Quality Tolerance Limits
Quality Tolerance Limits (QTLs) form a key part of the RBM approach. A QTL is defined as a level, point, or value associated with a trial variable that should trigger an investigation if a deviation is detected, in order to determine if there is a possible systematic issue (i.e. a trend has occurred). QTLs are monitored at the trial level and are pre-defined before the trial commences from a review of historical data from similar trials and where possible, using statistical methods and modelling. If there is limited historical information available about the trial variable of interest, difficulties may arise in developing a QTL.
Over recent years advances in technology have provided the promise of improving the conduct & oversight of clinical trials. Across industry, multi-disciplinary teams are working closely together to reap the rewards of risk based monitoring approaches. However, whilst the potential advantages of Risk Based Monitoring (RBM) are clear, the best way to successfully embed RBM in clinical trials is still emerging.
Although unusually high levels of deviations may indicate an issue at that site which may need to be quickly addressed, it is also important to be able to detect unusually low levels of deviations as this may indicate underreporting.
Predefined quality tolerance limits (QTLs) were introduced in the revised ICH E6 (R2) Section 5 update to help identify systematic issues that can impact subject safety or reliability of trial results.
The critical focus concerns the approach concerning the loss of evaluable subjects, patient discontinuation, and inclusion/exclusion errors.
Quality tolerance limits (QTLs), a statistical process control methodology, facilitate the execution of high-quality clinical trials. With the release of the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) E6(R2), QTLs are a requirement. There are challenges in the interpretation and implementation of these guidelines.
The ICH guidelines provide a sparse definition of QTLs and how to use them. “Predefined quality tolerance limits should be established, taking into consideration the medical and statistical characteristics of the variables as well as the statistical design of the trial….”
QTL is different from control limits, sometimes called alarm or action limits, which indicate that the trial is not progressing as expected (e.g., losing subjects to follow-up at a greater rate than historical trials) but not yet crossing the QTL.
There needs to be more clarity about the difference between key risk indicators (KRIs) and QTLs. Study teams use KRIs to monitor similar parameters to QTLs, such as dropout rate. The difference is that KRIs are at the site level, intended to find sites that are performing poorly by comparing them to either other sites or predefined fixed limits. QTLs are at the trial level, intended to assess the quality of an entire trial. It is beneficial to leverage the QTL parameter (e.g., dropout) as a KRI as well because, typically, the first step in root-cause analysis of a study-level issue is to see if the problem is driven by a single or small number of sites. Key Risk Indicators (KRI) are metrics used to identify and monitor potential risks to an organization. They are used to help organizations proactively identify and mitigate risks, rather than simply reacting to them after they occur. KRIs are typically chosen based on their ability to provide early warning of potential risks and their impact on the organization.
Control charts are graphs monitoring a process sequentially over time, for example, the number of subjects who did not meet an inclusion or exclusion criteria versus the calendar date. Control charts differ from a simple time series plot by augmenting the time series plot of the parameter over time with action or secondary limit lines to indicate when the process needs to be corrected. The term process in SPC means a production method (e.g., assembly line) in traditional use and a clinical trial in the current context. Control charts also differ from another standard quality control method, acceptance sampling. In a sampling framework, the focus is on the product. A random sample is taken from a manufactured batch, and the entire batch is either accepted or rejected based on the results of the random sample.
Obviously, the process approach is more appropriate for a clinical trial where patients and their data are always remembered. In SPC, the monitoring or charting of a process is the second and more straightforward part of a two-step process. In the first step, a process is optimized to minimize defective output and establish the average and variability of the output.
In the clinical trial QTL process, the first step is skipped since there is no opportunity to have a run-in period to see how the operational aspects of a trial are behaving. Instead, the best historical and subject matter expert knowledge is used to make an educated guess on how the process should behave.
