Brazilian Journal of Psychiatry (Jul 2023)

Identifying Depression Early in Adolescence: assessing the performance of a risk score for future onset of depression in an independent Brazilian sample

  • Graccielle R. Cunha,
  • Arthur Caye,
  • Pedro Pan,
  • Helen L. Fisher,
  • Rivka Pereira,
  • Carolina Ziebold,
  • Rodrigo Bressan,
  • Eurípedes Constantino Miguel,
  • Giovanni A. Salum,
  • Luis Augusto Rohde,
  • Brandon A. Kohrt,
  • Valeria Mondelli,
  • Christian Kieling,
  • Ary Gadelha

DOI
https://doi.org/10.47626/1516-4446-2022-2775
Journal volume & issue
Vol. 45, no. 3
pp. 242 – 248

Abstract

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Objective: The Identifying Depression Early in Adolescence Risk Score (IDEA-RS) was recently developed in Brazil using data from the Pelotas 1993 Birth Cohort to estimate the individualized probability of developing depression in adolescence. This model includes 11 sociodemographic variables and has been assessed in longitudinal studies from four other countries. We aimed to test the performance of IDEA-RS in an independent, community-based, school-attending sample within the same country: the Brazilian High-Risk Cohort. Methods: Standard external validation, refitted, and case mix-corrected models were used to predict depression among 1442 youth followed from a mean age of 13.5 years at baseline to 17.7 years at follow-up, using probabilities calculated with IDEA-RS coefficients. Results: The area under the curve was 0.65 for standard external validation, 0.70 for the case mix-corrected model, and 0.69 for the refitted model, with discrimination consistently above chance for predicting depression in the new dataset. There was some degree of miscalibration, corrected by model refitting (calibration-in-the-large reduced from 0.77 to 0). Conclusion: IDEA-RS was able to parse individuals with higher or lower probability of developing depression beyond chance in an independent Brazilian sample. Further steps should include model improvements and additional studies in populations with high levels of subclinical symptoms to improve clinical decision making.

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