Abstract
BackgroundA better understanding of the current features of lung cancer clinical research registration is important for improving registration quality and standardizing the registration. This study aimed to assess the registration quality of lung cancer studies on ClinicalTrials.gov and analyze the influencing factors.MethodsLung cancer clinical researches registered in the ClinicalTrials.gov database were searched on 7 July 2021. The characteristics of trials that registered up to 7 July 2021 were assessed. The quality of completed and terminated lung cancer studies from 1 July 2007 to 7 July 2020 was assessed using a modified version of the World Health Organization (WHO) Trial Registration Data Set (TRDS, V.1.3.1). Multivariate logistic regression analysis was also used to analyze the factors influencing study registration quality. An above-average registration quality score represented a high registration quality.ResultsA total of 6,448 clinical studies on lung cancer were used to summarise the registration characteristics. Most interventional studies were randomized (41.88%), single group (48.07%), and open-label (82.86%) studies, while most observational studies were cohort studies (59.08%). In total, 2,171 completed and terminated studies were assessed, with an average quality score (out of 54) of 36.76±5.69. None of the assessed studies had a 100% modified TRDS reporting rate, and missing summary results were the main factor affecting the quality scores. Multivariate logistic regression analyses showed that prospective registrations [adjusted odds ratio (aOR), 2.18; 95% confidence interval (CI), 1.79–2.65], multi-center studies (aOR, 1.73; 95% CI, 1.39–2.16), government-sponsored studies (aOR, 3.09; 95% CI, 1.48–6.42), and published studies (aOR, 1.43; 95% CI, 1.15–1.78) were more likely to be high quality research.ConclusionsTo improve the quality of registration, awareness of prospective registration should be further improved and government investment should be increased. At the same time, more efficient and extensive data sharing after completion of the studies should be actively promoted.
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