Attribution of neuropsychiatric symptoms and prioritization of evidence in the diagnosis of neuropsychiatric lupus: mixed methods analysis of patient and clinician perspectives from the international INSPIRE study.

Abstract

OBJECTIVE: Neuropsychiatric lupus (NPSLE) is challenging to diagnose. Many neuropsychiatric symptoms, such as headache and hallucinations, cannot be verified by tests or clinician assessment. We investigated prioritizations of methods for diagnosing NPSLE and attributional views. METHODS: Thematic and comparative analyses were used to investigate how clinicians prioritize sources of evidence from a 13-item list, and explore discordances in clinician (surveys n = 400, interviews n = 50) and patient (surveys n = 676, interviews n = 27) perspectives on attribution. RESULTS: We identified high levels of variability and uncertainty in clinicians' assessments of neuropsychiatric symptoms in SLE patients. In attributional decisions, clinicians ranked clinicians' assessments above diagnostic tests (many of which they reported were often unenlightening in NPSLE). Clinicians ranked patient opinion of disease activity last, and 46% of patients reported never/rarely having been asked if their SLE was flaring, despite experienced patients often having 'attributional insight'. SLE patients estimated higher attributability of neuropsychiatric symptoms to the direct effects of SLE on the nervous system than clinicians (P < 0.001 for all symptoms excluding mania), and 24% reported that their self-assessment of disease activity was never/rarely concordant with their clinicians. Reports of misattributions were common, particularly of non-verifiable diffuse symptoms. Terminology differed between clinicians and influenced attribution estimates. CONCLUSION: NPSLE diagnostic tests and clinician assessments have numerous limitations, particularly in detecting diffuse neuropsychiatric symptoms that can be directly attributable and benefit from immunosuppression. Our findings suggest that incorporating patient attributional insights-although also subject to limitations-may improve attribution decision-making. Consensus regarding terminology and interpretations of 'direct attributability' is required.