ArticleTrials2018
The inclusion of real world evidence in clinical development planning.
Article in Trials, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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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.
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.
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Framework for the synthesis of non-randomised studies and randomised controlled trials: a guidance on conducting a systematic review and meta-analysis for healthcare decision making.BMJ evidence-based medicine · 2022Pooled it
- Pooled it
- Can Real-World Data From Hospital Information Systems Be Directly Utilized for Efficacy Studies: An Analysis of Data Time Points.Journal of evidence-based medicine · 2025Article
- Evaluating and improving real-world evidence with Targeted Learning.BMC medical research methodology · 2023Observational
- Article
- The effect of adding real-world evidence to regulatory submissions on the breadth of population indicated for rare disease medicine treatment by the European Medicines Agency.Journal of pharmaceutical policy and practice · 2022Article
- Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design.Clinical pharmacology and therapeutics · 2022Review
- Methods for the inclusion of real-world evidence in network meta-analysis.BMC medical research methodology · 2021Article
- Real-world evidence and product development: Opportunities, challenges and risk mitigation.Wiener klinische Wochenschrift · 2021Review
- Incorporating single-arm studies in meta-analysis of randomised controlled trials: a simulation study.BMC medical research methodology · 2021Article
- Impact of Real-World Data on Market Authorization, Reimbursement Decision & Price Negotiation.Therapeutic innovation & regulatory science · 2021Review
- RWE Framework: An Interactive Visual Tool to Support a Real-World Evidence Study Design.Drugs - real world outcomes · 2019Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundWhen designing studies it is common to search the literature to investigate variability estimates to use in sample size calculations. Proprietary data of previously designed trials in a particular indication are also used to obtain estimates of variability. Estimates of treatment effects are typically obtained from randomised controlled clinical trials (RCTs). Based on the observed estimates of treatment effect, variability and the minimum clinical relevant difference to detect, the sample size for a subsequent trial is estimated. However, data from real world evidence (RWE) studies, such as observational studies and other interventional studies in patients in routine clinical practice, are not widely used in a systematic manner when designing studies. In this paper, we propose a framework for inclusion of RWE in planning of a clinical development programme.
methodsIn our proposed approach, all evidence, from both RCTs and RWE (i.e. from studies in routine clinical practice), available at the time of designing of a new clinical trial is combined in a Bayesian network meta-analysis (NMA). The results can be used to inform the design of the next clinical trial in the programme. The NMA was performed at key milestones, such as at the end of the phase II trial and prior to the design of key phase III studies. To illustrate the methods, we designed an alternative clinical development programme in multiple sclerosis using RWE through clinical trial simulations.
resultsInclusion of RWE in the NMA and the resulting trial simulations demonstrated that 284 patients per arm were needed to achieve 90% power to detect effects of predetermined size in the TRANSFORMS study. For the FREEDOMS and FREEDOMS II clinical trials, 189 patients per arm were required. Overall there was a reduction in sample size of at least 40% across the three phase III studies, which translated to a time savings of at least 6 months for the undertaking of the fingolimod phase III programme.
conclusionThe use of RWE resulted in a reduced sample size of the pivotal phase III studies, which led to substantial time savings compared to the approach of sample size calculations without RWE.
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Registered trials
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.