›› 2018, Vol. 38 ›› Issue (6): 676-.doi: 10.3969/j.issn.1674-8115.2018.06.016

• Review • Previous Articles     Next Articles

Progress in researches on latent class analysis based subtyping of depression

WANG Cheng-lei1, WU Zhi-guo1, FANG Yi-ru1, 2, 3   

  1. 1. Division of Mood Disorder, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; 2. Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai 200031, China; 3. Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
  • Online:2018-06-28 Published:2018-07-03
  • Supported by:
    National Key Research and Development Program of China, 2016YFC1307100; National Natural Science Foundation of China, 91232719; Foundation of Shanghai Hospital Development Center, SHDC12015131, SHDC12015302; Medical Engineering Cross Research Foundation of Shanghai Jiao Tong University, YG2015MS47

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Abstract: Depression is a highly heterogeneous syndrome. Homogeneous subtypes according to symptomatology of illness may contribute to development of individualized treatment, assessment on outcomes and prognosis. Latent class analysis is a flexible statistical approach to determine classes with similar symptom profiles in a heterogeneous group, which has been widely used in data-driven subtyping of depression to increase accuracy of subtyping. This article reviewed existing symptom-based subtypes of depression and findings of researches on latent class analysis based illness subtyping.

Key words: depression, subtyping, latent class analysis

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