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

Abstract

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.