Use of health plan combined with registry data to predict clinical trial recruitment

Abstract

Background: Large pragmatic clinical trials (PCTs) are increasingly used to conduct comparative effectiveness research. In the context of planning a safety PCT of the live herpes zoster vaccine in rheumatoid arthritis (RA) patients aged ≥ 50 years receiving anti-tumor necrosis factor (TNF) therapy, we evaluated the use of health plan combined with registry data to assess the feasibility of recruiting the 4000 patients needed for the trial and to facilitate site selection.

Methods: Using national US data from Medicare, we identified older RA patients who received anti-TNF therapy in the last quarter of 2009. Extrapolations were made from the Medicare patient population to younger patients and those with other types of insurance using the Consortium of Rheumatology Researchers of North America (CORRONA) disease registry. Patients' treating rheumatologists were grouped into practices and sorted by size from the greatest to the least number of eligible patients.

Results: Approximately 50,000 RA patients receiving anti-TNF therapy were identified in the Medicare data, distributed across 1980 physician practices. After augmenting Medicare data with information from CORRONA and extrapolating to younger patients and those with other types of insurance, more than 12,000 potentially eligible study subjects were identified from the 50 largest rheumatology practices.

Conclusion: Health plan and registry databases appear useful to assess feasibility of large pragmatic trials and to assist in selection of recruitment sites with the greatest number of potentially eligible patients. This novel approach is applicable to trials with simple inclusion/exclusion criteria that can be readily assessed in these data sources.

Figure 1

Number of Potentially Eligible Patients Needed for Trial Recruitment According to the Number of Physician Offices* Required to Participate * physician offices in the figure were ranked from the largest to the smallest based upon the number of patients eligible for the trial