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<div class="lia-message-template-content-zone"> <p> Chris Wells - Statistical Scientist @ Roche Products Ltd:</p> <p>Can Statistical monitoring really improve data integrity? A consolidated review of multiple analyses using JMP Clinical.</p> <p>It has been said that βData integrity is a fundamental component of information securityβ but what is the meaning of this? Broadly, it refers to the accuracy and consistency of data stored in a database over its entire lifecycle but it may have widely different meanings depending on the specific context. Within the context of a clinical trial, it refers to that data being accurate, complete and unique to the associated βlivingβ patient. Data Integrity is needed to protect the well-being of study participants and maintain the integrity of the final analysis results, so that patients, regulators and all interested parties can have belief in the data.</p> <p>The opposite of data integrity is <span><a href="https://en.wikipedia.org/wiki/Data_corruption" target="_blank">data corruption</a></span>, which is a form of <span><a href="https://en.wikipedia.org/wiki/Data_loss" target="_blank">data loss</a></span>. Data that is recorded incorrectly results in a loss of data for that patient or falsified data results in bias of the trial results.</p> <p>I will review the overall findings from 20 clinical studies using JMP Clinical and report on the level of findings and how they contributed to enhancing the overall data integrity.</p> </div>
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