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Enrollment Success, Factors, and Prediction Models in Cancer Trials (2008-2019)

Year: 2023

Type: article

Abstract: PURPOSE: To investigate the enrollment success rate of cancer clinical trials conducted in 2008-2019 and various factors lowering the enrollment success rate. METHODS: This is a cross-sectional study with clinical trial information from the largest registration database ClinicalTrials.gov. Enrollment success rate was defined as actual enrollment greater or equal to 85% of the estimated enrollment goal. The association between trial characteristics and enrollment success was evaluated using the multivariable logistic regression. RESULTS: < .05). The AUC for prediction of the final logistic regression models for all trials and specific trial groups ranged from 0.69 to 0.76. CONCLUSION: This large-scale study supports a lower enrollment success rate over years in cancer clinical trials. Identified factors for enrollment success can be used to develop and improve recruitment strategies for future cancer trials.

Source: JCO Oncology Practice

DOI: 10.1200/op.23.00147

Authors: Siqi Zhang, Jianrong Zhang, Sida Liu, Herbert Pang, Thomas E. Stinchcombe, Xiaofei Wang