Psychological Medicine

Original Articles

Predicting the onset of major depression in primary care: international validation of a risk prediction algorithm from Spain

J. Á. Bellóna1 c1, J. de Dios Lunaa2, M. Kinga3, B. Moreno-Küstnera4, I. Nazaretha5, C. Montón-Francoa6, M. J. GildeGómez-Barragána7, M. Sánchez-Celayaa8, M. Á. Díaz-Barreirosa9, C. Vicensa10, J. A. Cervillaa11, I. Švaba12, H.-I. Maaroosa13, M. Xaviera14, M. I. Geerlingsa15, S. Saldiviaa16, B. Gutiérreza11, E. Motricoa17, M. T. Martínez-Cañavatea18, B. Oliván-Blázqueza19, M. S. Sánchez-Artiagaa20, S. Marcha21, M. del Mar Muñoz-Garcíaa22, A. Vázquez-Medranoa7, P. Moreno-Perala23 and F. Torres-Gonzáleza11

a1 Centro de Salud El Palo, Unidad de Investigación del Distrito de Atención Primaria de Málaga (redIAPP, grupo SAMSERAP); Departamento de Medicina Preventiva, Universidad de Málaga, Spain;

a2 Departamento de Bioestadística (redIAPP, grupo SAMSERAP), Universidad de Granada, Spain;

a3 Department of Mental Health Sciences, University College London, UK;

a4 Fundación IMABIS; Unidad de Investigación del Distrito de Atención Primaria de Málaga (redIAPP, grupo SAMSERAP); Departamento de Personalidad, Evaluación y Tratamiento Psicológico, Universidad de Málaga, Spain;

a5 Department of Primary care and Population Health, University College London and Medical Research Council General Practice Research Framework, UK;

a6 Centro de Salud Casablanca. (redIAPP, grupo Aragón); Departamento de Medicina y Psiquiatría, Universidad de Zaragoza, Spain;

a7 Unidad Docente de Medicina Familiar y Comunitaria de La Rioja, Servicio Riojano de la Salud, Logroño, La Rioja, Spain;

a8 Unidad Docente de Medicina Familiar y Comunitaria, Área I de Atención Primaria, Madrid, Coordinadora de Investigación de la Sociedad Española de Medicina Familiar y Comunitaria, Spain;

a9 Centro de Salud Vecindario, Gerencia de Atención Primaria de Gran Canaria, Servicio Canario de Salud, Las Palmas, Spain;

a10 Centro de Salud son Serra-La Vileta, Unidad Docente de Medicina Familiar y Comunitaria de Mallorca, Instituto Balear de la Salud (redIAPP, grupo Baleares), Palma de Mallorca, Illes Balears, Spain;

a11 CIBERSAM, Departamento de Psiquiatría y Medicina legal, Universidad de Granada, Spain;

a12 Department of Family Medicine, University of Ljubljana, Slovenia;

a13 Faculty of Medicine, University of Tartu, Estonia;

a14 Faculdade Ciências Médicas, University of Lisbon, Portugal;

a15 University Medical Centre, Utrecht, The Netherlands;

a16 Departamento de Psiquiatría y Salud Mental, Universidad de Concepción, Chile;

a17 Fundación IMABIS, Unidad de Investigación del Distrito de Atención Primaria de Málaga (redIAPP, grupo SAMSERAP); Departamento de Psicología Social, Universidad de Málaga, Spain;

a18 Fundación IAVANTE, Granada, Spain;

a19 Unidad de Investigación de Atención Primaria (redIAPP, grupo Aragón); Instituto Aragonés de Ciencias de la Salud, Zaragoza, Spain;

a20 Centro de Salud Condes de Barcelona-Boadilla, Área 6 de Atención Primaria, Madrid, Spain;

a21 Unidad de Investigación de Atención Primaria de Baleares (redIAPP, grupo Baleares), Mallorca, Spain;

a22 Departamento de Psiquiatría y Medicina legal, Universidad de Granada, Spain;

a23 Fundación IMABIS, Unidad de Investigación del Distrito de Atención Primaria de Málaga (redIAPP, grupo SAMSERAP), Málaga, Spain

Abstract

Background The different incidence rates of, and risk factors for, depression in different countries argue for the need to have a specific risk algorithm for each country or a supranational risk algorithm. We aimed to develop and validate a predictD-Spain risk algorithm (PSRA) for the onset of major depression and to compare the performance of the PSRA with the predictD-Europe risk algorithm (PERA) in Spanish primary care.

Method A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multi-level logistic regression and inverse probability weighting to build the PSRA. In Spain (4574), Chile (2133) and another five European countries (5184), 11 891 non-depressed adult primary care attendees formed our at-risk population. The main outcome was DSM-IV major depression (CIDI).

Results Six variables were patient characteristics or past events (sex, age, sex×age interaction, education, physical child abuse, and lifetime depression) and six were current status [Short Form 12 (SF-12) physical score, SF-12 mental score, dissatisfaction with unpaid work, number of serious problems in very close persons, dissatisfaction with living together at home, and taking medication for stress, anxiety or depression]. The C-index of the PSRA was 0.82 [95% confidence interval (CI) 0.79–0.84]. The Integrated Discrimination Improvement (IDI) was 0.0558 [standard error (s.e.)=0.0071, Zexp=7.88, p<0.0001] mainly due to the increase in sensitivity. Both the IDI and calibration plots showed that the PSRA functioned better than the PERA in Spain.

Conclusions The PSRA included new variables and afforded an improved performance over the PERA for predicting the onset of major depression in Spain. However, the PERA is still the best option in other European countries.

(Received July 15 2010)

(Revised February 23 2011)

(Accepted March 02 2011)

(Online publication April 05 2011)

Correspondence

c1 Address for correspondence: J. Á. Bellón, M.D., Ph.D., Departamento de Medicina Preventiva, Facultad de Medicina, Universidad de Málaga, Campus de Teatinos, 29071 Málaga, Spain. (Email: JABELLON@terra.es)

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