Local Literature Bias in Genetic Epidemiology: An Empirical Evaluation of the Chinese Literature

Zhenglun Pan, Thomas A Trikalinos, Fotini K Kavvoura, Joseph Lau and John PA Ioannidis

PLOS Medicine, 2005, vol. 2, issue 12, 1-

Abstract: Background: Postulated epidemiological associations are subject to several biases. We evaluated whether the Chinese literature on human genome epidemiology may offer insights on the operation of selective reporting and language biases. Methods and Findings: We targeted 13 gene-disease associations, each already assessed by meta-analyses, including at least 15 non-Chinese studies. We searched the Chinese Journal Full-Text Database for additional Chinese studies on the same topics. We identified 161 Chinese studies on 12 of these gene-disease associations; only 20 were PubMed-indexed (seven English full-text). Many studies (14–35 per topic) were available for six topics, covering diseases common in China. With one exception, the first Chinese study appeared with a time lag (2–21 y) after the first non-Chinese study on the topic. Chinese studies showed significantly more prominent genetic effects than non-Chinese studies, and 48% were statistically significant per se, despite their smaller sample size (median sample size 146 versus 268, p

Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020334 (text/html)
https://journals.plos.org/plosmedicine/article/fil ... 20334&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pmed00:0020334

DOI: 10.1371/journal.pmed.0020334

Access Statistics for this article

More articles in PLOS Medicine from Public Library of Science
Bibliographic data for series maintained by plosmedicine ().