{"title":"评估临床试验的向量理论:生物等效性的应用","authors":"Vangelis D Karalis","doi":"10.3390/jcdd11070185","DOIUrl":null,"url":null,"abstract":"<p><p>A novel idea is introduced regarding the statistical comparisons of endpoints in clinical trials. Currently, the (dis)similarity of measured endpoints is not assessed. Instead, statistical analysis is directly applied, which can lead to multiplicity issues, reduced statistical power, and the recruitment of more subjects. The Vector-Based Comparison (VBC) approach originates from vector algebra and considers clinical endpoints as \"vectors\". In the general case of N clinical endpoints, a Cartesian coordinate system is defined, and the most important primary endpoint (E1) is set. Following an explicitly defined procedure, the pairwise relationships of the remaining N-1 endpoints with E1 are estimated, and the N-1 endpoints are decomposed into axes perpendicular to E1. The angle between vectors provides insight into the level of dependency between variables. Vectors that are perpendicular to each other are considered independent, and only these are used in the statistical analysis. In this work, VBC is applied to bioequivalence studies of three anti-hypertensive drugs: amlodipine, irbesartan, and hydrochlorothiazide. The results suggest that VBC is a reproducible, easily applicable method allowing for the discrimination and utilization of the endpoint component expressing different attributes. All clinical characteristics are assessed with increased statistical power, without inflation of type I error.</p>","PeriodicalId":15197,"journal":{"name":"Journal of Cardiovascular Development and Disease","volume":"11 7","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11277341/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Vector Theory of Assessing Clinical Trials: An Application to Bioequivalence.\",\"authors\":\"Vangelis D Karalis\",\"doi\":\"10.3390/jcdd11070185\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A novel idea is introduced regarding the statistical comparisons of endpoints in clinical trials. Currently, the (dis)similarity of measured endpoints is not assessed. Instead, statistical analysis is directly applied, which can lead to multiplicity issues, reduced statistical power, and the recruitment of more subjects. The Vector-Based Comparison (VBC) approach originates from vector algebra and considers clinical endpoints as \\\"vectors\\\". In the general case of N clinical endpoints, a Cartesian coordinate system is defined, and the most important primary endpoint (E1) is set. Following an explicitly defined procedure, the pairwise relationships of the remaining N-1 endpoints with E1 are estimated, and the N-1 endpoints are decomposed into axes perpendicular to E1. The angle between vectors provides insight into the level of dependency between variables. Vectors that are perpendicular to each other are considered independent, and only these are used in the statistical analysis. In this work, VBC is applied to bioequivalence studies of three anti-hypertensive drugs: amlodipine, irbesartan, and hydrochlorothiazide. The results suggest that VBC is a reproducible, easily applicable method allowing for the discrimination and utilization of the endpoint component expressing different attributes. All clinical characteristics are assessed with increased statistical power, without inflation of type I error.</p>\",\"PeriodicalId\":15197,\"journal\":{\"name\":\"Journal of Cardiovascular Development and Disease\",\"volume\":\"11 7\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11277341/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cardiovascular Development and Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3390/jcdd11070185\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cardiovascular Development and Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/jcdd11070185","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
摘要
本文就临床试验终点的统计比较提出了一个新想法。目前,并不对测量终点的(不)相似性进行评估。取而代之的是直接应用统计分析,这可能会导致多重性问题、统计能力下降以及招募更多受试者。基于向量的比较(VBC)方法源于向量代数,将临床终点视为 "向量"。在有 N 个临床终点的一般情况下,定义一个直角坐标系,并设定最重要的主要终点(E1)。按照明确定义的程序,估算其余 N-1 个终点与 E1 的成对关系,并将 N-1 个终点分解为垂直于 E1 的轴。矢量之间的角度可以让我们了解变量之间的依赖程度。相互垂直的向量被认为是独立的,只有这些向量被用于统计分析。本研究将 VBC 应用于三种抗高血压药物(氨氯地平、厄贝沙坦和氢氯噻嗪)的生物等效性研究。研究结果表明,VBC 是一种可重复、易于应用的方法,可以区分和利用表达不同属性的终点成分。在评估所有临床特征时,统计能力都得到了提高,而且不会出现 I 型误差。
A Vector Theory of Assessing Clinical Trials: An Application to Bioequivalence.
A novel idea is introduced regarding the statistical comparisons of endpoints in clinical trials. Currently, the (dis)similarity of measured endpoints is not assessed. Instead, statistical analysis is directly applied, which can lead to multiplicity issues, reduced statistical power, and the recruitment of more subjects. The Vector-Based Comparison (VBC) approach originates from vector algebra and considers clinical endpoints as "vectors". In the general case of N clinical endpoints, a Cartesian coordinate system is defined, and the most important primary endpoint (E1) is set. Following an explicitly defined procedure, the pairwise relationships of the remaining N-1 endpoints with E1 are estimated, and the N-1 endpoints are decomposed into axes perpendicular to E1. The angle between vectors provides insight into the level of dependency between variables. Vectors that are perpendicular to each other are considered independent, and only these are used in the statistical analysis. In this work, VBC is applied to bioequivalence studies of three anti-hypertensive drugs: amlodipine, irbesartan, and hydrochlorothiazide. The results suggest that VBC is a reproducible, easily applicable method allowing for the discrimination and utilization of the endpoint component expressing different attributes. All clinical characteristics are assessed with increased statistical power, without inflation of type I error.