Identifying Depression Early in Adolescence: assessing the performance of a risk score for future onset of depression in an independent Brazilian sample
Braz. J. Psychiatry (São Paulo, 1999, Impr.)
; 45(3): 242-248, May-June 2023. tab, graf
Article
em En
|
LILACS-Express
| LILACS
| ID: biblio-1447578
Biblioteca responsável:
BR1.1
ABSTRACT
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
LILACS
Tipo de estudo:
Etiology_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
País/Região como assunto:
America do sul
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Brasil
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article
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Project document