Feasibility of cancer clinical trial enrollment goals based on cancer incidence.
Tran, GN; Harker, M; Chiswell, K; Unger, JM; Fleury, M; Hirsch, BR; Miller, K; D'Almada, P; Tibbs, S; Zafar, Y
Published in: Journal of Clinical Oncology
20 Background: More than 20% of US clinical trials fail to accrue sufficient patients and terminate prematurely, impeding innovation and negating the valuable contributions of participating patients. The aim of this study is to estimate availability of patients for each trial opening in the national oncology clinical research portfolio to provide a benchmark for better understanding feasibility of clinical trial enrollment goals. Methods: The Database for Aggregate Analysis of ClinicalTrials.gov, up-to-date as of September 3, 2017, was used to identify actively-recruiting, interventional oncology trials at US sites. Observational studies were excluded as not all are registered. Trials were categorized via Medical Subject Headings or free text condition terms and sorted by cancer diagnosis. Trial slot availability was estimated between September 1, 2017, to August 31, 2018. Availability was estimated from total anticipated enrollment, assuming a constant recruitment rate. Estimates for studies with both foreign and US sites were pro-rated to calculate available enrollment in the US alone. The 2017 American Cancer Society cancer incidence estimates were used to approximate total US cancer diagnoses. Results: 4598 oncology trials were identified. Overall, an estimated 12.6 cancer patients are available for each clinical trial slot. The estimates by cancer diagnosis were: colorectal: 24.7 patients per trial slot; lung & bronchus: 20.1; prostate: 17.6; breast (female): 13.8; leukemia 11.6; and brain & other nervous system: 6.0. Conclusions: Across all diagnoses, 1 in 13 patients must enroll to meet accrual demands. This ratio varies by diagnosis. If cancer incidence is too low, trials with unrealistic accrual goals may be doomed at inception. In diagnoses with high disease burden, trial failure may be due to poor patient access or suboptimal design. [Table: see text]