Development and Validation of an International Risk Prediction Algorithm for Episodes of Major Depression in General Practice Attendees: The PredictD Study | Depressive Disorders | JAMA Psychiatry | JAMA Network
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Goldberg  DPHuxley  P Common Mental Disorders: A Bio-Social Model.  London, England Tavistock/Routledge1992;
Thornicroft  GSartorius  N The course and outcome of depression in different cultures: 10-year follow-up of the WHO Collaborative Study on the Assessment of Depressive Disorders.  Psychol Med 1993;23 (4) 1023- 1032PubMedGoogle ScholarCrossref
Cassano  PFava  M Depression and public health: an overview.  J Psychosom Res 2002;53 (4) 849- 857PubMedGoogle ScholarCrossref
Weich  SLewis  G Poverty, unemployment, and common mental disorders: population based cohort study.  BMJ 1998;317 (7151) 115- 119PubMedGoogle ScholarCrossref
Weich  SLewis  G Material standard of living, social class, and the prevalence of the common mental disorders in Great Britain.  J Epidemiol Community Health 1998;52 (1) 8- 14PubMedGoogle ScholarCrossref
Weich  SSloggett  ALewis  G Social roles and gender difference in the prevalence of common mental disorders.  Br J Psychiatry 1998;173489- 493PubMedGoogle ScholarCrossref
Stansfeld  SAFuhrer  RShipley  MJMarmot  MG Work characteristics predict psychiatric disorder: prospective results from the Whitehall II Study.  Occup Environ Med 1999;56 (5) 302- 307PubMedGoogle ScholarCrossref
Bruce  MLHoff  RA Social and physical health risk factors for first-onset major depressive disorder in a community sample.  Soc Psychiatry Psychiatr Epidemiol 1994;29 (4) 165- 171PubMedGoogle Scholar
Angst  JGamma  AEndrass  J Risk factors for the bipolar and depression spectra.  Acta Psychiatr Scand Suppl 2003; (418) 15- 19PubMedGoogle Scholar
Salokangas  RKRPoutanen  O Risk factors for depression in primary care: findings of the TADEP project.  J Affect Disord 1998;48 (2-3) 171- 180PubMedGoogle ScholarCrossref
Prince  MJHarwood  RHBlizard  RAThomas  AMann  AH Impairment, disability and handicap as risk factors for depression in old age: the Gospel Oak Project V.  Psychol Med 1997;27 (2) 311- 321PubMedGoogle ScholarCrossref
Prince  MJHarwood  RHBlizard  RAThomas  AMann  AH Social support deficits, loneliness and life events as risk factors for depression in old age: the Gospel Oak Project VI.  Psychol Med 1997;27 (2) 323- 332PubMedGoogle ScholarCrossref
Prince  MJHarwood  RHThomas  AMann  AH A prospective population-based cohort study of the effects of disablement and social milieu on the onset and maintenance of late-life depression: the Gospel Oak Project VII.  Psychol Med 1998;28 (2) 337- 350PubMedGoogle ScholarCrossref
Anderson  KMWilson  PWOdell  PMKannel  WB An updated coronary risk profile: a statement for health professionals.  Circulation 1991;83 (1) 356- 362PubMedGoogle ScholarCrossref
King  MWeich  STorres-González  FSvab  IMaaroos  HINeeleman  JXavier  MMorris  RWalker  CBellón-Saameño  JAMoreno-Küstner  BRotar  DRifel  JAluoja  AKalda  RGeerlings  MICarraça  Ide Almeida  MCVicente  BSaldivia  SRioseco  PNazareth  I Prediction of depression in European general practice attendees: the PREDICT study.  BMC Public Health 2006;6 (1) 6PubMedGoogle ScholarCrossref
Robins  LNWing  JWittchen  HUHelzer  JEBabor  TFBurke  JFarmer  AJablenski  APickens  RRegier  DA The Composite International Diagnostic Interview: an epidemiologic instrument suitable for use in conjunction with different diagnostic systems and in different cultures.  Arch Gen Psychiatry 1988;45 (12) 1069- 1077PubMedGoogle ScholarCrossref
World Health Organization, Composite International Diagnostic Interview (CIDI). Version 2.1.  Geneva, Switzerland WHO1997;
Weich  S Risk Factors for the Common Mental Disorders in Primary Care.  Cambridge, England University of Cambridge2001;
Arroll  BKhin  NKerse  N Screening for depression in primary care with two verbally asked questions: cross sectional study.  BMJ 2003;327 (7424) 1144- 1146PubMedGoogle ScholarCrossref
Karasek  RATheorell  T Healthy Work: Stress, Productivity, and the Reconstruction of Working Life.  New York, NY Basic Books1990;
Jenkinson  CLayte  RJenkinson  DLawrence  KPetersen  SPaice  CStradling  J A shorter form health survey: can the SF-12 replicate results from the SF-36 in longitudinal studies?  J Public Health Med 1997;19 (2) 179- 186PubMedGoogle ScholarCrossref
