Evidence map›Paper›PMID 30400970›Full record

ArticleOrphanet journal of rare diseases2018

Recommendations for the design of small population clinical trials.

Simon Day, Anneliene Hechtelt Jonker, Lilian Pek Lian Lau, Ralf-Dieter Hilgers, Ilan Irony, Kristina Larsson, Kit Cb Roes, Nigel Stallard

Abstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
–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

62 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  18. Characterizing circulating biomarkers for childhood dementia disorders: A scoping review of clinical trials.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025
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2 more citing papers are in PubMed but not listed here.

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

8 authors.

Simon DayClinical Trials Consulting & Training Limited, 53 Portway, North Marston, Buckingham, Buckinghamshire, MK18 3PL, UK. simon.day@CTCT-Ltd.co.uk.
Anneliene Hechtelt JonkerIRDiRC Scientific Secretariat, Inserm US-14, Paris, France.
Lilian Pek Lian LauIRDiRC Scientific Secretariat, Inserm US-14, Paris, France.
Ralf-Dieter HilgersDepartment of Medical Statistics, RWTH Aachen University, Aachen, Germany.
Ilan IronyCenter for Biologics Evaluation and Research/ Office of Tissues and Advanced Therapies, US Food and Drug Administration, Silver Spring, USA.
Kristina LarssonOrphan Medicines, European Medicines Agency, London, UK.
Kit Cb RoesJulius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht, The Netherlands.
Nigel StallardStatistics and Epidemiology, Warwick Medical School, University of Warwick, Coventry, UK.

Funding

Seventh Framework Programme 305207Seventh Framework Programme 602144Seventh Framework Programme 602552Seventh Framework Programme Health-F5-2013-603160
6 · The paper itself

Abstract

backgroundOrphan drug development faces numerous challenges, including low disease prevalence, patient population heterogeneity, and strong presence of paediatric patient populations. Consequently, clinical trials for orphan drugs are often smaller than those of non-orphan drugs, and they require the development of efficient trial designs relevant to small populations to gain the most information from the available data. The International Rare Diseases Research Consortium (IRDiRC) is aimed at promoting international collaboration and advance rare diseases research worldwide, and has as one of its goals to contribute to 1000 new therapies for rare diseases. IRDiRC set up a Small Population Clinical Trials (SPCT) Task Force in order to address the shortcomings of our understanding in carrying out clinical trials in rare diseases.

resultsThe IRDiRC SPCT Task Force met in March 2016 to discuss challenges faced in the design of small studies for rare diseases and present their recommendations, structured around six topics: different study methods/designs and their relation to different characteristics of medical conditions, adequate safety data, multi-arm trial designs, decision analytic approaches and rational approaches to adjusting levels of evidence, extrapolation, and patients' engagement in study design.

conclusionsRecommendations have been issued based on discussions of the Small Population Clinical Trials Task Force that aim to contribute towards successful therapy development and clinical use. While randomised clinical trials are still considered the gold standard, it is recommended to systematically take into consideration alternative trial design options when studying treatments for a rare disease. Combining different sources of safety data is important to give a fuller picture of a therapy's safety profile. Multi-arm trials should be considered an opportunity for rare diseases therapy development, and funders are encouraged to support such trial design via international networks. Patient engagement is critical in trial design and therapy development, a process which sponsors are encouraged to incorporate when conducting trials and clinical studies. Input from multiple regulatory agencies is recommended early and throughout clinical development. Regulators are often supportive of new clinical trial designs, provided they are well thought through and justified, and they also welcome discussions and questions on this topic. Parallel advice for multiregional development programs should also be considered.

Indexed as

Rare DiseasesBiomedical ResearchClinical Trials as TopicHumansResearch DesignClinical trialsIRDiRCPatient engagementRare diseasesRecommendationsSmall populationsSmall population studiesStatistical methods

Identifiers

PMID30400970
PMCPMC6219020

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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.