Relationship of rare disorder latent clusters to anxiety and depression symptoms.

OBJECTIVE

A single rare disorder or disease (RD) affects fewer than 200,000 Americans. Combined, RDs affect 30 million Americans. Collectively, people with RDs have higher levels of anxiety and depression compared with those with prevalent diseases. Previous attempts to study psychological distress within individual RDs or disease classification systems are limited by low power, generalizability, and predictive utility. The present study used mixture modeling to identify meaningful RD clusters associated with anxiety and depression.

METHOD: One-thousand and 218 participants with 232 RDs were surveyed on RD characteristics and anxiety and depression symptoms. Mixture modeling identified symptom clusters based on RD characteristics (i.e., age of symptom onset, disease course, fatigue, pain, physical function, duration of symptoms, and visibility).

RESULTS

The following six clusters were identified (most frequently represented RD in parentheses): stable (cutaneous T cell lymphoma), late onset and visible (spinocerebellar ataxia), moderate symptoms (spinocerebellar ataxia), invisible and tiring (idiopathic hypersomnia), severe symptoms (spinocerebellar ataxia), and early onset with severe symptoms (Ehlers-Danlos syndrome). There was a significant relationship between cluster membership and anxiety and depression symptoms. Clusters in order from least to most distress were: stable; late onset and visible; moderate symptoms; invisible and tiring; severe symptoms; and early onset with very severe symptoms. The last two clusters had clinically significantly more distress than the stable cluster.

CONCLUSIONS

Researchers, clinicians, RD organizations, and policymakers could make wide-reaching impacts by prioritizing funding, research, and interventions for people likely to fall in a cluster at high risk for distress. (PsycINFO Database Record (c) 2020 APA, all rights reserved).