score rose by 0.33±0.35 points compared to 0.01±0.32 who had no flare-up (p=0.002). ROC curve AUC was 0.80 (95% CI: 0.64, 0.95) (p=0.002), with optimal cut-point at increment of AUC-PDAS2 score by 0.11 to predict flare, sensitivity and specificity both being 80%. Moreover, rheumatologists decided to <i>escalate anti-rheumatic drugs</i> in 15/89 patients. ROC curve AUC was 0.71 (95% CI: 0.56, 0.86) (p=0.01), with optimal cut-point at PDAS2 score 4.33 to predict the need of escalating anti-rheumatic drugs, sensitivity being 60% and specificity 77%. <h3>Conclusions</h3> PDAS2 scoring by patients in-between follow-up is feasible and useful in reassuring RA patients kept in remission/LDAS, informing a potential flare from previous remission/LDAS state, and predicting rheumatologists9 decision to escalate anti-rheumatic drugs. AUC-PDAS2 concept is useful in development of smartphone application for patient use. <h3>References</h3> A&amp;R 2008 Feb 15;59(2):192–9. Rheumatology 2016 Nov;55(11):1954–8. <h3>Disclosure of Interest</h3> None declared