Tracking of Systemic Lupus Erythematosus (SLE) Longitudinally Using Biosensor and Patient-Reported Data: A Report on the Fully Decentralized Mobile Study to Measure and Predict Lupus Disease Activity Using Digital Signals-The OASIS Study.

(1) Objective: Systemic lupus erythematosus (SLE) is a complex disease involving immune dysregulation, episodic flares, and poor quality of life (QOL). For a decentralized digital study of SLE patients, machine learning was used to assess patient-reported outcomes (PROs), QOL, and biometric data for predicting possible disease flares. (2) Methods: Participants were recruited from the LupusCorner online community. Adults self-reporting an SLE diagnosis were consented and given a mobile application to record patient profile (PP), PRO, and QOL metrics, and enlisted participants received smartwatches for digital biometric monitoring. The resulting data were profiled using feature selection and classification algorithms. (3) Results: 550 participants completed digital surveys, 144 (26%) agreed to wear smartwatches, and medical records (MRs) were obtained for 68. Mining of PP, PRO, QOL, and biometric data yielded a 26-feature model for classifying participants according to MR-identified disease flare risk. ROC curves significantly distinguished true from false positives (ten-fold cross-validation: p < 0.00023; five-fold: p < 0.00022). A 25-feature Bayesian model enabled time-variant prediction of participant-reported possible flares (P(true) > 0.85, p < 0.001; P(nonflare) > 0.83, p < 0.0001). (4) Conclusions: Regular profiling of patient well-being and biometric activity may support proactive screening for circumstances warranting clinical assessment.

A Flare Risk Index Informed by Select Immune Mediators in Systemic Lupus Erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is marked by immune dysregulation linked to varied clinical disease activity. Using a unique longitudinal cohort of SLE patients, this study sought to identify optimal immune mediators informing an empirically refined flare risk index (FRI) reflecting altered immunity prior to clinical disease flare. METHODS: Thirty-seven SLE-associated plasma mediators were evaluated by microfluidic immunoassay in 46 samples obtained in SLE patients with an imminent clinical disease flare (preflare) and 53 samples obtained in SLE patients without a flare over a corresponding period (pre-nonflare). SLE patients were selected from a unique longitudinal cohort of 106 patients with classified SLE (meeting the American College of Rheumatology 1997 revised criteria for SLE or the Systemic Lupus International Collaborating Clinics 2012 revised criteria for SLE). Autoantibody specificities, hybrid SLE Disease Activity Index (hSLEDAI) scores, clinical features, and medication usage were also compared at preflare (mean ± SD 111 ± 47 days prior to flare) versus pre-nonflare (99 ± 21 days prior to nonflare) time points. Variable importance was determined by random forest analysis with logistic regression subsequently applied to determine the optimal number and type of analytes informing a refined FRI. RESULTS: Preflare versus pre-nonflare differences were not associated with demographics, autoantibody specificities, hSLEDAI scores, clinical features, nor medication usage. Forward selection and backward elimination of mediators ranked by variable importance resulted in 17 plasma mediator candidates differentiating preflare from pre-nonflare visits. A final combination of 11 mediators best informed a newly refined FRI, which achieved a maximum sensitivity of 97% and maximum specificity of 98% after applying decision curve analysis to define low, medium, and high FRI scores. CONCLUSION: We verified altered immune mediators associated with imminent disease flare, and a subset of these mediators improved the FRI to identify SLE patients at risk of imminent flare. This molecularly informed, proactive management approach could be critical in prospective clinical trials and the clinical management of lupus.

Clinical disease activity and flare in SLE: Current concepts and novel biomarkers.

Systemic lupus erythematosus (SLE) is a complex and heterogeneous systemic autoimmune disease associated with innate and adaptive immune dysregulation. SLE occurs primarily in females of childbearing age, with increased prevalence and severity in minority populations. Despite improvements in treatment modalities, SLE patients frequently experience periods of heightened disease activity and flare that can lead to permanent organ damage, increased morbidity, and early mortality. Such outcomes impair quality of life and inflict a significant socioeconomic burden. Predicting changes in SLE disease activity could allow for closer monitoring and preemptive treatment, but existing clinical, demographic and serologic markers have been only modestly predictive. Novel, proactive approaches to clinical disease management are thus critically needed. Panels of blood biomarkers can detect a breadth of immune pathway dysregulation that captures SLE heterogeneity and disease activity. Alterations in the balance of pro-inflammatory and regulatory soluble mediators have been associated with changes in clinical disease activity and are detectable several weeks prior to clinical flare occurrence. A soluble mediator score has been highly predictive of impending flare in both European American and African American SLE patients, and this score does not require a priori knowledge of specific pathway activation in the patient. We review current concepts of disease activity and flare in SLE, focusing on the potential of novel blood biomarkers to characterize and predict changes in disease activity. Measuring the disordered immune response in SLE in this way promises to improve disease management and prevent organ damage in SLE.