AIMS: Monitoring risk-based approaches in clinical trials are encouraged by regulatory guidance. However, the impact of a targeted source data verification (SDV) on data-management (DM) workload and on final data quality needs to be addressed. METHODS: MONITORING was a prospective study aiming at comparing full SDV (100% of data verified for all patients) and targeted SDV (only key data verified for all patients) followed by the same DM program (detecting missing data and checking consistency) on final data quality, global workload and staffing costs. RESULTS: In all, 137 008 data including 18 124 key data were collected for 126 patients from 6 clinical trials. Compared to the final database obtained using the full SDV monitoring process, the final database obtained using the targeted SDV monitoring process had a residual error rate of 1.47% (95% confidence interval, 1.41-1.53%) on overall data and 0.78% (95% confidence interval, 0.65-0.91%) on key data. There were nearly 4 times more queries per study with targeted SDV than with full SDV (mean ± standard deviation: 132 ± 101 vs 34 ± 26; P = .03). For a handling time of 15 minutes per query, the global workload of the targeted SDV monitoring strategy remained below that of the full SDV monitoring strategy. From 25 minutes per query it was above, increasing progressively to represent a 50% increase for 45 minutes per query. CONCLUSION: Targeted SDV monitoring is accompanied by increased workload for DM, which allows to obtain a small proportion of remaining errors on key data (<1%), but may substantially increase trial costs.
AIMS: Monitoring risk-based approaches in clinical trials are encouraged by regulatory guidance. However, the impact of a targeted source data verification (SDV) on data-management (DM) workload and on final data quality needs to be addressed. METHODS: MONITORING was a prospective study aiming at comparing full SDV (100% of data verified for all patients) and targeted SDV (only key data verified for all patients) followed by the same DM program (detecting missing data and checking consistency) on final data quality, global workload and staffing costs. RESULTS: In all, 137 008 data including 18 124 key data were collected for 126 patients from 6 clinical trials. Compared to the final database obtained using the full SDV monitoring process, the final database obtained using the targeted SDV monitoring process had a residual error rate of 1.47% (95% confidence interval, 1.41-1.53%) on overall data and 0.78% (95% confidence interval, 0.65-0.91%) on key data. There were nearly 4 times more queries per study with targeted SDV than with full SDV (mean ± standard deviation: 132 ± 101 vs 34 ± 26; P = .03). For a handling time of 15 minutes per query, the global workload of the targeted SDV monitoring strategy remained below that of the full SDV monitoring strategy. From 25 minutes per query it was above, increasing progressively to represent a 50% increase for 45 minutes per query. CONCLUSION: Targeted SDV monitoring is accompanied by increased workload for DM, which allows to obtain a small proportion of remaining errors on key data (<1%), but may substantially increase trial costs.
Authors: K Boudjema; C Camus; F Saliba; Y Calmus; E Salamé; G Pageaux; C Ducerf; C Duvoux; C Mouchel; A Renault; P Compagnon; R Lorho; E Bellissant Journal: Am J Transplant Date: 2011-04-05 Impact factor: 8.086
Authors: Eric L Eisenstein; Rory Collins; Beena S Cracknell; Oscar Podesta; Elizabeth D Reid; Peter Sandercock; Yuriy Shakhov; Michael L Terrin; Mary Ann Sellers; Robert M Califf; Christopher B Granger; Rafael Diaz Journal: Clin Trials Date: 2008 Impact factor: 2.486
Authors: Stephany N Duda; Bryan E Shepherd; Cynthia S Gadd; Daniel R Masys; Catherine C McGowan Journal: PLoS One Date: 2012-04-06 Impact factor: 3.240
Authors: Sharon B Love; Emma Armstrong; Carrie Bayliss; Melanie Boulter; Lisa Fox; Joanne Grumett; Patricia Rafferty; Barbara Temesi; Krista Wills; Andrea Corkhill Journal: Trials Date: 2021-04-14 Impact factor: 2.279