Evidence map›Paper›PMID 38984466›Full record

ArticleESC heart failure2024

Eligibility of Asian and European registry patients for phase III trials in heart failure with reduced ejection fraction.

Yvonne Mei Fong Lim, Folkert W Asselbergs, Ayoub Bagheri, Spiros Denaxas, Wan Ting Tay, Adriaan Voors, Carolyn Su Ping Lam, Stefan Koudstaal, Diederick E Grobbee, Ilonca Vaartjes

Abstract read
In one paragraph

Article in ESC heart failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yvonne Mei Fong LimJulius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Folkert W AsselbergsInstitute of Health Informatics, University College London, London, UK.
Ayoub BagheriDepartment of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.
Spiros DenaxasInstitute of Health Informatics, UCL BHF Research Accelerator and Health Data Research UK, University College London, London, UK.
Wan Ting TayNational Heart Centre Singapore, Singapore, Singapore.
Adriaan VoorsDepartment of Cardiology, University Medical Center Groningen, Groningen, The Netherlands.
Carolyn Su Ping LamNational Heart Centre Singapore, Singapore, Singapore.
Stefan KoudstaalDepartment of Cardiology, Groene Hart Ziekenhuis, Gouda, The Netherlands.
Diederick E GrobbeeJulius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Ilonca VaartjesJulius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

Funding

European Federation of Pharmaceutical Industries and AssociationsEuropean Union's Horizon 2020 research and innovation programmeInnovative Medicines Initiative 2 Joint Undertaking 116074UCL Hospitals NIHR Biomedical Research CentreUniversity Medical Center Utrecht Global Health Support Program
6 · The paper itself

Abstract

aimsTraditional 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. METHODS AND

resultsInterventional 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.

conclusionsBased 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.

Indexed as

Clinical Trials, Phase III as TopicHeart FailurePatient SelectionRegistriesStroke VolumeAsiaEligibility DeterminationEuropeHumansClinical trialsDisease registryGeneralizabilityHeart failurePatient eligibility

Identifiers

PMID38984466
PMCPMC11631231

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.