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BACKGROUND: Functional neurological disorder (FND) is a common and disabling neuropsychiatric condition, which disproportionally affects women compared with men. While the etiopathogenesis of this disorder remains elusive, immune dysregulation is emerging as one potential mechanism. To begin to understand the role of immune dysfunctions in FND, we assessed the prevalence of several common autoimmune diseases (ADs) in a large cohort of patients with FND and examined the influence of psychiatric comorbidities and biological sex. METHODS: Using a large biorepository database (Mass General Brigham Biobank), we obtained demographic and clinical data of a cohort of 643 patients diagnosed with FND between January 2015 and December 2021. The proportion of ADs was calculated overall, by sex and by the presence of psychiatric comorbidities. RESULTS: The overall prevalence of ADs in our sample was 41.9%, with connective tissue and autoimmune endocrine diseases being the most commonly observed ADs. Among patients with FND and ADs, 27.7% had ≥2 ADs and 8% met criteria for multiple autoimmune syndrome. Rates of ADs were significantly higher in subjects with comorbid major depressive disorder and post-traumatic stress disorder (p= 0.02). Women represented the largest proportion of patients with concurrent ADs, both in the overall sample and in the subgroups of interest (p's < 0.05). CONCLUSIONS: This study is unique in providing evidence of an association between FND and ADs. Future studies are needed to investigate the mechanisms underlying this association and to understand whether FND is characterised by distinct dysregulations in immune response.
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INTRODUCTION: The high failure rate of clinical trials in traumatic brain injury (TBI) may be attributable, in part, to the use of untested or insensitive measurement instruments. Of more than 1,000 clinical outcome assessment measures (COAs) for TBI, few have been systematically vetted to determine their performance within specific "contexts of use (COU)." As described in guidance issued by the U.S. Food and Drug Administration (FDA), the COU specifies the population of interest and the purpose for which the COA will be employed. COAs are commonly used for screening, diagnostic categorization, outcome prediction, and establishing treatment effectiveness. COA selection typically relies on expert consensus; there is no established methodology to match the appropriateness of a particular COA to a specific COU. We developed and pilot-tested the Evidence-Based Clinical Outcome assessment Platform (EB-COP) to systematically and transparently evaluate the suitability of TBI COAs for specific purposes. METHODS AND FINDINGS: Following a review of existing literature and published guidelines on psychometric standards for COAs, we developed a 6-step, semi-automated, evidence-based assessment platform to grade COA performance for six specific purposes: diagnosis, symptom detection, prognosis, natural history, subgroup stratification and treatment effectiveness. Mandatory quality indicators (QIs) were identified for each purpose using a modified Delphi consensus-building process. The EB-COP framework was incorporated into a Qualtrics software platform and pilot-tested on the Glasgow Outcome Scale-Extended (GOSE), the most widely-used COA in TBI clinical studies. CONCLUSION: The EB-COP provides a systematic methodology for conducting more precise, evidence-based assessment of COAs by evaluating performance within specific COUs. The EB-COP platform was shown to be feasible when applied to a TBI COA frequently used to detect treatment effects and can be modified to address other populations and COUs. Additional testing and validation of the EB-COP are warranted.
