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学科主题: 精神卫生
题名:
MAJOR DEPRESSIVE DISORDER SUBTYPES TO PREDICT LONG-TERM COURSE
作者: van Loo, Hanna M.1; Cai, Tianxi2; Gruber, Michael J.3; Li, Junlong2; de Jonge, Peter1; Petukhova, Maria3; Rose, Sherri3; Sampson, Nancy A.3; Schoevers, Robert A.1; Wardenaar, Klaas J.1; Wilcox, Marsha A.4; Al-Hamzawi, Ali Obaid5; Andrade, Laura Helena6; Bromet, Evelyn J.7; Bunting, Brendan8; Fayyad, John9; Florescu, Silvia E.10; Gureje, Oye11; Hu, Chiyi12; Huang, Yueqin13; Levinson, Daphna14; Medina-Mora, Maria Elena15; Nakane, Yoshibumi16; Posada-Villa, Jose17; Scott, Kate M.18; Xavier, Miguel19; Zarkov, Zahari20; Kessler, Ronald C.3
关键词: epidemiology ; depression ; anxiety ; anxiety disorders ; suicide ; self-harm ; panic attacks
刊名: DEPRESSION AND ANXIETY
发表日期: 2014-09-01
DOI: 10.1002/da.22233
卷: 31, 期:9, 页:765-777
收录类别: SCI ; SSCI
文章类型: Article
WOS标题词: Social Sciences ; Science & Technology
类目[WOS]: Psychology, Clinical ; Psychiatry ; Psychology
研究领域[WOS]: Psychology ; Psychiatry
关键词[WOS]: RECURSIVE PARTITIONING ANALYSIS ; WORLD-HEALTH-ORGANIZATION ; COMMON MENTAL-DISORDERS ; LARGE-SAMPLE ; GENERAL-POPULATION ; ANXIETY DISORDERS ; RISK ; COMORBIDITY ; INPATIENTS ; REMISSION
英文摘要:

BackgroundVariation in the course of major depressive disorder (MDD) is not strongly predicted by existing subtype distinctions. A new subtyping approach is considered here.

MethodsTwo data mining techniques, ensemble recursive partitioning and Lasso generalized linear models (GLMs), followed by k-means cluster analysis are used to search for subtypes based on index episode symptoms predicting subsequent MDD course in the World Mental Health (WMH) surveys. The WMH surveys are community surveys in 16 countries. Lifetime DSM-IV MDD was reported by 8,261 respondents. Retrospectively reported outcomes included measures of persistence (number of years with an episode, number of years with an episode lasting most of the year) and severity (hospitalization for MDD, disability due to MDD).

ResultsRecursive partitioning found significant clusters defined by the conjunctions of early onset, suicidality, and anxiety (irritability, panic, nervousness-worry-anxiety) during the index episode. GLMs found additional associations involving a number of individual symptoms. Predicted values of the four outcomes were strongly correlated. Cluster analysis of these predicted values found three clusters having consistently high, intermediate, or low predicted scores across all outcomes. The high-risk cluster (30.0% of respondents) accounted for 52.9-69.7% of high persistence and severity, and it was most strongly predicted by index episode severe dysphoria, suicidality, anxiety, and early onset. A total symptom count, in comparison, was not a significant predictor.

ConclusionsDespite being based on retrospective reports, results suggest that useful MDD subtyping distinctions can be made using data mining methods. Further studies are needed to test and expand these results with prospective data. (C) 2014 Wiley Periodicals, Inc.

