Statistical Use in Clinical Studies: Is There Evidence of a Methodological Shift?

• Published in: PloS one Vol. 10; no. 10; p. e0140159
• Main Authors: Yi, Dali, Ma, Dihui, Li, Gaoming, Zhou, Liang, Xiao, Qin, Zhang, Yanqi, Liu, Xiaoyu, Chen, Hongru, Pettigrew, Julia Christine, Yi, Dong, Liu, Ling, Wu, Yazhou
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 08.10.2015; Public Library of Science (PLoS)
• Subjects: Bias; Clinical trials; Collaboration; Confidence intervals; Content analysis; Control methods; Curricula; Data analysis; Data collection; Data Interpretation, Statistical; Education; Genomes; Health care; Health education; Humans; Management; Mathematical models; Medical research; Medicine; Models, Statistical; Observational studies; Pediatrics; Preventive medicine; Randomized Controlled Trials as Topic - methods; Regression analysis; Research Design; Software; Statistical analysis; Statistical methods; Statistics; Studies; Survival analysis; Training; Trends; United States; United States > US; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0140159

Several studies indicate that the statistical education model and level in medical training fails to meet the demands of clinicians, especially when they want to understand published clinical research. We investigated how study designs and statistical methods in clinical studies have changed in the last twenty years, and we identified the current trends in study designs and statistical methods in clinical studies. We reviewed 838 eligible clinical study articles that were published in 1990, 2000, and 2010 in four journals New England Journal of Medicine, Lancet, Journal of the American Medical Association and Nature Medicine. The study types, study designs, sample designs, data quality controls, statistical methods and statistical software were examined. Substantial changes occurred in the past twenty years. The majority of the studies focused on drug trials (61.6%, n = 516). In 1990, 2000, and 2010, there was an incremental increase in RCT studies (74.4%, 82.8%, and 84.0%, respectively, p = 0.013). Over time, there was increased attention on the details of selecting a sample and controlling bias, and there was a higher frequency of utilizing complex statistical methods. In 2010, the most common statistical methods were confidence interval for superiority and non-inferiority comparison (41.6%), survival analysis (28.5%), correction analysis for covariates (18.8%) and Logistic regression (15.3%). These findings indicate that statistical measures in clinical studies are continuously developing and that the credibility of clinical study results is increasing. These findings provide information for future changes in statistical training in medical education.