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      The data management of a phase III efficacy trial of an 11-valent pneumococcal conjugate vaccine and related satellite studies conducted in the Philippines

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          Abstract

          Background

          A large phase III placebo-controlled, randomized efficacy trial of an investigational 11-valent pneumococcal conjugate vaccine against pneumonia in children less than 2 years of age was conducted in the Philippines from July 2000 to December 2004. Clinical data from 12,194 children who were given either study vaccine or placebo was collected from birth up to two years of age for the occurrence of radiologically proven pneumonia as the primary endpoint, and for clinical pneumonia and invasive pneumococcal disease as the secondary endpoints. Several tertiary endpoints were also explored. Along the core trial, several satellite studies on herd immunity, cost-effectiveness of the study vaccine, acute otitis media, and wheezing were conducted.

          Results

          We describe here in detail how the relevant clinical records were managed and how quality control procedures were implemented to ensure that valid data were obtained respectively for the core trial and for the satellite studies. We discuss how the task was achieved, what the challenges were and what might have been done differently.

          Conclusions

          There were several factors that made the task of data management doable and efficient. First, a pre-trial data management system was available. Secondly, local committed statisticians, programmers and support staff were available and partly familiar to clinical trials. Thirdly, the personnel had undergone training during trial and grew with the task they were supposed to do. Thus the knowledge needed to develop and operate clinical data system was fully transferred to local staff.

          Trial registration

          Current Controlled Trials ISRCTN62323832

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          Most cited references11

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          Double data entry: what value, what price?

          We challenge the notion that double data entry is either sufficient or necessary to ensure good-quality data in clinical trials. Although we do not completely reject that notion, we quantify some of the effects that poor quality data have on final study results in terms of estimation, significance testing, and power. By introducing digit errors into simulated blood pressure measurements we demonstrate that simple range checks allow us to detect (and therefore correct) the main errors that impact the final study results and conclusions. The errors that cannot easily be detected by such range checks, although possibly numerous, are shown to be of little importance in drawing the correct conclusions from the statistical analysis of data. Exploratory data analysis cannot identify all errors that a second data entry would detect, but on the other hand, not all errors that are found by exploratory data analysis are detectable by double data entry. Double data entry is concerned solely with ensuring, to a high degree of certainty, that what is recorded on the case record form is transcribed into the database. Exploratory data analysis looks beyond the case record form to challenge the plausibility of the written data. In this sense, the second entering of data has some benefit, but the use of exploratory data analysis methods, either as data entry is ongoing or at the end of data entry and as the first stage in an analysis strategy, should always be mandatory.
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            Data quality assurance, monitoring, and reporting.

            In conclusion, the quality assurance and monitoring program is an integral and continuing part of study operations. A system must be devised and implemented by the coordinating center investigators, with the endorsement of the study leadership and support of the field site and resource center personnel. Proactive mechanisms for promoting high-quality data acquisition and reporting must be implemented. Data quality monitoring must address the entire process by which the data are gathered, transmitted, stored, and analyzed. Data quality should be monitored continually, with summary reports prepared and distributed to the study leadership. Appropriate training and certification enhance data quality, and site visits allow data collection and storage processes to be observed directly. The quality assurance and monitoring system must be documented. It should be flexible enough so that new means of quality assurance or monitoring can be added when necessary during the course of the study. At the completion of the study, quality monitoring results should be summarized in a final report regarding the level of quality achieved by the study investigators and personnel. Finally, for a quality assurance and monitoring program to be successful, the coordinating center investigators and personnel must provide prompt feedback and suggestions for corrective action whenever a data quality problem is discovered. This need can be met only when the coordinating center staff understand data quality goals and are up to date with all phases of data management and reporting. Delays in initiating any stage of data management and quality monitoring may result in uncorrectable data problems. Thus, knowledgeable and efficient coordinating center personnel are essential to achieving good data quality studywide.
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              A simple guide to five normal forms in relational database theory

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                Author and article information

                Journal
                BMC Res Notes
                BMC Res Notes
                BMC Research Notes
                BioMed Central
                1756-0500
                2012
                7 June 2012
                : 5
                : 274
                Affiliations
                [1 ]Research Institute for Tropical Medicine, Muntinlupa City, Philippines
                [2 ]National Institute for Health and Welfare, Helsinki, Finland
                [3 ]Karolinska Institutet, Stockholm, Sweden
                [4 ]University of Queensland, Brisbane, Australia
                Article
                1756-0500-5-274
                10.1186/1756-0500-5-274
                3434041
                22676626
                a1833b97-8845-4f33-aa99-56ec67cd6f63
                Copyright ©2012 Sanvictores et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 1 July 2011
                : 11 May 2012
                Categories
                Correspondence

                Medicine
                Medicine

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