Phuse US Connect 2022 Abstract – Accepted for Presentation
The current gold standard for validation of programs written to summarize data from clinical trials is 100% double programming of all analysis datasets, tables, listings, and figures. This approach, however, does not identify cross-table discrepancies, and, we would argue, is not the best method of obtaining the highest quality results. As it is a manual exercise, it is labour intensive and subject to human error.
Performing cross table checks of outputs manually is a common practice performed by biostatisticians in the pharmaceutical industry. Manually validating multiple tables takes a significant amount of time and resources. This repetitive work can be done by a dedicated software, allowing the biostatisticians to focus on the statistical aspects of the study. It also provides a consistent, specified approach, whereas the current checking process is often unspecified and therefore not replicable.
An automation solution developed by Beaconcure cross checks two or more outputs in exactly the same way as figures within and across tables are commonly compared today but it does so in a comprehensive, consistent and faster manner. This technology can be used multiple times as data accumulates, identifying programming errors that lead to discrepancies in the output. It can also be used for all of reporting, not just tables for Clinical Study Reports, for example, Interim Analyses, Safety Updates, output for Data Monitoring Committees.
We will present at the conference multiple examples of cross-table checks as well as the automated process for performing the checking.
