Statistical models to predict recruitment in clinical trials were rarely used by statisticians in UK and European networks

Autor: Susanna Dodd, Efstathia Gkioni, Roser Rius, Carrol Gamble
Přispěvatelé: Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Biostatistics [Liverpool, Royaume-Uni], University of Liverpool, Department of Statistics and Operations Researc, BarcelonaTech (UPC), Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa, Universitat Politècnica de Catalunya. GRBIO - Grup de Recerca en Bioestadística i Bioinformàtica, Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Lallemant, Christopher
Rok vydání: 2019
Předmět:
Monitoring
Epidemiology
media_common.quotation_subject
Audit
Surveys
62 Statistics::62D05 Sampling theory
sample surveys [Classificació AMS]
03 medical and health sciences
Clinical trials
0302 clinical medicine
Prediction methods
[SDV.EE.SANT] Life Sciences [q-bio]/Ecology
environment/Health
Humans
Quality (business)
030212 general & internal medicine
Sampling (Statistics)
Implementation
media_common
[SDV.EE.SANT]Life Sciences [q-bio]/Ecology
environment/Health
Clinical Trials as Topic
Actuarial science
Models
Statistical
Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària [Àrees temàtiques de la UPC]
Patient Selection
Statistical model
Research Personnel
United Kingdom
3. Good health
Clinical trial
Europe
Clinical research
Current practice
Recruitment
Prediction
Psychology
Mostreig (Estadística)
030217 neurology & neurosurgery
Zdroj: JOURNAL OF CLINICAL EPIDEMIOLOGY
Journal of Clinical Epidemiology
Journal of Clinical Epidemiology, Elsevier, 2020, 124, pp.58-68. ⟨10.1016/j.jclinepi.2020.03.012⟩
Journal of Clinical Epidemiology, 2020, 124, pp.58-68. ⟨10.1016/j.jclinepi.2020.03.012⟩
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
ISSN: 1878-5921
0895-4356
Popis: International audience; Objective: Identify the current practice for recruitment prediction and monitoring within clinical trials.Study Design and Setting: Chief investigators (CIs) were surveyed to identify data sources and adjustments made to support recruitment prediction. Statisticians were surveyed to determine methods and adjustments used when predicting and monitoring recruitment. Participants were identified from the National Institute for Health Research recently funded studies, the UK Clinical Research Collaboration registered Clinical Trial Units network or by the European Clinical Research Infrastructure Network.Results: A total of 51 CIs (UK = 32, ECRIN = 19) and 104 statisticians (UK = 51, ECRIN = 53) were contacted. Response rates varied (CIs UK = 53% ECRIN = 32%; statisticians UK = 98% ECRIN = 36%).Multiple data sources are used to support recruitment rates, most commonly audit data from multiple sites. Variation in individual site recruitment rates are frequently incorporated, but staggered site openings were featured more commonly among UK respondents. Simple prediction methods are preferred to rarely used statistical models. Lack of familiarity with statistical methods are barriers to their use with evidence needed to justify the time required to support their implementation.Conclusion: Simplistic methods will continue as the mainstay of prediction; however, generation of evidence supporting the benefits of complex statistical models should promote their implementations. Multiple data sources to support recruitment prediction are being used, and further work on the quality of these data is needed. Pressure to be optimistic about recruitment rates for the trial to be attractive to funders was felt by a sizable minority. (C) 2020 The Authors. Published by Elsevier Inc.
Databáze: OpenAIRE
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