Barbor  TFde la Fuente  JRSaunders  JGrant  M The Alcohol Use Disorders Identification Test: Guidelines for the Use in Primary Health Care.  Geneva, Switzerland World Health Organization1989;
Taylor  JFRosen  RCLeiblum  SR Self-report assessment of female sexual function: psychometric evaluation of the Brief Index of Sexual Functioning for Women.  Arch Sex Behav 1994;23 (6) 627- 643PubMedGoogle ScholarCrossref
Tyrer  P Personality disorder and social functioning. Peck  DFShapiro  CM Measuring Human Problems a Practical Guide. Chichester, NY Wiley & Sons1990;119- 142Google Scholar
Fink  LABernstein  DHandelsman  LFoote  JLovejoy  M Initial reliability and validity of the childhood trauma interview: a new multidimensional measure of childhood interpersonal trauma.  Am J Psychiatry 1995;152 (9) 1329- 1335PubMedGoogle Scholar
King  MSpeck  PThomas  A The Royal Free interview for religious and spiritual beliefs: development and standardization.  Psychol Med 1995;25 (6) 1125- 1134PubMedGoogle ScholarCrossref
Qureshi  NBethea  JModell  BBrennan  PPapageorgiou  ARaeburn  SHapgood  RModell  M Collecting genetic information in primary care: evaluating a new family history tool [published online ahead of print July 29, 2005].  Fam Pract 2005;22 (6) 663- 669PubMedGoogle ScholarCrossref
Spitzer  RLKroenke  KWilliams  JB Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary care evaluation of mental disorders: patient health questionnaire.  JAMA 1999;282 (18) 1737- 1744PubMedGoogle ScholarCrossref
Sproston  KPrimatesta  P Health Survey for England 2002: a Survey Carried out on Behalf of the Department of Health. Volume 1: The Health of Children and Young People.  London, England The Stationery Office2003;
Brugha  TBebbington  PTennant  CHurry  J The List of Threatening Experiences: a subset of 12 life event categories with considerable long-term contextual threat.  Psychol Med 1985;15 (1) 189- 194PubMedGoogle ScholarCrossref
Janssen  IHanssen  MBak  MBijl  RVde Graaf  RVollebergh  W McKenzie  Kvan Os  J Discrimination and delusional ideation.  Br J Psychiatry 2003;18271- 76PubMedGoogle ScholarCrossref
Blaxter  M Health and Lifestyles.  London, England Routledge1990;
 Stata [computer program]. Release 9 College Station, TX StataCorp2007;
Royston  P Multiple imputation of missing values: update of ice.  Stata Journal 2005;5 (4) 527- 536Google Scholar
Schafer  JL Multiple imputation: a primer.  Stat Methods Med Res 1999;8 (1) 3- 15PubMedGoogle ScholarCrossref
Rubin  DB Multiple Imputation for Non-Response in Surveys.  New York, NY John Wiley & Sons1987;
Piccinelli  MWilkinson  G Gender differences in depression: critical review.  Br J Psychiatry 2000;177 (6) 486- 492PubMedGoogle ScholarCrossref
Weissman  MMBland  RCCanino  GJFaravelli  CGreenwald  SHwu  HGJoyce  PRKaram  EGLee  CKLellouch  JLépine  JPNewman  SCRubio-Stipec  MWells  JEWickramaratne  PJWittchen  HYeh  EK Cross-national epidemiology of major depression and bipolar disorder.  JAMA 1996;276 (4) 293- 299PubMedGoogle ScholarCrossref
Harrell  FE Regression Modelling Strategies.  New York, NY Springer2001;
Copas  JB Regression, prediction and shrinkage.  J R Stat Soc Ser B 1983;45311- 354Google Scholar
Cooper  HHedges  LV The Handbook of Research Synthesis.  New York, NY Russell Sage Foundation1994;
Rubenstein  LVRayburn  NRKeeler  EBFord  DERost  KMSherbourne  CD Predicting outcomes of primary care patients with major depression: development of a depression prognosis index.  Psychiatr Serv 2007;58 (8) 1049- 1056PubMedGoogle ScholarCrossref
Pepe  MSJanes  HLongton  GLeisenring  WNewcomb  P Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker.  Am J Epidemiol 2004;159 (9) 882- 890PubMedGoogle ScholarCrossref
Conroy  RMPyörälä  KFitzgerald  APSans  SMenotti  ADe Backer  GDe Bacquer  DDucimetière  PJousilahti  PKeil  UNjølstad  IOganov  RGThomsen  TTunstall-Pedoe  HTverdal  AWedel  HWhincup  PWilhelmsen  LGraham  IMSCORE project group, Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project.  Eur Heart J 2003;24 (11) 987- 1003PubMedGoogle ScholarCrossref
Altman  DGRoyston  P What do we mean by validating a prognostic model?  Stat Med 2000;19 (4) 453- 473PubMedGoogle ScholarCrossref
Moons  KGDonders  ARSteyerberg  EWHarrell  FE Penalized maximum likelihood estimation to directly adjust diagnostic and prognostic prediction models for overoptimism: a clinical example.  J Clin Epidemiol 2004;57 (12) 1262- 1270PubMedGoogle ScholarCrossref
Original Article
December 1, 2008