语种: 英语
所属项目编号: R01 MH070884 ; R13-MH066849 ; R01-MH069864 ; R01 DA016558 ; FIRCA R03-TW006481 ; 91812607 ; 03/00204-3 ; H13-SHOGAI-023 ; H14-TOKUBETSU-026 ; H16-KOKORO-013 ; R03 TW006481-01 ; INPRFMDIES 4280 ; CONACyT-G30544-H ; RO1-MH61905 ; 044708
项目资助者: National Institute of Mental Health (NIMH) ; John D. and Catherine T. MacArthur Foundation ; Pfizer Foundation ; U.S. Public Health Service ; Fogarty International Center ; Pan American Health Organization ; Eli Lilly &amp ; Company Foundation ; Ortho-McNeil Pharmaceutical, Inc. ; GlaxoSmithKline ; Sanofi Aventis ; Bristol-Myers Squibb ; VICI from the Netherlands Research Foundation (NWO-ZonMW) ; State of Sao Paulo Research Foundation (FAPESP) ; Ministry of Health ; National Center for Public Health Protection ; Shenzhen Bureau of Health ; Shenzhen Bureau of Science, Technology, and Information ; Ministry of Social Protection ; Japanese and European funds through United Nations Development Group Iraq Trust Fund (UNDG ITF) ; Israel National Institute for Health Policy and Health Services Research ; National Insurance Institute of Israel ; Japan Ministry of Health, Labour and Welfare ; Lebanese Ministry of Public Health ; WHO (Lebanon) ; National Institute of Health/Fogarty International Center ; Sheikh Hamdan Bin Rashid Al Maktoum Award for Medical Sciences ; AstraZeneca ; Eli Lilly ; Hikma Pharm ; Pfizer ; Roche ; Sanofi-Aventis ; Servier ; Novartis ; National Institute of Psychiatry Ramon de la Fuente ; National Council on Science and Technology ; PanAmerican Health Organization (PAHO) ; New Zealand Ministry of Health ; Alcohol Advisory Council ; Health Research Council ; WHO (Geneva) ; WHO (Nigeria) ; Federal Ministry of Health, Abuja, Nigeria ; Health and Social Care Research and Development Division of the Public Health Agency ; Champalimaud Foundation ; Gulbenkian Foundation ; Foundation for Science and Technology (FCT) ; Ministry of Public Health ; U.S. National Institute of Mental Health ; National Institute of Drug Abuse (NIDA) ; Substance Abuse and Mental Health Services Administration (SAMHSA) ; Robert Wood Johnson Foundation (RWJF) ; John W. Alden Trust ; Janssen Pharmaceuticals
WOS记录号: WOS:000342668100007
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bjmu.edu.cn/handle/400002259/65765
Appears in Collections:北京大学精神卫生研究所_期刊论文

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作者单位: 1.Univ Coll Ibadan Hosp, Dept Psychiat, Ibadan, Nigeria
2.Peking Univ, Inst Mental Hlth, Beijing 100871, Peoples R China
3.Minist Hlth, Mental Hlth Serv, Dept Res & Planning, Jerusalem, Israel
4.Nagasaki Int Univ, Fac Human Sociol, Dept Social Work, Nagasaki, Japan
5.Harvard Univ, Sch Med, Dept Biostat, Boston, MA 02115 USA
6.Al Qadisia Univ, Dept Psychiat, Coll Med, Diwania, Iraq
7.Natl Sch Publ Hlth Management & Profess Dev, Bucharest, Romania
8.Univ Groningen, Univ Med Ctr Groningen, Dept Psychiat, Groningen, Netherlands
9.Harvard Univ, Sch Med, Dept Hlth Care Policy, Boston, MA 02115 USA
10.Johnson & Johnson Pharmaceut Res & Dev, Titusville, NJ USA
11.Univ Sao Paulo, Sch Med, Sect Psychiat Epidemiol LIM 23, Dept & Inst Psychiat, Sao Paulo, Brazil
12.SUNY Stony Brook, Stony Brook, NY 11794 USA
13.Univ Ulster, Psychol Res Inst, Coleraine BT52 1SA, Londonderry, North Ireland
14.St George Hosp Univ Med Ctr, Inst Dev Res Advocacy & Appl Care, Beirut, Lebanon
15.Shenzhen Kangning Hosp, Shenzhen Inst Mental Hlth, Shenzhen, Guangdong, Peoples R China
16.Inst Nacl Psiquiatria Ramon de la Fuente, Mexico City, DF, Mexico
17.Univ Nova Lisboa, Dept Mental Hlth, P-1200 Lisbon, Portugal
18.Univ Colegio Mayor Cundinamarca, Bogota, Colombia
19.Univ Otago, Dept Psychol Med, Dunedin, New Zealand
20.Natl Ctr Publ Hlth & Anal, Dept Mental Hlth, Sofia, Bulgaria

Recommended Citation:
van Loo, Hanna M.,Cai, Tianxi,Gruber, Michael J.,et al. MAJOR DEPRESSIVE DISORDER SUBTYPES TO PREDICT LONG-TERM COURSE[J]. DEPRESSION AND ANXIETY,2014,31(9):765-777.
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