Background The patient acceptable symptom state (PASS) is a single-question outcome tool to assess the level of symptoms at which patients with rheumatic diseases consider themselves well. Data published in the literature concerning the application of PASS to patients with Ankylosing Spondylitis and Rheumatoid Arthritis, show correlation with disease activity. No data are available concerning the use of this tool in patients with SLE.
Objectives To evaluate the discriminant capability of PASS according to disease activity in a cohort of SLE patients.
Methods Consecutive patients affected by SLE, according with ACR classification criteria, were invited to participate in this study. At each visit, the patients underwent complete physical examination, and the clinical and laboratory data were collected in a standardized computerized electronically-filled form including demographics, past medical history with date of diagnosis, co-morbidities, previous and concomitant treatments. A blood sample for evaluation of serum complement C3 and C4 levels and determination of autoantibodies [ANA, anti-dsDNA, ENA (Sm, RNP, SSA, SSB), anticardiolipin IgG/IgM, antiBeta2GPI, LAC] was obtained. Disease activity was assessed with SLEDAI and ECLAM, chronic damage was evaluated with SLICC. PASS was assessed by asking patients to answer yes or no to a single question: “Considering all the different ways your disease is affecting you, if you would stay in this state for the next months, do you consider that your current state is satisfactory?”.
Results One hundred sixty five SLE patients were enrolled (M/F 12/153; mean age 40.4±11.8 years, mean disease duration 109.1±96.2 months; mean SLEDAI 2.1±2.8; mean ECLAM 0.8±1.0; mean SLICC 0.2±0.6). We dichotomized our patients according with the answer given to PASS: group 1 (patients answering yes) and group 2 (patients answering no). We found that PASS was associated with disease activity. Indeed, group 1 patients had significantly better SLEDAI and ECLAM values than group 2 patients (1.8±2.7 versus 3.4±2.3 [P=0.004]; 0.7±0.9 versus 1.4±1.1 [P=0.0027], respectively). When considering the clinical manifestations, articular involvement was less frequent in group 1 (7.7% versus 39.4%, P=0.00003). Concerning the autoantibody profile, the ENA prevalence was significantly lower in group 1 patients compared with group 2 (22.7% versus 64.3%, P=0.003). In particular, significant difference was found when considering anti-SSA (18.2% versus 42.0%, P=0.0003), anti-Sm (2.3% versus 21.4%, P<0.001), and anti-RNP (2.3% versus 14%, P=0.002). Moreover, group 1 patients were taking less frequently immunosuppressants (32.5% versus 48.4%, P=0.03). No significant differences were observed when considering chronic damage, evaluated with SLICC.
Conclusions In the routinary clinical practice, SLE patients assessment performed with the usage of complex disease activity indices such as SLEDAI and ECLAM, could be time consuming. In our study, for the first time, we used a quick and easily comprehensible tool, PASS, to evaluate the patients’ status. This single question seems to be able to discriminate patients with different disease activity especially when this is determined by musculoskeletal involvement.
Disclosure of Interest None Declared