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Prediction of RECRUITment In randomized clinical Trials (RECRUIT-IT)-rationale and design for an international collaborative study.
Kasenda, Benjamin; Liu, Junhao; Jiang, Yu; Gajewski, Byron; Wu, Cen; von Elm, Erik; Schandelmaier, Stefan; Moffa, Giusi; Trelle, Sven; Schmitt, Andreas Michael; Herbrand, Amanda K; Gloy, Viktoria; Speich, Benjamin; Hopewell, Sally; Hemkens, Lars G; Sluka, Constantin; McGill, Kris; Meade, Maureen; Cook, Deborah; Lamontagne, Francois; Tréluyer, Jean-Marc; Haidich, Anna-Bettina; Ioannidis, John P A; Treweek, Shaun; Briel, Matthias.
  • Kasenda B; Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland. benjamin.kasenda@gmail.com.
  • Liu J; Department of Medical Oncology, University Hospital and University of Basel, Basel, Switzerland. benjamin.kasenda@gmail.com.
  • Jiang Y; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
  • Gajewski B; University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, USA.
  • Wu C; Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, 38152, USA.
  • von Elm E; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
  • Schandelmaier S; University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, USA.
  • Moffa G; Department of Statistics, Kansas State University, Manhattan, KS, 66506, USA.
  • Trelle S; Cochrane Switzerland, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
  • Schmitt AM; Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
  • Herbrand AK; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.
  • Gloy V; Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland.
  • Speich B; CTU Bern, University of Bern, Bern, Switzerland.
  • Hopewell S; Department of Medical Oncology, University Hospital and University of Basel, Basel, Switzerland.
  • Hemkens LG; Department of Medical Oncology, University Hospital and University of Basel, Basel, Switzerland.
  • Sluka C; Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
  • McGill K; Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
  • Meade M; Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
  • Cook D; Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
  • Lamontagne F; Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
  • Tréluyer JM; Clinical Trial Unit, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
  • Haidich AB; Nursing, Midwifery, and Allied Health Professionals Research Unit, Glasgow Caledonian University, Glasgow, UK.
  • Ioannidis JPA; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.
  • Treweek S; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.
  • Briel M; Centre de recherche du CHU de Sherbrooke and Université de Sherbrooke, Sherbrooke, Canada.
Trials ; 21(1): 731, 2020 Aug 21.
Article en En | MEDLINE | ID: mdl-32825846
BACKGROUND: Poor recruitment of patients is the predominant reason for early termination of randomized clinical trials (RCTs). Systematic empirical investigations and validation studies of existing recruitment models, however, are lacking. We aim to provide evidence-based guidance on how to predict and monitor recruitment of patients into RCTs. Our specific objectives are the following: (1) to establish a large sample of RCTs (target n = 300) with individual patient recruitment data from a large variety of RCTs, (2) to investigate participant recruitment patterns and study site recruitment patterns and their association with the overall recruitment process, (3) to investigate the validity of a freely available recruitment model, and (4) to develop a user-friendly tool to assist trial investigators in the planning and monitoring of the recruitment process. METHODS: Eligible RCTs need to have completed the recruitment process, used a parallel group design, and investigated any healthcare intervention where participants had the free choice to participate. To establish the planned sample of RCTs, we will use our contacts to national and international RCT networks, clinical trial units, and individual trial investigators. From included RCTs, we will collect patient-level information (date of randomization), site-level information (date of trial site activation), and trial-level information (target sample size). We will examine recruitment patterns using recruitment trajectories and stratifications by RCT characteristics. We will investigate associations of early recruitment patterns with overall recruitment by correlation and multivariable regression. To examine the validity of a freely available Bayesian prediction model, we will compare model predictions to collected empirical data of included RCTs. Finally, we will user-test any promising tool using qualitative methods for further tool improvement. DISCUSSION: This research will contribute to a better understanding of participant recruitment to RCTs, which could enhance efficiency and reduce the waste of resources in clinical research with a comprehensive, concerted, international effort.
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Texto completo: 1 Ejes tematicos: Pesquisa_clinica Banco de datos: MEDLINE Asunto principal: Proyectos de Investigación / Ensayos Clínicos Controlados Aleatorios como Asunto / Selección de Paciente Tipo de estudio: Clinical_trials / Guideline / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article

Texto completo: 1 Ejes tematicos: Pesquisa_clinica Banco de datos: MEDLINE Asunto principal: Proyectos de Investigación / Ensayos Clínicos Controlados Aleatorios como Asunto / Selección de Paciente Tipo de estudio: Clinical_trials / Guideline / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article