Literature DB >> 18283080

Ensuring trial validity by data quality assurance and diversification of monitoring methods.

Colin Baigent1, Frank E Harrell, Marc Buyse, Jonathan R Emberson, Douglas G Altman.   

Abstract

Errors in the design, the conduct, the data collection process, and the analysis of a randomized trial have the potential to affect not only the safety of the patients in the trial, but also, through the introduction of bias, the safety of future patients. Trial monitoring, defined broadly to include methods of oversight which begin when the study is designed and continue until it is reported in a publication, has a role to play in eliminating such errors. On-site monitoring can be extremely inefficient for the identification of errors most likely to compromise patient safety or bias study results. However, a variety of other monitoring strategies offer alternatives to on-site monitoring. Each new trial should conduct a risk assessment to identify the optimal means of monitoring, taking into account the likely sources of error, their consequences for patients, the study's validity, and the available resources. Trial management committees should consider central statistical monitoring a key aspect of such monitoring. The systematic application of this approach would be likely to lead to tangible benefits, and resources that are currently wasted on inefficient on-site monitoring could be diverted to increasing trial sample sizes or conducting more trials.

Entities:  

Mesh:

Year:  2008        PMID: 18283080     DOI: 10.1177/1740774507087554

Source DB:  PubMed          Journal:  Clin Trials        ISSN: 1740-7745            Impact factor:   2.486


  41 in total

1.  A Hercule Poirot of clinical research.

Authors:  Junichi Sakamoto
Journal:  Gastric Cancer       Date:  2016-01       Impact factor: 7.370

Review 2.  Data-driven risk identification in phase III clinical trials using central statistical monitoring.

Authors:  Catherine Timmermans; David Venet; Tomasz Burzykowski
Journal:  Int J Clin Oncol       Date:  2015-08-02       Impact factor: 3.402

3.  Statistical monitoring of data quality and consistency in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial.

Authors:  Catherine Timmermans; Erik Doffagne; David Venet; Lieven Desmet; Catherine Legrand; Tomasz Burzykowski; Marc Buyse
Journal:  Gastric Cancer       Date:  2015-08-23       Impact factor: 7.370

Review 4.  Statistical challenges for central monitoring in clinical trials: a review.

Authors:  Koji Oba
Journal:  Int J Clin Oncol       Date:  2015-10-23       Impact factor: 3.402

5.  Data fraud in clinical trials.

Authors:  Stephen L George; Marc Buyse
Journal:  Clin Investig (Lond)       Date:  2015

6.  INVESTIGATING THE EFFICACY OF CLINICAL TRIAL MONITORING STRATEGIES: Design and Implementation of the Cluster Randomized START Monitoring Substudy.

Authors:  Katherine Huppler Hullsiek; Jonathan M Kagan; Nicole Engen; Jesper Grarup; Fleur Hudson; Eileen T Denning; Catherine Carey; David Courtney-Rodgers; Elizabeth B Finley; Per O Jansson; Mary T Pearson; Dwight E Peavy; Waldo H Belloso
Journal:  Ther Innov Regul Sci       Date:  2015-03-01       Impact factor: 1.778

7.  Which preoperative factors, including bone bruise, are associated with knee pain/symptoms at index anterior cruciate ligament reconstruction (ACLR)? A Multicenter Orthopaedic Outcomes Network (MOON) ACLR Cohort Study.

Authors:  Warren R Dunn; Kurt P Spindler; Annunziato Amendola; Jack T Andrish; Christopher C Kaeding; Robert G Marx; Eric C McCarty; Richard D Parker; Frank E Harrell; Angel Q An; Rick W Wright; Robert H Brophy; Matthew J Matava; David C Flanigan; Laura J Huston; Morgan H Jones; Michelle L Wolcott; Armando F Vidal; Brian R Wolf
Journal:  Am J Sports Med       Date:  2010-07-01       Impact factor: 6.202

8.  Ensuring participant safety and trial integrity with clinical trials oversight.

Authors:  Catherine Godfrey; Manizhe Payton; Sybil Tasker; Scott Proestel; Jeffrey T Schouten
Journal:  J Acquir Immune Defic Syndr       Date:  2014-01-01       Impact factor: 3.731

9.  Measuring the Quality of Data Collection in a Large Observational Cohort of HIV and AIDS.

Authors:  Mariska Hillebregt; Elly de Lange-de Klerk; Dirk Knol; Frank de Wolf; Colette Smit
Journal:  Open AIDS J       Date:  2010-05-05

Review 10.  A systematic review of the reporting of Data Monitoring Committees' roles, interim analysis and early termination in pediatric clinical trials.

Authors:  Ricardo M Fernandes; Johanna H van der Lee; Martin Offringa
Journal:  BMC Pediatr       Date:  2009-12-13       Impact factor: 2.125

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.