JCO oncology practice · 2023
Enrollment Success, Factors, and Prediction Models in Cancer Trials (2008-2019).
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
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Ошибки и ограничения
История · было → стало
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Zhang Siqi, Zhang Jianrong, Liu Sida, Pang Herbert, Stinchcombe Thomas E, Wang Xiaofei
Аннотация
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: A total of 4,004 trials in breast, lung, and colorectal cancers were included. The overall enrollment success rate was 49.1%. Compared with 2008-2010 (51.5%) and 2011-2013 (52.1%), the enrollment success rate is lower in 2014-2016 (46.5%) and 2017-2019 (36.4%). Regression analyses found trial activation year, phase I, phase I/phase II, and phase II (v phase III), sponsor agency of government (v industry), not requiring healthy volunteers, and estimated enrollment of 50-100, 100-200, 200, and >500 (v 0-50) were associated with a lower enrollment success rate (P < .05). However, trials with placebo comparator, ≥5 locations (v 1 location), and a higher number of secondary end points (eg, ≥5 v 0) were associated with a higher enrollment success rate (P < .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.
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: A total of 4,004 trials in breast, lung, and colorectal cancers were included. The overall enrollment success rate was 49.1%. Compared with 2008-2010 (51.5%) and 2011-2013 (52.1%), the enrollment success rate is lower in 2014-2016 (46.5%) and 2017-2019 (36.4%). Regression analyses found trial activation year, phase I, phase I/phase II, and phase II (v phase III), sponsor agency of government (v industry), not requiring healthy volunteers, and estimated enrollment of 50-100, 100-200, 200, and >500 (v 0-50) were associated with a lower enrollment success rate (P < .05). However, trials with placebo comparator, ≥5 locations (v 1 location), and a higher number of secondary end points (eg, ≥5 v 0) were associated with a higher enrollment success rate (P < .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.