Development of the Diabetes Technology Society Blood Glucose Monitor System Surveillance Protocol.

BACKGROUND: Inaccurate blood glucsoe monitoring systems (BGMSs) can lead to adverse health effects. The Diabetes Technology Society (DTS) Surveillance Program for cleared BGMSs is intended to protect people with diabetes from inaccurate, unreliable BGMS products that are currently on the market in the United States. The Surveillance Program will provide an independent assessment of the analytical performance of cleared BGMSs. METHODS: The DTS BGMS Surveillance Program Steering Committee included experts in glucose monitoring, surveillance testing, and regulatory science. Over one year, the committee engaged in meetings and teleconferences aiming to describe how to conduct BGMS surveillance studies in a scientifically sound manner that is in compliance with good clinical practice and all relevant regulations. RESULTS: A clinical surveillance protocol was created that contains performance targets and analytical accuracy-testing studies with marketed BGMS products conducted by qualified clinical and laboratory sites. This protocol entitled "Protocol for the Diabetes Technology Society Blood Glucose Monitor System Surveillance Program" is attached as supplementary material. CONCLUSION: This program is needed because currently once a BGMS product has been cleared for use by the FDA, no systematic postmarket Surveillance Program exists that can monitor analytical performance and detect potential problems. This protocol will allow identification of inaccurate and unreliable BGMSs currently available on the US market. The DTS Surveillance Program will provide BGMS manufacturers a benchmark to understand the postmarket analytical performance of their products. Furthermore, patients, health care professionals, payers, and regulatory agencies will be able to use the results of the study to make informed decisions to, respectively, select, prescribe, finance, and regulate BGMSs on the market.

The surveillance error grid.

Currently used error grids for assessing clinical accuracy of blood glucose monitors are based on out-of-date medical practices. Error grids have not been widely embraced by regulatory agencies for clearance of monitors, but this type of tool could be useful for surveillance of the performance of cleared products. Diabetes Technology Society together with representatives from the Food and Drug Administration, the American Diabetes Association, the Endocrine Society, and the Association for the Advancement of Medical Instrumentation, and representatives of academia, industry, and government, have developed a new error grid, called the surveillance error grid (SEG) as a tool to assess the degree of clinical risk from inaccurate blood glucose (BG) monitors. A total of 206 diabetes clinicians were surveyed about the clinical risk of errors of measured BG levels by a monitor. The impact of such errors on 4 patient scenarios was surveyed. Each monitor/reference data pair was scored and color-coded on a graph per its average risk rating. Using modeled data representative of the accuracy of contemporary meters, the relationships between clinical risk and monitor error were calculated for the Clarke error grid (CEG), Parkes error grid (PEG), and SEG. SEG action boundaries were consistent across scenarios, regardless of whether the patient was type 1 or type 2 or using insulin or not. No significant differences were noted between responses of adult/pediatric or 4 types of clinicians. Although small specific differences in risk boundaries between US and non-US clinicians were noted, the panel felt they did not justify separate grids for these 2 types of clinicians. The data points of the SEG were classified in 15 zones according to their assigned level of risk, which allowed for comparisons with the classic CEG and PEG. Modeled glucose monitor data with realistic self-monitoring of blood glucose errors derived from meter testing experiments plotted on the SEG when compared to the data plotted on the CEG and PEG produced risk estimates that were more granular and reflective of a continuously increasing risk scale. The SEG is a modern metric for clinical risk assessments of BG monitor errors that assigns a unique risk score to each monitor data point when compared to a reference value. The SEG allows the clinical accuracy of a BG monitor to be portrayed in many ways, including as the percentages of data points falling into custom-defined risk zones. For modeled data the SEG, compared with the CEG and PEG, allows greater precision for quantifying risk, especially when the risks are low. This tool will be useful to allow regulators and manufacturers to monitor and evaluate glucose monitor performance in their surveillance programs.