Zachary Smith1, Ralf Bilke2, Sybrand Pretorius3, Kenneth Getz4. 1. Tufts CSDD, Tufts University, Boston, USA. zachary.smith605922@tufts.edu. 2. Boehringer Ingelheim, Ingelheim am Rhein, Germany. 3. Parexel, Newton, USA. 4. Tufts CSDD, Tufts University, Boston, USA.
Abstract
Tufts Center for the Study of Drug Development (Tufts CSDD) collected data on trial design elements and clinical trial performance outcomes from 187 protocols provided by 20 companies. 10 design variables were tested for correlations with 11 performance variables, and regression models of each performance variable were tested. Results: Many significant correlations were found (p < .01, p < .05). The number of countries and the number of sites were each positively correlated with amendment frequency, longer screening and study duration as well as study participant dropout rates. The number of internal reviews prior to protocol finalization was also positively correlated with these same performance outcomes. In regression modeling, scientific and operational design characteristics were significant predictors of cycle time, enrollment and retention outcomes, and amendment frequency, even when controlling for phase and therapeutic area. These predictors included the number of endpoints, eligibility criteria, procedures per visit, number of countries, and investigative sites. The results of this analysis suggest practical considerations for optimizing protocol performance.
Tufts Center for the Study of Drug Development (Tufts CSDD) collected data on trial design elements and clinical trial performance outcomes from 187 protocols provided by 20 companies. 10 design variables were tested for correlations with 11 performance variables, and regression models of each performance variable were tested. Results: Many significant correlations were found (p < .01, p < .05). The number of countries and the number of sites were each positively correlated with amendment frequency, longer screening and study duration as well as study participant dropout rates. The number of internal reviews prior to protocol finalization was also positively correlated with these same performance outcomes. In regression modeling, scientific and operational design characteristics were significant predictors of cycle time, enrollment and retention outcomes, and amendment frequency, even when controlling for phase and therapeutic area. These predictors included the number of endpoints, eligibility criteria, procedures per visit, number of countries, and investigative sites. The results of this analysis suggest practical considerations for optimizing protocol performance.
Authors: Joseph A DiMasi; Zachary Smith; Ingrid Oakley-Girvan; Andrew Mackinnon; Mary Costello; Pamela Tenaerts; Kenneth A Getz Journal: Ther Innov Regul Sci Date: 2022-09-14 Impact factor: 1.337