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使用自我报告有抑郁症的青少年早期样本评估抑郁症风险预测模型。

Assessing a prediction model for depression risk using an early adolescent sample with self-reported depression.

作者信息

Xu Eileen Y, MacSweeney Niamh, Thng Gladi, Barbu Miruna C, Shen Xueyi, Kwong Alex S F, Romaniuk Liana, McIntosh Andrew, Lawrie Stephen M, Whalley Heather C

机构信息

Division of Psychiatry University of Edinburgh Royal Edinburgh Hospital Edinburgh UK.

出版信息

JCPP Adv. 2024 Sep 3;5(2):e12276. doi: 10.1002/jcv2.12276. eCollection 2025 Jun.

DOI:10.1002/jcv2.12276
PMID:40519960
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12159326/
Abstract

BACKGROUND

Major depressive disorder (MDD) in adolescence is a risk factor for poor physical and psychiatric outcomes in adulthood, with earlier age of onset associated with poorer outcomes. Identifying Depression Early in Adolescence Risk Score (IDEA-RS) is a model for predicting MDD in youth aged >15 years, but replication in younger samples (<15 years) is lacking. Here, we tested IDEA-RS in a younger sample (9-11 years) to assess whether IDEA-RS could be applied to earlier onset depression.

METHODS

We applied IDEA-RS predictor weights to 9854 adolescents (9-11 years) from the Adolescent Brain Cognitive Development (ABCD) Study, United States. We derived incident depression outcomes from self-reported data at 2-year follow-up (11-13 years): incident MDD and increase in depression symptoms (DS). Sensitivity analyses were conducted using parent-reported data. We assessed accuracy and calibration in predicting self-reported incident depression and compared this to a refitted model with predictor weights derived in ABCD. Lastly, we tested associations between IDEA-RS predictors and self-reported incident depression.

RESULTS

External replication yielded better-than-chance discriminative capacity for self-reported incident depression (MDD: AUC = 61.4%, 95% CI = 53.5%-69.4%; DS: AUC = 57.9%, 95% CI = 54.6%-61.3%) but showed poor calibration with overly extreme risk estimates. Re-estimating predictor weights improved discriminative capacity (MDD: AUC = 75.9%, 95% CI = 70.3%-81.4%; DS: AUC = 64.8%, 95% CI = 61.9%-67.7%) and calibration. IDEA-RS predictors 'poorest level of relationship with the primary caregiver' (OR = 4.25, 95% CI = 1.73-10.41) and 'high/highest levels of family conflict' (OR = 3.36 [95% CI = 1.34-8.43] and OR = 3.76 [95% CI = 1.50-9.38], respectively) showed greatest associations with self-reported incident MDD.

CONCLUSIONS

While IDEA-RS yields better-than-chance predictions on external replication, accuracy is improved when differences between samples, such as case-control mix, are adjusted for. IDEA-RS may be more suited to research settings with sufficient data for refitting. Altogether, we find that IDEA-RS can be generalisable to early adolescents after refitting and that family dysfunction may be especially impactful for this period of development.

摘要

背景

青少年重度抑郁症(MDD)是成年期身体和精神状况不佳的一个风险因素,发病年龄越早,预后越差。青少年早期抑郁症风险识别评分(IDEA-RS)是一种预测15岁以上青少年患MDD的模型,但在年龄更小的样本(<15岁)中缺乏重复验证。在此,我们在一个年龄更小的样本(9-11岁)中测试了IDEA-RS,以评估其是否可应用于更早发病的抑郁症。

方法

我们将IDEA-RS预测因子权重应用于来自美国青少年大脑认知发展(ABCD)研究的9854名青少年(9-11岁)。我们从2年随访(11-13岁)时的自我报告数据中得出新发抑郁症结局:新发MDD和抑郁症状(DS)增加。使用家长报告的数据进行敏感性分析。我们评估了预测自我报告的新发抑郁症的准确性和校准情况,并将其与使用在ABCD中得出的预测因子权重重新拟合的模型进行比较。最后,我们测试了IDEA-RS预测因子与自我报告的新发抑郁症之间的关联。

结果

外部重复验证显示,对于自我报告的新发抑郁症具有高于随机水平的判别能力(MDD:曲线下面积[AUC]=61.4%,95%置信区间[CI]=53.5%-69.4%;DS:AUC=57.9%,95%CI=54.6%-61.3%),但校准情况较差,风险估计过于极端。重新估计预测因子权重提高了判别能力(MDD:AUC=75.9%,95%CI=70.3%-81.4%;DS:AUC=64.8%,95%CI=61.9%-67.7%)和校准情况。IDEA-RS预测因子“与主要照顾者关系最差水平”(比值比[OR]=4.25,95%CI=1.73-10.41)和“家庭冲突高/最高水平”(OR分别为3.36[95%CI=1.34-8.43]和3.76[95%CI=1.50-9.38])与自我报告的新发MDD关联最大。

结论

虽然IDEA-RS在外部重复验证时预测效果优于随机水平,但在对样本差异(如病例对照组合)进行调整后,准确性会提高。IDEA-RS可能更适合有足够数据进行重新拟合的研究环境。总体而言,我们发现IDEA-RS在重新拟合后可推广到早期青少年,并且家庭功能障碍在此发育阶段可能影响尤其大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfed/12159326/1de26209287d/JCV2-5-e12276-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfed/12159326/addd52964bf0/JCV2-5-e12276-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfed/12159326/34353ee777c5/JCV2-5-e12276-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfed/12159326/1de26209287d/JCV2-5-e12276-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfed/12159326/addd52964bf0/JCV2-5-e12276-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfed/12159326/34353ee777c5/JCV2-5-e12276-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfed/12159326/1de26209287d/JCV2-5-e12276-g002.jpg

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