Predictors of patient-reported outcomes phenotypes in SLE during remission: a cluster analysis approach.

OBJECTIVE

To identify different clusters of SLE patients in remission based on patient-reported outcomes (PROs) and clinical factors that predict cluster membership.

METHODS

A cross-sectional monocentric study of adult consecutive SLE outpatients in stable clinical remission. Clinical and laboratory data were collected. At enrolment, each patient completed PROs. A hierarchical clustering analysis based on PROs exploring fatigue (Functional Assessment of Chronic Illness Therapy), disease impact (Lupus Impact Tracker), mental and physical health (mental component summary and physical component summary of the Short Form 36) was performed. Logistic regression assessed predictors of cluster membership, adjusting for demographic and clinical variables.

RESULTS

195 SLE patients were enrolled. Two distinct clusters emerged: a 'low symptom burden (LSB)' cluster, including 81/195 (41.5%) patients, and a 'high symptom burden (HSB)' cluster, including 114/195 (58.5%) patients. The HSB was characterised by worse scores in all PROs compared with the LSB. The HSB cluster exhibited older age at diagnosis (33.23±11.97 vs 27.75±11.57; p=0.002), less frequent previous renal involvement (33.3% vs 65.4%; p<0.001), more frequent previous neuropsychiatric lupus (17.2% vs 1.3%; p=0.001), more fibromyalgia (26.3% vs 5.3%; p=0.001) and ongoing glucocorticoid use (58.8% vs 37.0%; p=0.004). Fibromyalgia (OR 7.27, 95% CI 2.27 to 29.15, p=0.002) and glucocorticoid treatment (OR 3.05, 95% CI 1.43 to 6.77, p=0.005) were independently associated with higher likelihood of HSB membership; renal involvement was associated with LSB membership (OR 0.23, 95% CI 0.10 to 0.51, p≤0.001).

CONCLUSIONS

Among SLE patients in remission, two distinct health-related quality of life phenotypes can be identified: an HSB and an LSB. Fibromyalgia and glucocorticoid treatment emerged as independent predictors of HSB. These findings underline the need to optimise disease management and align treatment goals with patient priorities.