Linox and Linox(smart) ICD leads are safe, reliable and infrequently associated with lead-related AEs. Additionally, estimated cumulative survival probability is clinically acceptable and well within industry standards. Ongoing data collection will confirm the longer-term safety and performance of the Linox family of ICD leads.
Background Risk-based monitoring is a concept endorsed by the Food and Drug Administration to improve clinical trial data quality by focusing monitoring efforts on critical data elements and higher risk investigator sites. BIOTRONIK approached this by implementing a comprehensive strategy that assesses risk and data quality through a combination of operational controls and data surveillance. This publication demonstrates the effectiveness of a data-driven risk assessment methodology when used in conjunction with a tailored monitoring plan. Methods We developed a data-driven risk assessment system to rank 133 investigator sites comprising 3442 subjects and identify those sites that pose a potential risk to the integrity of data collected in implantable cardiac device clinical trials. This included identification of specific risk factors and a weighted scoring mechanism. We conducted trend analyses for risk assessment data collected over 1 year to assess the overall impact of our data surveillance process combined with other operational monitoring efforts. Results Trending analyses of key risk factors revealed an improvement in the quality of data collected during the observation period. The three risk factors follow-up compliance rate, unavailability of critical data, and noncompliance rate correspond closely with Food and Drug Administration's risk-based monitoring guidance document. Among these three risk factors, 100% (12/12) of quantiles analyzed showed an increase in data quality. Of these, 67% (8/12) of the improving trends in worst performing quantiles had p-values less than 0.05, and 17% (2/12) had p-values between 0.05 and 0.06. Among the poorest performing site quantiles, there was a statistically significant decrease in subject follow-up noncompliance rates, protocol noncompliance rates, and incidence of missing critical data. Conclusion One year after implementation of a comprehensive strategy for risk-based monitoring, including a data-driven risk assessment methodology to target on-site monitoring visits, statistically significant improvement was seen in a majority of measurable risk factors at the worst performing site quantiles. For the three risk factors which are most critical to the overall compliance of cardiac rhythm management medical device studies: follow-up compliance rate, unavailability of critical data, and noncompliance rate, we measured significant improvement in data quality. Although the worst performing site quantiles improved but not significantly in some risk factors such as subject attrition, the data-driven risk assessment highlighted key areas on which to continue focusing both on-site and centralized monitoring efforts. Data-driven surveillance of clinical trial performance provides actionable observations that can improve site performance. Clinical trials utilizing risk-based monitoring by leveraging a data-driven quality assessment combined with specific operational procedures may lead to an improvement in data quality and resource efficiencies.
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