Anxiety onset in adolescents: a machine-learning prediction.
Anxiety onset in adolescents: a machine-learning prediction.
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DOI：
10.1038/s41380-022-01840-z
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发表时间：
2023-02
影响因子：
11
通讯作者：
Artiges, Eric
中科院分区：
文献类型：
--
作者：
Chavanne, Alice;Paillere Martinot, Marie Laure;Penttilae, Jani;Grimmer, Yvonne;Conrod, Patricia;Stringaris, Argyris;van Noort, Betteke;Isensee, Corinna;Becker, Andreas;Banaschewski, Tobias;Bokde, Arun L. W.;Desrivieres, Sylvane;Flor, Herta;Grigis, Antoine;Garavan, Hugh;Gowland, Penny;Heinz, Andreas;Bruehl, Ruediger;Nees, Frauke;Orfanos, Dimitri Papadopoulos;Paus, Tomas;Poustka, Luise;Hohmann, Sarah S.;Millenet, Sabina;Froehner, Juliane;Smolka, Michael;Walter, Henrik;Whelan, Robert;Schumann, Gunter;Martinot, Jean-Luc;Artiges, Eric
最近的纵向研究在青年人中报道了MRI相关的前瞻性焦虑症状在青春期，一个脆弱的时期，为焦虑症的发作。然而，其预测价值尚未确定。通过机器学习算法进行个体预测可能有助于弥合与临床相关性的差距。采用随机森林、支持向量机和Logistic回归算法的投票分类器评估感兴趣灰质体积和心理测量分数在前瞻性临床焦虑检测中的预测相关性。年龄在18-23岁的临床焦虑参与者（N = 156）在14岁时与健康对照组（N = 424）一起进行了调查。Shapley值被提取用于特征重要性的深入解释。对合并焦虑症的前瞻性预测主要依赖于心理测量学特征，并实现了中等性能（接受者工作曲线下面积= 0.68），而广泛性焦虑症（GAD）预测实现了类似的性能。MRI区域体积并没有提高前瞻性合并焦虑症的预测性能，就单独的心理测量功能，但他们提高了GAD的预测性能，尾状核和苍白球体积是其中最有贡献的功能。总之，在非焦虑的14岁青少年中，可以单独预测4-8年后的未来临床焦虑发作。神经质、绝望和情绪症状等心理测量学特征是焦虑症的主要预测因素。神经解剖学数据，如尾状核和苍白球体积，被证明是有价值的广泛性焦虑症，并应包括在前瞻性的临床预测青少年焦虑。
Recent longitudinal studies in youth have reported MRI correlates of prospective anxiety symptoms during adolescence, a vulnerable period for the onset of anxiety disorders. However, their predictive value has not been established. Individual prediction through machine-learning algorithms might help bridge the gap to clinical relevance. A voting classifier with Random Forest, Support Vector Machine and Logistic Regression algorithms was used to evaluate the predictive pertinence of gray matter volumes of interest and psychometric scores in the detection of prospective clinical anxiety. Participants with clinical anxiety at age 18–23 (N = 156) were investigated at age 14 along with healthy controls (N = 424). Shapley values were extracted for in-depth interpretation of feature importance. Prospective prediction of pooled anxiety disorders relied mostly on psychometric features and achieved moderate performance (area under the receiver operating curve = 0.68), while generalized anxiety disorder (GAD) prediction achieved similar performance. MRI regional volumes did not improve the prediction performance of prospective pooled anxiety disorders with respect to psychometric features alone, but they improved the prediction performance of GAD, with the caudate and pallidum volumes being among the most contributing features. To conclude, in non-anxious 14 year old adolescents, future clinical anxiety onset 4–8 years later could be individually predicted. Psychometric features such as neuroticism, hopelessness and emotional symptoms were the main contributors to pooled anxiety disorders prediction. Neuroanatomical data, such as caudate and pallidum volume, proved valuable for GAD and should be included in prospective clinical anxiety prediction in adolescents.
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DOI：
10.1016/j.jaac.2017.01.013
发表时间：
2017-04
影响因子：
13.3
作者：
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通讯作者：
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影响因子：
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