在青春期早期识别抑郁症:在一个独立的巴西样本中评估未来抑郁症发病的风险评分的表现

G. R. Cunha, A. Caye, P. Pan, H. Fisher, Rivka B. Pereira, Carolina Ziebold, R. Bressan, B. Kohrt, V. Mondelli, C. Kieling, A. Gadelha
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摘要

目的:最近在巴西开发了识别青少年早期抑郁风险评分(IDEA-RS),使用1993年Pelotas出生队列的数据来估计青少年患抑郁症的个体化概率。该模型包括11个社会人口变量,并已在其他四个国家的纵向研究中进行了评估。我们的目的是在一个独立的、以社区为基础的、在同一国家上学的样本中测试IDEA-RS的性能:巴西高危队列。方法:采用标准外部验证模型、修正模型和病例混合校正模型预测1442名青少年的抑郁症,随访时平均年龄为13.5岁至17.7岁,使用IDEA-RS系数计算概率。结果:标准外部验证的曲线下面积为0.65,病例混合修正模型为0.70,修正模型为0.69,在新数据集中预测抑郁症的辨别率始终高于机会。通过模型修正,存在一定程度的校准错误(校准量从0.77降至0)。结论:IDEA-RS能够在独立的巴西样本中分析出患抑郁症概率较高或较低的个体。进一步的步骤应包括改进模型和在亚临床症状严重的人群中进行更多的研究,以改善临床决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Depression Early in Adolescence: assessing the performance of a risk score for future onset of depression in an independent Brazilian sample
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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