LAUSR

We appreciate the perspectives of Dr. Hudzik and colleagues on the potential clinical utility of Gensini score in our study (KorzonekSzlacheta et al., 2018; Guo et al., 2017). Gensini score is one premier tool for assessing the severity of coronary angiopathy. It is used generally for evaluating the relationship between other factors and the biological progression of coronary artery lesions (Liu et al., 2015; Park et al., 2017). For choice in clinical practice, such as stents or bypass surgery for coronary artery disease, or improve the clinical outcome after PCI, we always use the SYNTAX score (Murakami et al., 2014; Stone et al., 2016). We agree with Dr. Hudzik and colleagues that small sample size has low power and reduces the statistically significant. In our study (Guo et al., 2017), the sample size was relatively small. This meant that the subgroups were even smaller, and it may be that the bias for the data and the cofounders for multivariate analysis would be numerous. Larger studies should therefore be performed with the statistical analysis repeated. Fortunately, the small sample size does not influence the value of PTX3 in the risk evaluation of coronary artery disease (CAD) based on statistically significant data (P < .05 and the change of OR). Our results were supported by many statistical methods, such as t-test or Kruskal-Wallis rank sum test, Chi-square test, Univariate logistic regression, Multivariate logistic regression models, Pearson's test, Twoway ANOVA analysis and Receiver-operating characteristic. The correlations of PTX3 and CAD were not strong indeed. Consistently other inflammatory biomarkers, including matrix metalloprotein 9 (MMP9), interleukin-6 (IL-6), and the neutrophil to lymphocyte ratio (NLR) showed weaker correlations. That may be associated with some factors, such as sample size. This study aims to compare the associations between plasma levels of these biomarkers and CAD, identifying the best biomarker that has the most powerful association with CAD. The strong correlations of PTX3 and CAD could be found from many other studies (Liu et al., 2015; Salio et al., 2008). The diagnostic value of CRP and PTX3 was compared in some studies before. PTX3 could be superior to CRP as an inflammatory biomarker for CAD (Liu et al., 2015). However, there are few studies that investigate the association of PTX3 levels and other inflammation biomarkers, including MMP9, IL-6, and NLR, in the setting of CAD. In this report, we have explored and compared the association between PTX3, MMP9, IL-6, and NLR levels and CAD. The results showed that compared to NLR, MMP9, and IL-6, PTX3 displayed greater AUC and association with CAD. PTX3 may become a potentially powerful inflammatory biomarker for CAD.