PLoS ONE (May 2010)

A retrospective survey of research design and statistical analyses in selected Chinese medical journals in 1998 and 2008.

  • Zhichao Jin,
  • Danghui Yu,
  • Luoman Zhang,
  • Hong Meng,
  • Jian Lu,
  • Qingbin Gao,
  • Yang Cao,
  • Xiuqiang Ma,
  • Cheng Wu,
  • Qian He,
  • Rui Wang,
  • Jia He

DOI
https://doi.org/10.1371/journal.pone.0010822
Journal volume & issue
Vol. 5, no. 5
p. e10822

Abstract

Read online

BackgroundHigh quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium.Methodology/principal findingsTen (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, pConclusions/significanceChinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative.