The impact of clinical trial monitoring approaches on data integrity and cost--a review of current literature.

PURPOSE: Monitoring is a costly requirement when conducting clinical trials. New regulatory guidance encourages the industry to consider alternative monitoring methods to the traditional 100 % source data verification (SDV) approach. The purpose of this literature review is to provide an overview of publications on different monitoring methods and their impact on subject safety data, data integrity, and monitoring cost. METHODS: The literature search was performed by keyword searches in MEDLINE and hand search of key journals. All publications were reviewed for details on how a monitoring approach impacted subject safety data, data integrity, or monitoring costs. RESULTS: Twenty-two publications were identified. Three publications showed that SDV has some value for detection of not initially reported adverse events and centralized statistical monitoring (CSM) captures atypical trends. Fourteen publications showed little objective evidence of improved data integrity with traditional monitoring such as 100 % SDV and sponsor queries as compared to reduced SDV, CSM, and remote monitoring. Eight publications proposed a potential for significant cost reductions of monitoring by reducing SDV without compromising the validity of the trial results. CONCLUSIONS: One hundred percent SDV is not a rational method of ensuring data integrity and subject safety based on the high cost, and this literature review indicates that reduced SDV is a viable monitoring method. Alternative methods of monitoring such as centralized monitoring utilizing statistical tests are promising alternatives but have limitations as stand-alone tools. Reduced SDV combined with a centralized, risk-based approach may be the ideal solution to reduce monitoring costs while improving essential data quality.

Impact of source data verification on data quality in clinical trials: an empirical post hoc analysis of three phase 3 randomized clinical trials.

AIM: The aim of this project was to perform an empirical evaluation of the impact of on site source data verification (SDV) on the data quality in a clinical trial database to guide an informed decision on selection of the monitoring approach. METHODS: We used data from three randomized phase III trials monitored with a combination of complete SDV or partial SDV. After database lock, individual subject data were extracted from the clinical database and subjected to post hoc complete SDV. Error rates were calculated with focus on the degree of on study monitoring and relevance and analyzed for potential impact on end points. RESULTS: Data from a total of 2566 subjects including more than 3 million data fields were 100% source data verified post hoc. An overall error rate of 0.45% was found. No sites had 0% errors. 100% SDV yielded an error rate of 0.27% as compared with partial SDV having an error rate of 0.53% (P < 0.0001). Comparing partly and fully monitored subjects, minor differences were identified between variables of major importance to efficacy or safety. CONCLUSIONS: The findings challenge the notion that a 0% error rate is obtainable with on site monitoring. Data indicate consistently low error rates across the three trials analyzed. The use of complete vs. partial SDV offers a marginal absolute error rate reduction of 0.26%, i.e. a need to perform complete SDV of about 370 data points to avoid one unspecified error and does not support complete SDV as a means of providing meaningful improvements in data accuracy.