What are the domains and outcome measures used in the existing neuropsychiatric systemic lupus erythematosus literature?

Neuropsychiatric involvement in SLE (NPSLE) is one of the most complex and challenging manifestations to manage. Due to the diversity and complexity of NPSLE, lack of diagnostic specificity and paucity of evidence-based outcome measures and targeted endpoints, including absence of biomarkers, severe NPSLE is often listed as an exclusion criterion in SLE randomized controlled trials [1]. Given the diagnostic challenges coupled with the potential illness severity, NPLSE represents a major unmet need in SLE. In their systematic review ‘Relevant domains and outcome measurement instruments in neuropsychiatric systemic lupus erythematosus: a systematic literature review’, published in this issue of Rheumatology, Silvagni et al. take a step towards tackling the measurement challenges in NPSLE by identifying domains measured and outcome measurement instruments used in the existing literature [2]. The ultimate goal of this line of research is to develop core domain sets and core outcome measurement sets for use in NPSLE clinical trials and research studies. Core domain and core outcome measurement sets are standardized domains and associated measurement instruments that should be assessed and reported at a minimum in all randomized controlled trials and longitudinal observational studies in specific health areas, with a view to standardize and facilitate interpretation and cross-study comparisons [3]. As part of their methodology, Silvagni et al. reference a structured framework, the Outcome Measures in Rheumatology (OMERACT) filter, used to characterize outcome measures identified in their review based on the domain they represent [4]. The filter uses a hierarchical framework to classify outcome measurement in health intervention studies with the goal of optimizing content and face validity in core outcome sets [4]. The OMERACT Filter 2.1 framework is comprised of two concepts (Pathophysiology and Impact) that contain four core areas [‘manifestations/abnormalities’ under the pathophysiology concept and ‘life impact’, ‘death/lifespan’ and ‘societal/resource use’ (optional) under the Impact of health conditions concept]. Effects (both benefits and harms) of treatment interventions should measure domains within each core area [4]. In their systematic review, Silvagni et al. identified 83 studies, including randomized controlled trials, systematic reviews and observational studies, that used domains and instruments covering all of the core areas defined in the OMERACT framework, except for ‘societal/resource use’ [2]. This systematic review demonstrates the diversity and heterogeneity of domains and outcome measures used in NPSLE, and highlights that substantial work is needed to further develop core domain and outcome measurement sets in this field. However, to develop meaningful core sets, we must first agree on constructs to measure, and second how to measure them [5]. We must then ensure that the measures included are a good fit for the SLE population, meet the measurement purpose and are feasible to administer. NPSLE has presented a measurement challenge for decades. In 1999, the ACR developed standardized definitions for 19 neuropsychiatric syndromes observed in SLE [6]. However, given that none of the conditions defined by the ACR are specific to SLE, to adequately study impact, prognosis and treatment response in NPSLE, it is critical to determine whether a given neuropsychiatric condition is actually attributable to SLE [7]. Determining attribution can be particularly challenging for conditions such as anxiety and depression that are non-specific and common in the general population. Part of the diagnostic uncertainty in NPSLE is related to the lack of evidence-based biomarkers. In an effort to identify diagnostic and evaluative biomarkers, a number of studies have examined potential serum or cerebrospinal fluid markers (e.g. autoantibodies) or MRI-based indices, primarily by comparing the prevalence of these findings in NPSLE vs SLE or evaluating their change with treatment [1]. Unfortunately, this research has yet to demonstrate adequate reproducibility to allow for clinical use [1]. In addition to biomarker identification, the NPSLE literature requires evidence-based patient-reported outcome measures to evaluate whether proposed biomarkers and treatments have real-world applicability and benefit to patients, taking into account the effects of both the illness and its management. These outcomes are represented by the OMERACT core domain of ‘life impact’, and generally include measures evaluating the constructs of health-related quality of life, functioning and participation. Very few studies in NPSLE have been conducted with the goal of evaluating the properties of patient-reported outcome measures themselves, to assess their utility in NPSLE. An example of a study with such a goal is the one conducted by Hanly et al., which evaluated the responsiveness of the SF-36 in NPSLE outcomes [8]. Such studies are critical in core instrument set development. In the current review, Silvagni et al. have taken an important step in identifying and classifying the outcome measures currently used in the NPSLE literature. The next steps are to (i) determine which studies can be characterized as measurement property studies to inform at least one of the OMERACT pillars (truth, discrimination, feasibility), (ii) critically appraise the selected studies to determine the quality of methods, (iii) assess the adequacy of the study results, and (iv) perform data synthesis when multiple studies are available [9]. For example, a study may suggest that a particular autoantibody predicts NPSLE treatment response, but if the study methods are deemed of inadequate quality then the results cannot be trusted. Rigorous quality appraisal is critical in determining whether potential outcome measures are suitable for inclusion in core instrument sets. Further, outcome measures must be meaningful to patients and generalizable across settings and cultures. The OMERACT process provides guidance to researchers in the development of core sets [5]. According to the OMERACT framework, it is essential to first determine ‘what to measure’ (core domain sets) and then to decide on ‘how to measure it’ (core outcome measurement sets). OMERACT has different groups working on various projects related to rheumatic diseases. The SLE Working Group’s (https://omeract.org/working-groups/sle/) first aim is to revisit and update the SLE core domain sets, which were initially proposed in 1999 [10]. Three phases are mandatory for the OMERACT domain selection process including the generation of the domains, agreement and prioritization of the domains, and finally voting on the developed OMERACT core domain sets by all stakeholders. OMERACT requires the involvement of patient research partners in measurement research and representation from at least three continents in the research group, to promote patient-centred and internationally generalizable outcome measures [5]. Development and evaluation of biomarkers and outcome measures will be foundational to determining effective and patient-centred treatment strategies for NPSLE. Ensuring that measurement instruments are evidence-based and meaningful requires rigorous and standardized research, involvement of patients, key stakeholders and international cooperation. Involvement and guidance from an organization such as OMERACT early in the process of core domain and instrument set development provides a means and methodology for ensuring these criteria are met. Funding: No specific funding was received from any funding bodies in the public, commercial or not-for-profit sectors to carry out the work described in this manuscript. Disclosure statement: The authors have declared no conflicts of interest. The dataset used and analysed during the current study is available from the senior author on reasonable request. Commentary on ‘Relevant domains and outcome measurement instruments in neuropsychiatric systemic lupus erythematosus: a systematic literature review’ Data availability statement The dataset used and analysed during the current study is available from the senior author on reasonable request.

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