| Literature DB >> 31692297 |
Christine Lochner1, Nancy J Keuthen2, Erin E Curley3, Esther S Tung2,4, Sarah A Redden5,6, Emily J Ricketts7, Christopher C Bauer8, Douglas W Woods8, Jon E Grant5, Dan J Stein9.
Abstract
BACKGROUND: A promising approach to reducing the phenotypic heterogeneity of psychiatric disorders involves the identification of homogeneous subtypes. Careful study of comorbidity in obsessive-compulsive disorder (OCD) contributed to the identification of the DSM-5 subtype of OCD with tics. Here we investigated one of the largest available cohorts of clinically diagnosed trichotillomania (TTM) to determine whether subtyping TTM based on comorbidity would help delineate clinically meaningful subgroups.Entities:
Keywords: borderline personality disorder; comorbidity; depression; treatment; trichotillomania
Mesh:
Year: 2019 PMID: 31692297 PMCID: PMC6908854 DOI: 10.1002/brb3.1456
Source DB: PubMed Journal: Brain Behav Impact factor: 2.708
Figure 1Dendrogram of 304 cases with trichotillomania (Ward's method, with Euclidean distances)
Frequencies of each lifetime comorbid disorder, per cluster
| Comorbid disorders | Cluster membership | ||
|---|---|---|---|
|
Cluster 1: Simple TTM
|
Cluster 2: Depressive TTM
|
Cluster 3: Complex TTM
| |
| Major depressive disorder | 0 | 49 (100%) | 119 (62%) |
| Panic disorder with/out agoraphobia | 0 | 0 | 16 (8%) |
| Social anxiety disorder | 0 | 0 | 28 (15%) |
| Specific phobia | 0 | 0 | 43 (22%) |
| Generalized anxiety disorder | 0 | 0 | 42 (22%) |
| Obsessive‐compulsive disorder | 0 | 0 | 70 (36%) |
| Skin‐picking disorder | 0 | 0 | 46 (24%) |
| Posttraumatic stress disorder | 0 | 0 | 29 (15%) |
| Attention deficit disorder | 0 | 0 | 15 (8%) |
| Tics | 0 | 0 | 16 (8%) |
| Binge‐eating disorder | 0 | 0 | 12 (6%) |
| Body dysmorphic disorder | 0 | 0 | 17 (9%) |
| Alcohol abuse and dependence | 0 | 0 | 26 (14%) |
| Substance abuse and dependence | 0 | 0 | 43 (22%) |
Abbreviation: TTM, trichotillomania.
Demographic and clinical characteristics across clusters of cases
| Variable | Cluster membership | Statistic |
| ||
|---|---|---|---|---|---|
|
Cluster 1 Simple TTM
|
Cluster 2 Depressive TTM
|
Cluster 3 Complex TTM
| |||
| Sex | |||||
| Male | 3 | 1 | 13 | Chi‐square: 1.76 | .42 |
| Female | 60 | 48 | 179 | ||
| Mean age (in years) | 32.73 ( | 33.37 ( | 32.6 ( |
| .93 |
| Age of onset of TTM (in years) | 12.92 ( | 12.82 ( | 13.65 ( |
| .54 |
| Age of onset of comorbid MDD | (no MDD) | 23.4 ( | 21.3 ( |
| .50 |
| Duration of illness (in years) | 19.81 ( | 20.55 (SD13.14) | 18.87 ( |
| .67 |
| MGHHPS total score | 13.38 ( | 14.82 ( | 15.27 ( |
| .02 |
| BDI total score | 3.7 ( | 12.8 ( | 12.4 ( |
| .01 |
Abbreviations: BDI, Beck Depression Inventory; MDD, major depressive disorder; MGHHPS, Massachusetts General Hospital Hair Pulling Scale; TTM, trichotillomania.
Of the 168 cases with lifetime MDD, only 46 (27.4%) had age of onset of MDD data available.
Cluster 3 cases had significantly worse hair‐pulling than those in Cluster 1 (p = .02).
Clusters 2 (p = .04) and 3 (p = .003) both had significantly more severe depressive symptomatology than Cluster 1 cases.
Figure 2Comparison of trichotillomania (TTM) severity among the three identified clusters. Current effect: F(2, 295) = 3.75, p = .02, Kruskal–Wallis p < .01 Letters indicate post hoc differences at a 5% significance level, i.e. means without overlapping letters are significantly different
Figure 3Comparison of severity of depressive symptoms among the three identified clusters. Current effect: F(2, 52) = 5.07, p = <.01 Kruskal–Wallis p < .01. TTM, trichotillomania; Letters indicate post hoc differences at a 5% significance level, i.e. means without overlapping letters are significantly different