Who Can Get Functional Neurological Disorder and How Do They Get It? Pathophysiological Insights from Epidemiological Data

Background and ObjectivesFunctional neurological disorder (FND) is one of the most common causes of neurological symptoms and disability, but much remains unknown about its pathophysiology. In both clinical conversations and research publications, clinicians and researchers imply a variety of models for onset of the condition with respect to both the process culminating in its onset, and the distribution of susceptibility to the condition across the population. Here we used population-level data as evidence to arbitrate between these generative models of the condition. MethodsWe identified six hazard distributions corresponding to different pathophysiological processes, and four distributions of population susceptibility, as the assumptions underlying the range of plausible generative models resulting in the observed distribution of age of onset of FND. We combined these model families into 24 parametric proportional hazards models, and fitted each to the observed distribution of reported age at onset in two large FND datasets, one for functional movement disorders (FMD) and one for functional seizures (FS). Out-of-sample predictive accuracy for these models was compared using Bayesian model comparison. ResultsStrong trends were seen across model families with different distributions of population susceptibility to FND. For both datasets, the best-fitting model family overall was the mixture-cure family, which represents susceptibility as binary, with a susceptible and an unsusceptible proportion of the population. For the FMD dataset, some models in the log-normal frailty family had comparable fits to the mixture-cure models, and for the FS dataset, a number of the gamma frailty family had comparable fits. The variance parameters for each of these frailty distributions were so large as to imply binary risk, approximating mixture-cure models. Models with exponential hazard distributions--which correspond to a generative process where a single trigger in a susceptible person brings about the condition--were universally poor fits for the observed data. Other hazard distributions were insufficiently distinguished by their out-of-sample predictive accuracy to make further inference as to the underlying process resulting in onset of FND in susceptible individuals. InterpretationOur results suggest that susceptibility to FND is approximately binary, with the susceptible proportion of the population extremely likely to develop FND in their lifetime. The results also argue strongly against a generative model where a single trigger is sufficient to cause the onset of FND in a susceptible person.