The use of patient-reported outcome measures to classify type 1 and 2 systemic lupus erythematosus activity.

Objective: We developed a model that categorizes systemic lupus erythematosus (SLE) activity into two dimensions: Type 1 SLE consists of inflammatory activity, including arthritis, nephritis, and rashes; Type 2 SLE includes fatigue, myalgia, mood disturbance, and cognitive dysfunction. Patient-reported outcome (PRO) measures have received attention as a way to capture symptomatology of SLE. The objective of this study was to explore the use of existing PRO measures to classify Type 1 and 2 SLE activity. Methods: Systemic lupus erythematosus patients completed three questionnaires: Systemic Lupus Activity Questionnaire (SLAQ), Polysymptomatic Distress Scale (PSD), and Patient Health Questionnaire (PHQ-2). SLE Disease Activity Index (SLEDAI) and physician global assessments (PGA; 0–3) for Type 1 and Type 2 activity were also recorded. High Type 1 SLE activity was defined as cSLEDAI ≥4 (scored without labs), SLEDAI ≥6, active nephritis, or Type 1 PGA ≥1.0. High Type 2 SLE activity was defined as Type 2 PGA ≥1.0. Patients with both high Type 1 and 2 activity were defined as Mixed SLE, and patients with low Type 1 and 2 activity were defined as Minimal SLE. Data were reduced with a factor analysis. Using a reduced set of 13 variables, multinomial logistic regression models estimated the probability of Minimal, Type 1, Type 2, and Mixed SLE classification. Results: The study included 208 patients with SLE. The model accurately predicted the clinician-based Type 1 and 2 SLE classification in 63% of patients; 73% of patients had their Type 1 SLE activity accurately predicted; and 83% had their Type 2 SLE activity accurately predicted. Performance varied by group: 87% of Minimal patients were correctly predicted to be in the Minimal SLE group, yet only about one-third of patients in the Type 1 group were correctly predicted to be in the Type 1 group. Conclusions: Our findings indicate Type 2 SLE activity can be identified by patient-reported data. The use of PROs was not as accurate at predicting Type 1 activity. These findings highlight the challenges of using PROs to categorize and classify SLE symptoms since some manifestations of Type 1 activity (e.g., nephritis) may be essentially clinically silent while other Type 1 manifestations may cause severe symptoms. [ABSTRACT FROM AUTHOR]