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Abstract
Although it is widely recommended that clinical trials undergo some type of quality
review, the number and variety of quality assessment scales that exist make it unclear
how to achieve the best assessment.
To determine whether the type of quality assessment scale used affects the conclusions
of meta-analytic studies.
Meta-analysis of 17 trials comparing low-molecular-weight heparin (LMWH) with standard
heparin for prevention of postoperative thrombosis using 25 different scales to identify
high-quality trials. The association between treatment effect and summary scores and
the association with 3 key domains (concealment of treatment allocation, blinding
of outcome assessment, and handling of withdrawals) were examined in regression models.
Pooled relative risks of deep vein thrombosis with LMWH vs standard heparin in high-quality
vs low-quality trials as determined by 25 quality scales.
Pooled relative risks from high-quality trials ranged from 0.63 (95% confidence interval
[CI], 0.44-0.90) to 0.90 (95% CI, 0.67-1.21) vs 0.52 (95% CI, 0.24-1.09) to 1.13 (95%
CI, 0.70-1.82) for low-quality trials. For 6 scales, relative risks of high-quality
trials were close to unity, indicating that LMWH was not significantly superior to
standard heparin, whereas low-quality trials showed better protection with LMWH (P<.05).
Seven scales showed the opposite: high quality trials showed an effect whereas low
quality trials did not. For the remaining 12 scales, effect estimates were similar
in the 2 quality strata. In regression analysis, summary quality scores were not significantly
associated with treatment effects. There was no significant association of treatment
effects with allocation concealment and handling of withdrawals. Open outcome assessment,
however, influenced effect size with the effect of LMWH, on average, being exaggerated
by 35% (95% CI, 1%-57%; P= .046).
Our data indicate that the use of summary scores to identify trials of high quality
is problematic. Relevant methodological aspects should be assessed individually and
their influence on effect sizes explored.