Estimating survival in data-driven phenotypes of mental health symptoms and peripheral biomarkers: A prospective study

IF 3.7 Q2 IMMUNOLOGY Brain, behavior, & immunity - health Pub Date : 2024-06-25 DOI:10.1016/j.bbih.2024.100815
Santiago Allende , Peter J. Bayley
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Abstract

Background

Chronic psychological stress has widespread implications, including heightened mortality risk, mental and physical health conditions, and socioeconomic consequences. Stratified precision psychiatry shows promise in mitigating these effects by leveraging clinical heterogeneity to personalize interventions. However, little attention has been given to patient self-report.

Methods

We addressed this by combining stress-related self-report measures with peripheral biomarkers in a latent profile analysis and survival model. The latent profile models were estimated in a representative U.S. cohort (n = 1255; mean age = 57 years; 57% female) and cross-validated in Tokyo, Japan (n = 377; mean age = 55 years; 56% female).

Results

We identified three distinct groups: “Good Mental Health”, “Poor Mental Health”, and “High Inflammation”. Compared to the “Good Mental Health” group, the “High Inflammation” and “Poor Mental Health” groups had an increased risk of mortality, but did not differ in mortality risk from each other.

Conclusions

This study emphasizes the role of patient self-report in stratified psychiatry.

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估算心理健康症状数据驱动表型和外周生物标志物的存活率:前瞻性研究
背景 慢性心理压力具有广泛的影响,包括增加死亡风险、身心健康状况和社会经济后果。分层精准精神病学利用临床异质性进行个性化干预,有望减轻这些影响。我们将压力相关的自我报告测量与外周生物标记物结合起来,建立了一个潜在特征分析和生存模型,从而解决了这一问题。我们在具有代表性的美国队列(n = 1255;平均年龄 = 57 岁;57% 为女性)中估算了潜特征模型,并在日本东京进行了交叉验证(n = 377;平均年龄 = 55 岁;56% 为女性):结果我们确定了三个不同的组别:"心理健康良好 "组、"心理健康不良 "组和 "炎症严重 "组。与 "精神健康状况良好 "组相比,"高炎症 "组和 "精神健康状况差 "组的死亡风险增加,但彼此的死亡风险没有差异。
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来源期刊
Brain, behavior, & immunity - health
Brain, behavior, & immunity - health Biological Psychiatry, Behavioral Neuroscience
CiteScore
8.50
自引率
0.00%
发文量
0
审稿时长
97 days
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