1. Prioritisation and design of clinical trials
- Author
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Petros Pechlivanoglou, Eline M. Krijkamp, M. G. Myriam Hunink, Anna Heath, Radiology & Nuclear Medicine, Epidemiology, and Erasmus MC other
- Subjects
Research resources ,Epidemiology ,Psychological intervention ,03 medical and health sciences ,0302 clinical medicine ,SDG 3 - Good Health and Well-being ,Health care ,Methods ,Humans ,Medicine ,Value of information analysis ,Relevance (information retrieval) ,030212 general & internal medicine ,Health policy ,Clinical Trials as Topic ,Data collection ,Value-driven research ,business.industry ,Data Collection ,Health Policy ,Research ,030503 health policy & services ,Clinical study design ,Uncertainty ,Type I and type II errors ,Clinical trial design ,3. Good health ,Clinical trial ,Risk analysis (engineering) ,Research Design ,Sample size determination ,0305 other medical science ,business - Abstract
Clinical trials require participation of numerous patients, enormous research resources and substantial public funding. Time-consuming trials lead to delayed implementation of beneficial interventions and to reduced benefit to patients. This manuscript discusses two methods for the allocation of research resources and reviews a framework for prioritisation and design of clinical trials. The traditional error-driven approach of clinical trial design controls for type I and II errors. However, controlling for those statistical errors has limited relevance to policy makers. Therefore, this error-driven approach can be inefficient, waste research resources and lead to research with limited impact on daily practice. The novel value-driven approach assesses the currently available evidence and focuses on designing clinical trials that directly inform policy and treatment decisions. Estimating the net value of collecting further information, prior to undertaking a trial, informs a decision maker whether a clinical or health policy decision can be made with current information or if collection of extra evidence is justified. Additionally, estimating the net value of new information guides study design, data collection choices, and sample size estimation. The value-driven approach ensures the efficient use of research resources, reduces unnecessary burden to trial participants, and accelerates implementation of beneficial healthcare interventions.
- Published
- 2021
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