Randomized clinical trials in HEPATOLOGY: predictors of quality

Hepatology. 1999 Nov;30(5):1134-8. doi: 10.1002/hep.510300510.

Abstract

Evidence shows that the quality of randomized clinical trials (RCTs) affects estimates of intervention efficacy, which is significantly exaggerated in low-quality trials. The present study examines the quality of all 235 RCTs published in HEPATOLOGY from the initiation in 1981 through August 1998. Quality was assessed by means of a validated 5-point scale and separate quality components associated with empirical evidence of bias. Only 26% of all RCTs reported sample size calculations, 52% adequate generation of the allocation sequence, 34% adequate allocation concealment and 34% double-blinding. The median quality score of all trials was 3 points (range, 1-5 points). Multiple logistic regression analysis explored the association between quality and therapeutic areas, number of centers, external funding, year of publication, and country of origin. High-quality trials were most likely to investigate portal hypertension (odds ratio [OR]: 2.4; 95% CI: 1.1-5.5; P =.03), be multicentered (OR: 3.4; 95% CI: 1.3-8.9; P =.01), sponsored by public organizations (OR: 4.2; 95% CI: 2.1-8.6; P =.0001), or the drug and device industry (OR: 4.7; 95% CI: 2.2-10.2; P =.0001) compared with other therapeutic areas, single-center trials, and trials with no external funding. Quality did not improve with time and was not associated with country of origin. The main conclusions are that the quality of RCTs in HEPATOLOGY needs improvement and that the probability of high quality increased with the number of centers involved and external funding.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bias
  • Clinical Trials as Topic / statistics & numerical data
  • Ethics, Medical
  • Gastroenterology / standards*
  • Humans
  • Liver Diseases / therapy*
  • MEDLINE
  • Periodicals as Topic*
  • Randomized Controlled Trials as Topic / standards*
  • Randomized Controlled Trials as Topic / statistics & numerical data
  • Reproducibility of Results
  • Research Design
  • United States