Abstract：
OBJECTIVE: Traditional approaches to designing clinical trials for heart failure (HF) have historically relied on expertise and past practices. However, the evolving landscape of healthcare, marked by the advent of novel data science applications and increased data availability, offers a compelling opportunity to transition towards a data-driven paradigm in trial design. This research aims to evaluate the scope and determinants of disparities between clinical trials and registries by leveraging natural language processing for the analysis of trial eligibility criteria. The findings contribute to the establishment of a robust design framework for guiding future HF trials.
RESULTS: Interventional phase III trials registered for HF on ClinicalTrials.gov as of the end of 2021 were identified. Natural language processing was used to extract and structure the eligibility criteria for quantitative analysis. The most common criteria for HF with reduced ejection fraction (HFrEF) were applied to estimate patient eligibility as a proportion of registry patients in the ASIAN-HF (N = 4868) and BIOSTAT-CHF registries (N = 2545). Of the 375 phase III trials for HF, 163 HFrEF trials were identified. In these trials, the most frequently encountered inclusion criteria were New York Heart Association (NYHA) functional class (69%), worsening HF (23%), and natriuretic peptides (18%), whereas the most frequent comorbidity-based exclusion criteria were acute coronary syndrome (64%), renal disease (55%), and valvular heart disease (47%). On average, 20% of registry patients were eligible for HFrEF trials. Eligibility distributions did not differ (P = 0.18) between Asian [median eligibility 0.20, interquartile range (IQR) 0.08-0.43] and European registry populations (median 0.17, IQR 0.06-0.39). With time, HFrEF trials became more restrictive, where patient eligibility declined from 0.40 in 1985-2005 to 0.19 in 2016-2022 (P = 0.03). When frequency among trials is taken into consideration, the eligibility criteria that were most restrictive were prior myocardial infarction, NYHA class, age, and prior HF hospitalization.
CONCLUSIONS: Based on 14 trial criteria, only one-fifth of registry patients were eligible for phase III HFrEF trials. Overall eligibility rates did not differ between the Asian and European patient cohorts.
RESULTS: Interventional phase III trials registered for HF on ClinicalTrials.gov as of the end of 2021 were identified. Natural language processing was used to extract and structure the eligibility criteria for quantitative analysis. The most common criteria for HF with reduced ejection fraction (HFrEF) were applied to estimate patient eligibility as a proportion of registry patients in the ASIAN-HF (N = 4868) and BIOSTAT-CHF registries (N = 2545). Of the 375 phase III trials for HF, 163 HFrEF trials were identified. In these trials, the most frequently encountered inclusion criteria were New York Heart Association (NYHA) functional class (69%), worsening HF (23%), and natriuretic peptides (18%), whereas the most frequent comorbidity-based exclusion criteria were acute coronary syndrome (64%), renal disease (55%), and valvular heart disease (47%). On average, 20% of registry patients were eligible for HFrEF trials. Eligibility distributions did not differ (P = 0.18) between Asian [median eligibility 0.20, interquartile range (IQR) 0.08-0.43] and European registry populations (median 0.17, IQR 0.06-0.39). With time, HFrEF trials became more restrictive, where patient eligibility declined from 0.40 in 1985-2005 to 0.19 in 2016-2022 (P = 0.03). When frequency among trials is taken into consideration, the eligibility criteria that were most restrictive were prior myocardial infarction, NYHA class, age, and prior HF hospitalization.
CONCLUSIONS: Based on 14 trial criteria, only one-fifth of registry patients were eligible for phase III HFrEF trials. Overall eligibility rates did not differ between the Asian and European patient cohorts.
摘要：
目的：设计心力衰竭（HF）临床试验的传统方法历来依赖于专业知识和过去的实践。然而,不断发展的医疗保健景观，以新型数据科学应用的出现和数据可用性的增加为标志，提供了一个令人信服的机会，在试验设计中过渡到数据驱动的范式。这项研究旨在通过利用自然语言处理来分析试验资格标准来评估临床试验和注册之间差异的范围和决定因素。这些发现有助于建立一个强大的设计框架，以指导未来的HF试验。
结果：确定了截至2021年底在ClinicalTrials.gov上注册的HF介入III期试验。自然语言处理用于提取和构建定量分析的合格标准。射血分数降低的HF（HFrEF）的最常见标准用于评估ASIAN-HF（N=4868）和BIOSTAT-CHF注册（N=2545）中注册患者的比例。在针对HF的375个III期试验中，确定了163项HFrEF试验。在这些试验中,最常遇到的纳入标准是纽约心脏协会（NYHA）功能等级（69％），HF恶化（23%），和利钠肽（18％），而最常见的基于合并症的排除标准是急性冠脉综合征（64%），肾脏疾病（55%），和心脏瓣膜病（47%）。平均而言,20%的注册患者符合HFrEF试验的条件。亚洲人[中位资格0.20，四分位距（IQR）0.08-0.43]和欧洲注册人群（中位资格0.17，IQR0.06-0.39）之间的资格分布没有差异（P=0.18）。随着时间的推移,HFrEF试验变得更加严格，患者资格从1985-2005年的0.40下降至2016-2022年的0.19(P=0.03).当考虑到试验中的频率时，最严格的资格标准是既往心肌梗死,NYHA类，年龄,和以前的HF住院。
结论：基于14项试验标准，只有五分之一的注册患者符合III期HFrEF试验的条件.亚洲和欧洲患者队列的总体合格率没有差异。
结果：确定了截至2021年底在ClinicalTrials.gov上注册的HF介入III期试验。自然语言处理用于提取和构建定量分析的合格标准。射血分数降低的HF（HFrEF）的最常见标准用于评估ASIAN-HF（N=4868）和BIOSTAT-CHF注册（N=2545）中注册患者的比例。在针对HF的375个III期试验中，确定了163项HFrEF试验。在这些试验中,最常遇到的纳入标准是纽约心脏协会（NYHA）功能等级（69％），HF恶化（23%），和利钠肽（18％），而最常见的基于合并症的排除标准是急性冠脉综合征（64%），肾脏疾病（55%），和心脏瓣膜病（47%）。平均而言,20%的注册患者符合HFrEF试验的条件。亚洲人[中位资格0.20，四分位距（IQR）0.08-0.43]和欧洲注册人群（中位资格0.17，IQR0.06-0.39）之间的资格分布没有差异（P=0.18）。随着时间的推移,HFrEF试验变得更加严格，患者资格从1985-2005年的0.40下降至2016-2022年的0.19(P=0.03).当考虑到试验中的频率时，最严格的资格标准是既往心肌梗死,NYHA类，年龄,和以前的HF住院。
结论：基于14项试验标准，只有五分之一的注册患者符合III期HFrEF试验的条件.亚洲和欧洲患者队列的总体合格率没有差异。
