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A review of research on eligibility criteria for clinical trials
Qianmin Su1, Gaoyi Cheng2, Jihan Huang3
1Department of Computer Science, School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, No. 333 Longteng Road, Shanghai, 201620, China. suqm@sues.edu.cn.
Abstract:
The purpose of this paper is to systematically sort out and analyze the cutting-edge research on the eligibility criteria of clinical trials. Eligibility criteria are important prerequisites for the success of clinical trials. It directly affects the final results of the clinical trials. Inappropriate eligibility criteria will lead to insufficient recruitment, which is an important reason for the eventual failure of many clinical trials. We have investigated the research status of eligibility criteria for clinical trials on academic platforms such as arXiv and NIH. We have classified and sorted out all the papers we found, so that readers can understand the frontier research in this field. Eligibility criteria are the most important part of a clinical trial study. The ultimate goal of research in this field is to formulate more scientific and reasonable eligibility criteria and speed up the clinical trial process. The global research on the eligibility criteria of clinical trials is mainly divided into four main aspects: natural language processing, patient pre-screening, standard evaluation, and clinical trial query. Compared with the past, people are now using new technologies to study eligibility criteria from a new perspective (big data). In the research process, complex disease concepts, how to choose a suitable dataset, how to prove the validity and scientific of the research results, are challenges faced by researchers (especially for computer-related researchers). Future research will focus on the selection and improvement of artificial intelligence algorithms related to clinical trials and related practical applications such as databases, knowledge graphs, and dictionaries.
Insights
This study reviews cutting-edge research on clinical trial eligibility criteria. Optimizing these criteria using big data and AI is crucial for successful patient recruitment and faster trial completion.
Area of Science:
- Clinical Research
- Biomedical Informatics
- Data Science
Background:
- Eligibility criteria are critical for clinical trial success, directly impacting recruitment and outcomes.
- Inappropriate criteria often lead to insufficient patient enrollment, a major cause of trial failure.
- Understanding current research trends is essential for advancing clinical trial design.
Purpose of the Study:
- To systematically review and analyze the latest research on clinical trial eligibility criteria.
- To provide a clear overview of the frontier research landscape in this field.
- To identify key challenges and future directions for improving eligibility criteria.
Main Methods:
- Conducted a comprehensive investigation of research on clinical trial eligibility criteria using academic platforms like arXiv and NIH.
- Classified and organized collected papers to present a structured analysis of the field.
- Focused on emerging technologies and big data approaches in eligibility criteria research.
Main Results:
- Identified four main research aspects: natural language processing, patient pre-screening, standard evaluation, and clinical trial query.
- Highlighted the shift towards utilizing new technologies and big data for studying eligibility criteria.
- Noted challenges including complex disease concepts, dataset selection, and result validation.
Conclusions:
- Formulating more scientific and reasonable eligibility criteria is key to accelerating clinical trials.
- Future research should concentrate on artificial intelligence algorithms, databases, knowledge graphs, and dictionaries.
- Advancements in these areas will enhance the efficiency and success rate of clinical trials.
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