Anxiety has specific syndromal profiles in Parkinson disease: a data-driven approach.

Starkstein SE, Dragovic M, Dujardin K, Marsh L, Martinez-Martin P, Pontone GM, Richard IH, Weintraub D, Leentjens AF. Anxiety has specific syndromal profiles in Parkinson disease: a data-driven approach. The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry. 2014 Dec 1; 22(12):1410-7.

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Abstract:

BACKGROUND: Anxiety symptoms are common in Parkinson disease (PD). Recent evidence suggests that anxiety syndromes as encountered in clinical practice may not correspond to the DSM-IV classification of anxiety disorders. OBJECTIVE: To examine the syndromal pattern of the anxiety spectrum in a large series of patients with PD, as determined with a data-driven approach using latent class analysis (LCA). METHODS: 342 patients with PD were recruited from referrals to movement disorders or psychiatry clinics at six tertiary centers. Participants were assessed with a structured psychiatric interview and specific scales rating the severity of anxiety, depression, cognition and parkinsonism. The main outcome measure was classes of patients with a specific syndromal profile of anxiety symptoms based on LCA. RESULTS: LCA identified four classes that were interpreted as "no anxiety or depression", "episodic anxiety without depression", "persistent anxiety with depression", and "both persistent and episodic anxiety with depression". Symptoms of persistent anxiety were almost invariably associated with symptoms of depression. There were significant differences between classes in terms of history of depression and anxiety, use of psychoactive medication, and on the Mentation and Complications sections of the Unified Parkinson Disease Rating Scale. CONCLUSIONS: Patients with PD show different syndromic profiles of anxiety that do not align with the symptom profiles represented by DSM-IV anxiety disorders and major depression. Accordingly, DSM-IV criteria for anxiety disorders may not be clinically useful in PD. The different classes identified here provide empirically validated phenotypes for future research.