Skip to main content
    • Aa
    • Aa

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity

  • K. J. Wardenaar (a1), H. M. van Loo (a1), T. Cai (a2), M. Fava (a3), M. J. Gruber (a4), J. Li (a2), P. de Jonge (a1), A. A. Nierenberg (a5), M. V. Petukhova (a4), S. Rose (a4), N. A. Sampson (a4), R. A. Schoevers (a1), M. A. Wilcox (a6), J. Alonso (a7), E. J. Bromet (a8), B. Bunting (a9), S. E. Florescu (a10), A. Fukao (a11), O. Gureje (a12), C. Hu (a13), Y. Q. Huang (a14), A. N. Karam (a15), D. Levinson (a16), M. E. Medina Mora (a17), J. Posada-Villa (a18), K. M. Scott (a19), N. I. Taib (a20), M. C. Viana (a21), M. Xavier (a22), Z. Zarkov (a23) and R. C. Kessler (a4)...

Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question.


Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes.


Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6–72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors.


Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Corresponding author
* Address for correspondence: R. C. Kessler, Ph.D., Department of Health Care Policy, Harvard Medical School, Boston, MA, USA. (Email:
Hide All
C Andreescu , BH Mulsant , PR Houck , EM Whyte , S Mazumdar , AY Dombrovski , BG Pollock , CF Reynolds 3rd (2008). Empirically derived decision trees for the treatment of late-life depression. American Journal of Psychiatry 165, 855862.

RA Berk (2008). Statistical Learning from a Regression Perspective. Springer: New York, NY.

C Bottomley , I Nazareth , F Torres-Gonzalez , I Svab , HI Maaroos , MI Geerlings , M Xavier , S Saldivia , M King (2010). Comparison of risk factors for the onset and maintenance of depression. British Journal of Psychiatry 196, 1317.

M Candrian , A Farabaugh , DA Pizzagalli , L Baer , M Fava (2007). Perceived stress and cognitive vulnerability mediate the effects of personality disorder comorbidity on treatment outcome in major depressive disorder: a path analysis study. Journal of Nervous and Mental Disease 195, 729737.

N Carragher , G Adamson , B Bunting , S McCann (2009). Subtypes of depression in a nationally representative sample. Journal of Affective Disorders 113, 8899.

YJ Chang , LJ Chen , KP Chung , MS Lai (2012). Risk groups defined by Recursive Partitioning Analysis of patients with colorectal adenocarcinoma treated with colorectal resection. BMC Medical Research Methodology 12, 2.

ST Chao , SA Koyfman , N Woody , L Angelov , SL Soeder , CA Reddy , LA Rybicki , T Djemil , JH Suh (2012). Recursive partitioning analysis index is predictive for overall survival in patients undergoing spine stereotactic body radiation therapy for spinal metastases. International Journal of Radiation Oncology, Biology, Physics 82, 17381743.

LA Clark , D Watson (2006). Distress and fear disorders: an alternative empirically based taxonomy of the ‘mood’ and ‘anxiety’ disorders. British Journal of Psychiatry 189, 481483.

PJ Cooper , L Murray (1995). Course and recurrence of postnatal depression. Evidence for the specificity of the diagnostic concept. British Journal of Psychiatry 166, 191195.

M Fink , AJ Rush , R Knapp , K Rasmussen , M Mueller , TA Rummans , K O'Connor , M Husain , M Biggs , S Bailine , CH Kellner (2007). DSM melancholic features are unreliable predictors of ECT response: a CORE publication. Journal of ECT 23, 139146.

J Friedman , T Hastie , R Tibshirani (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software 33, 122.

JM Haro , S Arbabzadeh-Bouchez , TS Brugha , G de Girolamo , ME Guyer , R Jin , JP Lepine , F Mazzi , B Reneses , G Vilagut , NA Sampson , RC Kessler (2006). Concordance of the Composite International Diagnostic Interview Version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO World Mental Health surveys. International Journal of Methods in Psychiatric Research 15, 167180.

G Hasler , G Northoff (2011). Discovering imaging endophenotypes for major depression. Molecular Psychiatry 16, 604619.

T Hastie , R Tibshirani , J Friedman (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd edn.Springer: New York, NY.

MA Ilgen , K Downing , K Zivin , KJ Hoggatt , HM Kim , D Ganoczy , KL Austin , JF McCarthy , JM Patel , M Valenstein (2009). Exploratory data mining analysis identifying subgroups of patients with depression who are at high risk for suicide. Journal of Clinical Psychiatry 70, 14951500.

FA Jain , AM Hunter , JO Brooks 3rd, AF Leuchter (2013). Predictive socioeconomic and clinical profiles of antidepressant response and remission. Depression and Anxiety 30, 624630.

G James , D Witten , T Hastie , R Tibshirani (2013). An Introduction to Statistical Learning: With Applications in R. Springer: New York, NY.

RC Kessler , GP Amminger , S Aguilar-Gaxiola , J Alonso , S Lee , TB Ustun (2007). Age of onset of mental disorders: a review of recent literature. Current Opinion in Psychiatry 20, 359364.

RC Kessler , TB Üstün (2004). The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI). International Journal of Methods in Psychiatric Research 13, 93121.

B Knäuper , CF Cannell , N Schwarz , ML Bruce , RC Kessler (1999). Improving accuracy of major depression age-of-onset reports in the US National Comorbidity Survey. International Journal of Methods in Psychiatric Research 8, 3948.

F Lamers , M Burstein , JP He , S Avenevoli , J Angst , KR Merikangas (2012). Structure of major depressive disorder in adolescents and adults in the US general population. British Journal of Psychiatry 201, 143150.