Development and Validation of an International Risk Prediction Algorithm for Episodes of Major Depression in General Practice Attendees: The PredictD Study

Author Affiliations

Author Affiliations: Departments of Mental Health Sciences (Drs King and Walker and Mr Levy) and Primary Care and Population Sciences (Drs Bottomley and Nazareth), University College London, Medical Research Council General Practice Research Framework (Mr Levy and Dr Nazareth), and Medical Research Council Clinical Trials Unit (Dr Royston), London, and Health Sciences Research Institute, University of Warwick, Coventry (Dr Weich), England; Department of Preventive Medicine, El Palo Health Centre, Malaga (Dr Bellón-Saameño), and Department of Psychiatry, University of Granada, Granada (Drs Moreno and Torres-Gonzalez), Spain; Department of Family Medicine, University of Ljubljana, Ljubljana, Slovenia (Drs Švab, Rotar, and Rifel); Faculty of Medicine, University of Tartu, Tartu, Estonia (Drs Maaroos, Aluoja, and Kalda); University Medical Center, Utrecht, the Netherlands (Drs Neeleman and Geerlings); Faculdade Ciências Médicas, University of Lisbon (Drs Xavier and Gonçalves-Pereira), and Encarnação Health Centre (Dr Carraça), Lisbon, Portugal; and Departamento de Psiquiatría y Salud Mental, Universidad de Concepción, Concepción, Chile (Drs Vicente and Saldivia and Mr Melipillan).

Arch Gen Psychiatry. 2008;65(12):1368-1376. doi:10.1001/archpsyc.65.12.1368

Context  Strategies for prevention of depression are hindered by lack of evidence about the combined predictive effect of known risk factors.

Objectives  To develop a risk algorithm for onset of major depression.

Design  Cohort of adult general practice attendees followed up at 6 and 12 months. We measured 39 known risk factors to construct a risk model for onset of major depression using stepwise logistic regression. We corrected the model for overfitting and tested it in an external population.

Setting  General practices in 6 European countries and in Chile.

Participants  In Europe and Chile, 10 045 attendees were recruited April 2003 to February 2005. The algorithm was developed in 5216 European attendees who were not depressed at recruitment and had follow-up data on depression status. It was tested in 1732 patients in Chile who were not depressed at recruitment.

Main Outcome Measure  DSM-IV major depression.

Results  Sixty-six percent of people approached participated, of whom 89.5% participated again at 6 months and 85.9%, at 12 months. Nine of the 10 factors in the risk algorithm were age, sex, educational level achieved, results of lifetime screen for depression, family history of psychological difficulties, physical health and mental health subscale scores on the Short Form 12, unsupported difficulties in paid or unpaid work, and experiences of discrimination. Country was the tenth factor. The algorithm's average C index across countries was 0.790 (95% confidence interval [CI], 0.767-0.813). Effect size for difference in predicted log odds of depression between European attendees who became depressed and those who did not was 1.28 (95% CI, 1.17-1.40). Application of the algorithm in Chilean attendees resulted in a C index of 0.710 (95% CI, 0.670-0.749).

Conclusion  This first risk algorithm for onset of major depression functions as well as similar risk algorithms for cardiovascular events and may be useful in prevention of depression.