Prospects of Statistical and Biostatistical Techniques in the Study of Diagnosis, Survival Analysis, and Disease Progression of Alzheimer’s Disease

V. Deo
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引用次数: 1

Abstract

Finding potent and clinically standardized biomarkers is of utmost importance for early detection of any disease which further helps in developing prevention and cure techniques. Use of statistical techniques becomes inevitable to validate the predictive power of the biomarkers and also to ensure the reproducibility of results. Identification of statistically significant covariates and competing risks is another important aspect of any biostatistical study for understanding disease progression. This paper attempts to review some useful statistical and biostatistical techniques being utilized in the study of dementia, Alzheimer’s disease (AD) in particular, and also proposes some potentially reliable techniques which can be helpful in critically examining the complexities involved in brain activities of AD patients and its association with other pathological and physical changes in the patients. This paper concludes by proposing an objective-wise methodological structure for biostatistical analyses of AD.
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统计和生物统计技术在阿尔茨海默病诊断、生存分析和疾病进展研究中的前景
寻找有效和临床标准化的生物标志物对于任何疾病的早期发现都是至关重要的,这进一步有助于开发预防和治疗技术。为了验证生物标记物的预测能力和确保结果的可重复性,使用统计技术变得不可避免。鉴别统计上显著的协变量和竞争风险是了解疾病进展的任何生物统计学研究的另一个重要方面。本文综述了目前在痴呆症,特别是阿尔茨海默病(AD)研究中应用的一些有用的统计和生物统计技术,并提出了一些潜在的可靠技术,这些技术可以帮助我们批判性地研究AD患者脑活动的复杂性及其与患者其他病理和生理变化的关系。本文最后提出了一种客观的AD生物统计分析方法结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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