T Lumley (2004). Analysis of complex survey samples. Journal of Statistical Software 9, 119.

R Musil , P Zill , F Seemuller , B Bondy , S Meyer , I Spellmann , W Bender , M Adli , I Heuser , R Fisher , W Gaebel , W Maier , M Rietschel , D Rujescu , R Schennach , HJ Moller , M Riedel (2013). Genetics of emergent suicidality during antidepressive treatment – data from a naturalistic study on a large sample of inpatients with a major depressive episode. European Neuropsychopharmacology 23, 663674.

JC Nelson , Q Zhang , W Deberdt , LB Marangell , O Karamustafalioglu , IA Lipkovich (2012). Predictors of remission with placebo using an integrated study database from patients with major depressive disorder. Current Medical Research and Opinion 28, 325334.

BW Penninx , AT Beekman , JH Smit , FG Zitman , WA Nolen , P Spinhoven , P Cuijpers , PJ De Jong , HW Van Marwijk , WJ Assendelft , K Van Der Meer , P Verhaak , M Wensing , R De Graaf , WJ Hoogendijk , J Ormel , R Van Dyck (2008). The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods. International Journal of Methods in Psychiatric Research 17, 121140.

DA Pizzagalli (2011). Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology 36, 183206.

M Rabinoff , CM Kitchen , IA Cook , AF Leuchter (2011). Evaluation of quantitative EEG by classification and regression trees to characterize responders to antidepressant and placebo treatment. Open Medical Informatics Journal 5, 18.

JD Rabinowitz , TJ Silhavy (2013). Systems biology: metabolite turns master regulator. Nature 500, 283284.

BS Rayner , GA Figtree , T Sabaretnam , P Shang , J Mazhar , JC Weaver , WN Lay , PK Witting , SN Hunyor , SM Grieve , LM Khachigian , R Bhindi (2013). Selective inhibition of the master regulator transcription factor egr-1 with catalytic oligonucleotides reduces myocardial injury and improves left ventricular systolic function in a preclinical model of myocardial infarction. Journal of the American Heart Association 2, e000023.

M Riedel , HJ Moller , M Obermeier , M Adli , M Bauer , K Kronmuller , P Brieger , G Laux , W Bender , I Heuser , J Zeiler , W Gaebel , R Schennach-Wolff , V Henkel , F Seemuller (2011). Clinical predictors of response and remission in inpatients with depressive syndromes. Journal of Affective Disorders 133, 137149.

B Ryu , DS Kim , AM Deluca , RM Alani (2007). Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression. PloS One 2, e594.

F Seemuller , M Riedel , M Obermeier , M Bauer , M Adli , C Mundt , F Holsboer , P Brieger , G Laux , W Bender , I Heuser , J Zeiler , W Gaebel , M Jager , V Henkel , HJ Moller (2009). The controversial link between antidepressants and suicidality risks in adults: data from a naturalistic study on a large sample of in-patients with a major depressive episode. International Journal of Neuropsychopharmacology 12, 181189.

C Strobl , J Malley , G Tutz (2009). An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychological Methods 14, 323348.

R Uher , MZ Dernovsek , O Mors , J Hauser , D Souery , A Zobel , W Maier , N Henigsberg , P Kalember , M Rietschel , A Placentino , J Mendlewicz , KJ Aitchison , P McGuffin , A Farmer (2011). Melancholic, atypical and anxious depression subtypes and outcome of treatment with escitalopram and nortriptyline. Journal of Affective Disorders 132, 112120.

MJ van der Laan , EC Polley , AE Hubbard (2007). Super learner. Statistical Applications in Genetics and Molecular Biology 6, Article 25.

MJ van der Laan , S Rose (2011). Targeted Learning: Causal Inference for Observational and Experimental Data. Springer: New York, NY.

HM van Loo , T Cai , MJ Gruber , J Li , P de Jonge , M Petukhova , S Rose , NA Sampson , RA Schoevers , KJ Wardenaar , MA Wilcox , A Al-Hamzawi , LH Andrade , EJ Bromet , B Bunting , J Fayyad , SE Florescu , O Gureje , C Hu , Y Huang , D Levinson , ME Medina-Mora , Y Nakane , J Posada-Villa , KM Scott , M Xavier , Z Zarkov , RC Kessler (2014). Major depressive disorder subtypes to predict long-term course. Depression and Anxiety. Published online: 14January2014. doi: 10.1002/da.22233.

HM van Loo , P de Jonge , JW Romeijn , RC Kessler , RA Schoevers (2012). Data-driven subtypes of major depressive disorder: a systematic review. BMC Medicine 10, 156.

MR Von Korff , KM Scott , O Gureje (2009). Global Perspectives on Mental-Physical Comorbidity in the WHO World Mental Health Surveys. Cambridge University Press: New York, NY.

E Vrieze , K Demyttenaere , R Bruffaerts , D Hermans , DA Pizzagalli , P Sienaert , T Hompes , P de Boer , M Schmidt , S Claes (2014). Dimensions in major depressive disorder and their relevance for treatment outcome. Journal of Affective Disorders 155, 3541.

H Zhang , BH Singer (2010). Recursive Partitioning and Applications, 2nd edn. Springer: New York, NY.

H Zou , T Hastie (2005). Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67, 301320.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Psychological Medicine
  • ISSN: 0033-2917
  • EISSN: 1469-8978
  • URL: /core/journals/psychological-medicine
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Altmetric attention score

Full text views

Total number of HTML views: 5
Total number of PDF views: 74 *
Loading metrics...

Abstract views

Total abstract views: 320 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 17th October 2017. This data will be updated every 24 hours.