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The Application of Principal Component Analysis on Clinical and Biochemical Parameters Exemplified in Children With Congenital Adrenal Hyperplasia.
Frontiers in Endocrinology ( IF 5.2 ) Pub Date : 2021-08-31 , DOI: 10.3389/fendo.2021.652888
Marie Lindhardt Ljubicic 1, 2 , Andre Madsen 1, 2, 3 , Anders Juul 1, 2 , Kristian Almstrup 1, 2 , Trine Holm Johannsen 1, 2
Affiliation  

Purpose Principal component analysis (PCA) is a mathematical model which simplifies data into new, combined variables. Optimal treatment of pediatric congenital adrenal hyperplasia (CAH) remains a challenge and requires evaluation of all biochemical and clinical markers. The aim of this study was to introduce PCA methodology as a tool to optimize management in a cohort of pediatric and adolescent patients with CAH by including adrenal steroid measurements and clinical parameters. Methods This retrospective, longitudinal cohort of 33 children and adolescents with CAH due to 21-hydroxylase deficiency included 406 follow-up observations. PCAs were applied to serum hormone concentrations and compared to treatment efficacy evaluated by clinical parameters. Results We provide and describe the first PCA models with hormone parameters denoted in sex- and age-adjusted standard deviation (SD) scores to comprehensibly describe the combined 'endocrine profiles' of patients with classical and non-classical CAH, respectively. Endocrine profile scores were predictive markers of treatment efficacy for classical (AUC=92%; accuracy 95%; p=1.8e-06) and non-classical CAH (AUC=80%; accuracy 91%; p=0.004). A combined PCA demonstrated clustering of patients with classical and non-classical CAH by serum 17-hydroxyprogesterone (17-OHP) and dehydroepiandrosterone-sulphate (DHEAS) concentrations. Conclusion As an example of the possibilities of PCA, endocrine profiles were successfully able to distinguish between patients with CAH according to treatment efficacy and to elucidate biochemical differences between classical and non-classical CAH.

中文翻译:

主成分分析在先天性肾上腺皮质增生症患儿临床生化指标中的应用。

目的 主成分分析 (PCA) 是一种数学模型,可将数据简化为新的组合变量。小儿先天性肾上腺增生症 (CAH) 的最佳治疗仍然是一个挑战,需要评估所有生化和临床标志物。本研究的目的是引入 PCA 方法作为一种工具,通过包括肾上腺类固醇测量和临床参数来优化一组儿童和青少年 CAH 患者的管理。方法 该回顾性纵向队列研究 33 名因 21-羟化酶缺乏而患有 CAH 的儿童和青少年,包括 406 次随访观察。PCA 被应用于血清激素浓度,并与临床参数评估的治疗效果进行比较。结果我们提供并描述了第一个 PCA 模型,其中激素参数以性别和年龄调整的标准偏差 (SD) 分数表示,以分别全面地描述经典和非经典 CAH 患者的组合“内分泌特征”。内分泌谱评分是经典(AUC=92%;准确度95%;p=1.8e-06)和非经典CAH(AUC=80%;准确度91%;p=0.004)治疗效果的预测标志物。联合 PCA 证明了通过血清 17-羟基孕酮 (17-OHP) 和硫酸脱氢表雄酮 (DHEAS) 浓度对经典和非经典 CAH 患者进行聚类。结论 作为 PCA 可能性的一个例子,
更新日期:2021-08-31
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