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Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses.

Abstract：

OBJECTIVES:To evaluate meta-analyses with trial sequential analysis (TSA). TSA adjusts for random error risk and provides the required number of participants (information size) in a meta-analysis. Meta-analyses not reaching information size are analyzed with trial sequential monitoring boundaries analogous to interim monitoring boundaries in a single trial. STUDY DESIGN AND SETTING:We applied TSA on meta-analyses performed in Cochrane Neonatal reviews. We calculated information sizes and monitoring boundaries with three different anticipated intervention effects of 30% relative risk reduction (TSA(30%)), 15% (TSA(15%)), or a risk reduction suggested by low-bias risk trials of the meta-analysis corrected for heterogeneity (TSA(LBHIS)). RESULTS:A total of 174 meta-analyses were eligible; 79 out of 174 (45%) meta-analyses were statistically significant (P<0.05). In the significant meta-analyses, TSA(30%) showed firm evidence in 61%. TSA(15%) and TSA(LBHIS) found firm evidence in 33% and 73%, respectively. The remaining significant meta-analyses had potentially spurious evidence of effect. In the 95 statistically nonsignificant (P>or=0.05) meta-analyses, TSA(30%) showed absence of evidence in 80% (insufficient information size). TSA(15%) and TSA(LBHIS) found that 95% and 91% had absence of evidence. The remaining nonsignificant meta-analyses had evidence of lack of effect. CONCLUSION:TSA reveals insufficient information size and potentially false positive results in many meta-analyses.

journal_name

J Clin Epidemiol

journal_title

Journal of clinical epidemiology

authors

Brok J,Thorlund K,Gluud C,Wetterslev J

doi

10.1016/j.jclinepi.2007.10.007

subject

Has Abstract

pub_date

2008-08-01 00:00:00

pages

763-9

issue

8

eissn

0895-4356

issn

1878-5921

pii

S0895-4356(07)00369-1

journal_volume

61

pub_type

杂志文章

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