Literature DB >> 26386325

Registration practices for observational studies on ClinicalTrials.gov indicated low adherence.

Stefania Boccia1, Kenneth J Rothman2, Nikola Panic3, Maria Elena Flacco4, Annalisa Rosso5, Roberta Pastorino3, Lamberto Manzoli6, Carlo La Vecchia7, Paolo Villari5, Paolo Boffetta8, Walter Ricciardi3, John P A Ioannidis9.   

Abstract

OBJECTIVE: The study aims to assess the status of registration of observational studies. STUDY DESIGN AND
SETTING: We identified studies on cancer research with prospective recruitment of participants that were registered from February 2000 to December 2011 in ClinicalTrials.gov. We recorded the dates of registration and start of recruitment, outcomes, and description of statistical method. We searched for publications corresponding to the registered studies through May 31, 2014.
RESULTS: One thousand one hundred nine registered studies were eligible. Primary and secondary outcomes were reported in 809 (73.0%) and 464 (41.8%) of them. The date of registration preceded the month of the study start in 145 (13.8%) and coincided in 205 (19.5%). A total of 151 publications from 120 (10.8%) registered studies were identified. In 2 (33.3%) of the 6 publications where ClinicalTrials.gov reported that the study started recruitment after registration, and in 9 (50.0%) of 18 publications where ClinicalTrials.gov reported the same date for registration and start of recruitment, the articles showed that the study had actually started recruiting before registration.
CONCLUSION: During the period reviewed, few observational studies have been registered. Registration usually occurred after the study started, and prespecification of outcomes and statistical analysis rarely occurred.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cancer protocol registration; ClinicalTrials.gov; Outcome reporting bias; Protocol registration; Registration of observational studies; Registration study records

Mesh:

Year:  2015        PMID: 26386325     DOI: 10.1016/j.jclinepi.2015.09.009

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  18 in total

Review 1.  Standards for design and measurement would make clinical research reproducible and usable.

Authors:  Kay Dickersin; Evan Mayo-Wilson
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-13       Impact factor: 11.205

2.  A metadata schema for data objects in clinical research.

Authors:  Steve Canham; Christian Ohmann
Journal:  Trials       Date:  2016-11-24       Impact factor: 2.279

3.  Vibration of effects in epidemiologic studies of alcohol consumption and breast cancer risk.

Authors:  Lingzhi Chu; John P A Ioannidis; Alex C Egilman; Vasilis Vasiliou; Joseph S Ross; Joshua D Wallach
Journal:  Int J Epidemiol       Date:  2020-04-01       Impact factor: 7.196

4.  The replication crisis in epidemiology: snowball, snow job, or winter solstice?

Authors:  Timothy L Lash; Lindsay J Collin; Miriam E Van Dyke
Journal:  Curr Epidemiol Rep       Date:  2018-04-12

5.  Gestational diabetes mellitus in women born small or preterm: Systematic review and meta-analysis.

Authors:  Yasushi Tsujimoto; Yuki Kataoka; Masahiro Banno; Shunsuke Taito; Masayo Kokubo; Yuko Masuzawa; Yoshiko Yamamoto
Journal:  Endocrine       Date:  2021-11-02       Impact factor: 3.633

6.  Clinical research data sharing: what an open science world means for researchers involved in evidence synthesis.

Authors:  Joseph S Ross
Journal:  Syst Rev       Date:  2016-09-20

7.  Postmarketing studies for novel drugs approved by both the FDA and EMA between 2005 and 2010: a cross-sectional study.

Authors:  Jean-David Zeitoun; Joseph S Ross; Ignacio Atal; Alexandre Vivot; Nicholas S Downing; Gabriel Baron; Philippe Ravaud
Journal:  BMJ Open       Date:  2017-12-21       Impact factor: 2.692

Review 8.  When Null Hypothesis Significance Testing Is Unsuitable for Research: A Reassessment.

Authors:  Denes Szucs; John P A Ioannidis
Journal:  Front Hum Neurosci       Date:  2017-08-03       Impact factor: 3.169

9.  Differential Globalization of Industry- and Non-Industry-Sponsored Clinical Trials.

Authors:  Ignacio Atal; Ludovic Trinquart; Raphaël Porcher; Philippe Ravaud
Journal:  PLoS One       Date:  2015-12-14       Impact factor: 3.240

10.  p-Curve and p-Hacking in Observational Research.

Authors:  Stephan B Bruns; John P A Ioannidis
Journal:  PLoS One       Date:  2016-02-17       Impact factor: 3.240

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