A critical appraisal of heterogeneity in Obsessive-Compulsive Disorder using symptom-based clustering analysis

Abstract

Obsessive-compulsive disorder (OCD) encompasses a broad range of symptoms and is commonly considered a heterogeneous condition. Attempts were made to define discrete OCD subtypes using a range of symptom-based methods including factor and cluster analyses. The present study aims to find the most appropriate clustering model based on Yale-Brown obsessive-compulsive scale (YBOCS) checklist explaining OCD heterogeneity. Five different clustering algorithms (FCM, K-means, Ward, Ward+K-means and Complete) applied on YBOCS symptoms of 216 patients with OCD. Data studied as four different sets including item-level raw data, item-based factor scores, category-level raw data and category-based factor scores and clustering results for 2 to 6 cluster solutions evaluated by four clustering indices (Davies-Bouldin, Calinski-Harabasz, Silhouettes and Dunn indices). Two-cluster solution was detected as the most appropriate model for item and category-based clustering analyses of YBOCS checklist symptoms. Patients in each cluster were characterized based on their clinical and demographic properties and results showed that they had similar patterns of symptoms but in different severities. Heterogenity of OCD based on the YBOCS-symptoms has been challenged as OCD patients were classified based on their symptom severity not their symptom patterns. More investigations need to find appropriate measures explaining OCD heterogeneity with clinical importance.

Novel ensemble method for the prediction of response to fluvoxamine treatment of obsessive–compulsive disorder

“…Moreover, exploratory factor analysis was applied to the 13 Y-BOCS obsession and compulsion categories. 54 Underlying factors were detected as factor 1: aggression, contamination, sexual, and religious obsessions as well as somatic, checking, and repeating compulsions; factor 2: symmetry obsession and cleaning, counting, and ordering compulsions; factor 3: contamination obsession and cleaning compulsion; and factor 4: hoarding obsession and compulsion. These factors were also considered as variables in our analysis.…”

Anxiety, OCD, delusions, and religiosity among the general public during the COVID‐19 pandemic

“…According to Hasanpour et al . (2017), researchers believe that OCD is a heterogeneous condition, as patients with OCD often display their symptoms in several different ways. Moreover, both obsessions and compulsions are varieties of cognitive inflexibility presented by patients with OCD (Lapidus et al .…”

“…OCD is the sixth most impeding psychiatric disorder, which is unexpectedly quite common in the general population (2.5 to 3 per cent), with lifetime primacy of 1.9 to 3.3 per cent that comprises a critical health-economic burden on society (Akhtar et al 1975). According to Hasanpour et al (2017), researchers believe that OCD is a heterogeneous condition, as patients with OCD often display their symptoms in several different ways. Moreover, both obsessions and compulsions are varieties of cognitive inflexibility presented by patients with OCD (Lapidus et al 2014).…”

<p>Fluvoxamine treatment response prediction in obsessive-compulsive disorder: association rule mining approach</p>

“…In the current study, we applied data mining algorithms to an OCD treatment response data set of Iranian patients to explore the most significant factors contributing to the treatment response. At first, we converted our data set variables which were chosen from previous studies9,27–31 and based on experts’ opinions to an appropriate format for application of Apriori algorithm. Next, we evaluated the association of each attribute with treatment response using support, confidence, and lift measures and found the most critical attributes that were associated with treatment response in OCD for pharmacotherapy with fluvoxamine.…”