HMG-CoA enzyme inhibitors for prevention of contrast-induced nephropathy

Abstract

To the Editor, We read with great interest the recent meta-analysis by Barbieri et al. [1] which showed that among patients undergoing coronary angiography/percutaneous intervention the use of short-term statins reduces the incidence of contrast-induced nephropathy (CIN). In light of increasing numbers of high-risk patients undergoing coronary interventions, the current results along with the findings of recent randomized studies have important implications. In particular, given the absence of other established pharamacological protective options, these results appear to suggest that unless otherwise contraindicated, statin therapy should be considered as a potentially viable intervention to prevent CIN in the ‘‘at-risk’’ population undergoing coronary angiography/interventions. Nevertheless, close inspection of the studies analyzed by the authors revealed some methodological issues that are worth mentioning and clarifying. Adopting the same search methodology as Barbieri et al., we have localized a relevant study by Quintavalle et al. [2] which has not been included in the meta-analysis. Additionally, the authors mention that they used the for fixed effect model analysis. We would like to point out here that the DerSimonian–Laird method is used for random-effects model analysis. In the absence of heterogeneity, pooled estimates of odd risks (ORs) with their 95 % confidence intervals (CIs) were calculated using the Mantel–Haenszel method. A DerSimonian–Laird randomeffects model for ORs estimation of all outcomes was used in the presence of heterogeneity. Moreover, the authors used a heterogeneity test cutoff P value of \0.1. Usually, statistically significant heterogeneity is defined as an X P value less than 0.05 or an I statistic greater than 75 %. We also noticed that the authors suggested there is no evidence of publication bias based on funnel plot methods. We would suggest that the small study effect, including publication bias, should be tested using the Egger’s test. If publication bias is found, the nonparametric trim and fill method of Duvall and Tweedie should be performed to add studies that appeared to be missing. Also, the Cochrane’s risk of bias tool [3] rather than the Jadad score should have been utilized in order to assess the individual risk of bias of each study. The subgroup analysis of studies into lowand highdose statin groups may not be the most appropriate way of approaching this topic. We believe that all studies used high-doses of statins. Finally, analysis of other available outcomes such as all-cause mortality and rates hemodialysis/hemofiltration would have been very helpful. Taking all the above into account provide a corrected estimation of the pooled odds ratio (Fig. 1). We believe that these remarks will contribute to further, more accurate elaboration and substantiation of the original results presented by Barbieri et al. [1].