Evidence map›Paper›PMID 32825846›Full record

ArticleTrials2020

Prediction of RECRUITment In randomized clinical Trials (RECRUIT-IT)-rationale and design for an international collaborative study.

Benjamin Kasenda, Junhao Liu, Yu Jiang, Byron Gajewski, Cen Wu, Erik von Elm, Stefan Schandelmaier, Giusi Moffa, Sven Trelle, Andreas Michael Schmitt and 15 more

Abstract read
In one paragraph

Article in Trials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
  2. Observational
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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

25 authors.

Benjamin KasendaBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland. benjamin.kasenda@gmail.com.ORCID http://orcid.org/0000-0003-0110-8585
Junhao LiuDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Yu JiangDivision of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, 38152, USA.
Byron GajewskiDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Cen WuDepartment of Statistics, Kansas State University, Manhattan, KS, 66506, USA.
Erik von ElmCochrane Switzerland, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Stefan SchandelmaierBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
Giusi MoffaDepartment of Mathematics and Computer Science, University of Basel, Basel, Switzerland.
Sven TrelleCTU Bern, University of Bern, Bern, Switzerland.
Andreas Michael SchmittDepartment of Medical Oncology, University Hospital and University of Basel, Basel, Switzerland.
Amanda K HerbrandDepartment of Medical Oncology, University Hospital and University of Basel, Basel, Switzerland.
Viktoria GloyBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
Benjamin SpeichBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
Sally HopewellCentre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Lars G HemkensBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
Constantin SlukaClinical Trial Unit, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
Kris McGillNursing, Midwifery, and Allied Health Professionals Research Unit, Glasgow Caledonian University, Glasgow, UK.
Maureen MeadeDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.
Deborah CookDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.
Francois LamontagneCentre de recherche du CHU de Sherbrooke and Université de Sherbrooke, Sherbrooke, Canada.
Jean-Marc TréluyerAssistance Publique-Hopitaux de Paris, Hopitaux Universitaires Paris Centre, Unité de Recherche clinique, 27 rue du Faubourg Saint-Jacques, 75014, Paris, France.
Anna-Bettina HaidichDepartment of Hygiene, Social-Preventive Medicine & Medical Statistics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece.
John P A IoannidisMeta-Research Innovation Center at Stanford (METRICS) and Departments of Medicine, of Health Research and Policy, of Biomedical Data Science, and of Statistics, Stanford University, Stanford, USA.
Shaun TreweekHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Matthias BrielBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.

Funding

Chief Scientist Office HSRU1Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 320030_133540/1
6 · The paper itself

Abstract

backgroundPoor 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.

methodsEligible 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.

Indexed as

Patient SelectionRandomized Controlled Trials as TopicResearch DesignHumansResearch PersonnelSample SizeAccrualPredictionRandomized clinical trialsRecruitment

Identifiers

PMID32825846
PMCPMC7441612

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.