Adverse events data handling

There is only one good solution to handling free-text variables that are needed for statistical analysis. The free-text variables need to be coded by clinical data management in the clinical database. If the adverse events were coded with a dictionary such as MedDRA, the previous example might look like Program 2.3. 

Serious adverse event (SAE) data handling (see Section 10.14.2 for additional discussion). 

International Conference on Harmonization Guideline on Data Elements for Transmission of Individual Case Safety Reports. This document s efforts focus on quality control/quality assurance endeavors to ensure accuracy and to promote validation in the handling of case safety reports for both preapproval and postapproval periods. It covers both adverse drug reaction and adverse event reports. 

Adverse event reporting Trial medication Premature withdrawal Subject replacement policy Criteria for excluding data Data analysis/statistical methods Quality control/assurance Data handling and record keeping Ethics (e.g. IRB/IEC approval)... 

As clinical trial protocols increase in complexity, there is an industry-wide shift toward adoption of electronic solutions to improve critical functions, most notably the collection, handling, analysis and storing of clinical data and the reporting of adverse and serious adverse events. 

Safety, adverse events and reporting of adverse events Sample collection, storage and handling of biological material Bioanalytical data (laboratory phase)... 

There are several important questions in drug safety evaluation How to detect unexpected adverse drug reactions while handling the multiplicity issue properly How to s)mthesize data from different trials, or even different sources How to deal with rare events How to evaluate multidimensional, complex safety information as a whole Can we monitor a potential safety issue in a continuous manner during a trial so that patients can be better protected These questions lead to some unique statistical challenges in quantitative safety analysis including low power due to rare events, multiplicity. 

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