Literature DB >> 9750037

Systems of protocol review, quality assurance, and data audit.

R B Weiss1.   

Abstract

The US National Cancer Institute (NCI) is the world's largest sponsor of clinical trials in cancer treatment and biology, and it is responsible for the reliability of data generated by means of its funding. The cooperative groups supported by the NCI consist of main academic institutions and smaller affiliates of these institutions. The size of these groups, their geographical dispersion, and the number of studies accruing patients at any one time make it a challenge to ensure that all requirements of institutional oversight, patient consent, protocol compliance, and data submission and quality are met. Each cooperative group has established various procedures for quality assurance. These include data coordinators at the data management center of the group, study chairs, and statisticians. In addition, each group has a committee of physician-investigators and clinical research associates who make periodic site visits to all member institutions to audit the on-site medical records of a sample of patients entered at that institution. The study records are compared with the medical records for all aspects of protocol management and data generation. In addition, adherence to requirements for consent-form signing and oversight by an institutional review board is assessed. Deviations from the study requirements are evaluated as being minor or major. A written report of the audit result is provided to both the NCI and the relevant administrative components of the cooperative group. The audit process has uncovered rare instances of scientific improprieties in these NCI-funded clinical trials, but more importantly it has educated investigators and support staff to improve adherence to research and data-collection requirements, which has resulted in greater reliability of study results.

Entities:  

Mesh:

Year:  1998        PMID: 9750037     DOI: 10.1007/s002800051087

Source DB:  PubMed          Journal:  Cancer Chemother Pharmacol        ISSN: 0344-5704            Impact factor:   3.333


  8 in total

1.  Tumor imaging protocols: problems and challenges.

Authors:  Mervyn D Cohen
Journal:  Pediatr Radiol       Date:  2003-07-10

2.  Preparing for Clinical Trial Data Audits.

Authors:  Raymond B Weiss; Susan S Tuttle
Journal:  J Oncol Pract       Date:  2006-07       Impact factor: 3.840

3.  Desiderata for a computer-assisted audit tool for clinical data source verification audits.

Authors:  Stephany N Duda; Firas H Wehbe; Cynthia S Gadd
Journal:  Stud Health Technol Inform       Date:  2010

4.  Successful coordination and execution of nontherapeutic studies in a cooperative group setting: lessons learned from Children's Oncology Group studies.

Authors:  Andrea Carter; Wendy Landier; Amy Schad; Allison Moser; Alexandra Schaible; Cara Hanby; Seira Kurian; F Lennie Wong; Doojduen Villaluna; Smita Bhatia
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-07       Impact factor: 4.254

5.  Efficient semiparametric inference for two-phase studies with outcome and covariate measurement errors.

Authors:  Ran Tao; Sarah C Lotspeich; Gustavo Amorim; Pamela A Shaw; Bryan E Shepherd
Journal:  Stat Med       Date:  2020-11-03       Impact factor: 2.373

6.  Quality control and data-handling in multicentre studies: the case of the Multicentre Project for Tuberculosis Research.

Authors:  T Caloto
Journal:  BMC Med Res Methodol       Date:  2001-12-21       Impact factor: 4.615

7.  Self-audits as alternatives to travel-audits for improving data quality in the Caribbean, Central and South America network for HIV epidemiology.

Authors:  Sarah C Lotspeich; Mark J Giganti; Marcelle Maia; Renalice Vieira; Daisy Maria Machado; Regina Célia Succi; Sayonara Ribeiro; Mario Sergio Pereira; Maria Fernanda Rodriguez; Gaetane Julmiste; Marco Tulio Luque; Yanink Caro-Vega; Fernando Mejia; Bryan E Shepherd; Catherine C McGowan; Stephany N Duda
Journal:  J Clin Transl Sci       Date:  2019-12-26

8.  Effectiveness of data auditing as a tool to reinforce good research data management (RDM) practice: a Singapore study.

Authors:  Hui Xing Lau; Ser Lin Celine Lee; Yusuf Ali
Journal:  BMC Med Ethics       Date:  2021-07-28       Impact factor: 2.652

  8 in total

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