Evaluating protocol lifecycle time intervals in HIV/AIDS clinical trials
Authors: Rosas Scott R , Schouten Jeffrey T , Dixon Dennis , Varghese Suresh , Cope Marie T , Marci Joe , Kagan Jonathan M 
Published: July 2014

Background:

Identifying efficacious interventions for the prevention and treatment of human diseases depends on the efficient development and implementation of controlled clinical trials. Essential to reducing the time and burden of completing the clinical trial lifecycle is determining which aspects take the longest, delay other stages, and may lead to better resource utilization without diminishing scientific quality, safety, or the protection of human subjects.

Purpose:

In this study, we modeled time-to-event data to explore relationships between clinical trial protocol development and implementation times, as well as to identify potential correlates of prolonged development and implementation.

Methods:

We obtained time interval and participant accrual data from 111 interventional clinical trials initiated between 2006 and 2011 by National Institutes of Health’s HIV/AIDS Clinical Trials Networks. We determined the time (in days) required to complete defined phases of clinical trial protocol development and implementation. Kaplan–Meier estimates were used to assess the rates at which protocols reached specified terminal events, stratified by study purpose (therapeutic, prevention) and phase group (pilot/phase I, phase II, and phase III/IV). We also examined several potential correlates to prolonged development and implementation intervals.

Results:

Even though phase grouping did not determine development or implementation times of either therapeutic or prevention studies, overall we observed wide variation in protocol development times. Moreover, we detected a trend toward phase III/IV therapeutic protocols exhibiting longer developmental (median 2½ years) and implementation times (>3 years). We also found that protocols exceeding the median number of days for completing the development interval had significantly longer implementation.

Limitations:

The use of a relatively small set of protocols may have limited our ability to detect differences across phase groupings. Some timing effects present for a specific study phase may have been masked by combining protocols into phase groupings. Presence of informative censoring, such as withdrawal of some protocols from development if they began showing signs of lost interest among investigators, complicates interpretation of Kaplan–Meier estimates. Because this study constitutes a retrospective examination over an extended period of time, it does not allow for the precise identification of relative factors impacting timing.

Conclusion:

Delays not only increase the time and cost to complete clinical trials but they also diminish their usefulness by failing to answer research questions in time. We believe that research analyzing the time spent traversing defined intervals across the clinical trial protocol development and implementation continuum can stimulate business process analyses and re-engineering efforts that could lead to reductions in the time from clinical trial concept to results, thereby accelerating progress in clinical research.