Letter by Wu and Zhao Regarding Article, "Effects of Sacubitril-Valsartan Versus Valsartan in Women Compared With Men With Heart Failure and Preserved Ejection Fraction: Insights From PARAGON-HF".

July 7, 2020 e3 Kai Wu, MD Song Zhao, PhD To the Editor: We read with interest the study by McMurray et al1 evaluating the effects of sacubitril-valsartan, versus valsartan, in women and men with heart failure and preserved ejection fraction. The results showed that, in comparison with valsartan, sacubitril-valsartan reduced the risk of hospitalization attributable to heart failure (HF) in women in comparison with men. After reading this article carefully, we suggest the following. First, the definition or threshold of natriuretic peptide level in this article is vague, even unclear. Specified value was not reported in this study, which could easily lead to misunderstanding. In clinical practice, a series of factors can affect NT-ProBNP (N-terminal pro-B–type natriuretic peptide) level, including age, sex, body weight, atrial fibrillation, severity of cardiac function, and estimated glomerular filtration rate. In this study, the authors considered the effect of atrial fibrillation on NTProBNP level but did not describe the influence of other factors on NT-ProBNP level, especially in patients >75 years of age,2 which might lead to bias in the assessment of HF. In addition, the diagnosis of HF was not reported. Is the diagnosis of HF judged by 1 clinician or by >2 clinicians? These descriptions are not clear in this article. In addition, it is also unknown whether the diagnosis of HF is consistent between 2 different clinicians. Second, Cox regression was used to compare the differences between groups in this study. However, the data of this study do not meet the requirements of Cox regression analysis, which can be seen clearly in Figure 1A and 1B. There are obvious intersections between the 2 curves in Figure 1A and 1B, which means that the 2 curves do not meet a proportional hazard assumption.3 The definition of proportional hazard hypothesis is that the effect of covariates on survival rate does not change with time. However, in the process of survival analysis, the influence of some variables on hazard function will change correspondingly with time; thus, it is necessary to assess the proportional hazard hypothesis before using the Cox regression model for data analysis. Only when the proportional hazard assumption is satisfied are the results of the Cox regression model meaningful. Third, the basis for adjusting covariates is not clear. As the authors described in Statistical Analysis, “age, heart rate, systolic blood pressure, body mass index, smoking status, NT-proBNP (log), eGFR, NYHA class, LVEF, prior HF hospitalization, myocardial infarction, diabetes, and atrial fibrillation were adjusted. ” However, we are curious about the basis for adjusting these factors, because there are many different covariates in Table 1, such as pulse pressure, heart rate, waist circumference, waist/hip ratio, history of medications, and diseases. Why not adjust other covariates with differences (P<0.05) in Table 1? The basis for adjusting those covariates is not reported, which is confusing. We suggest using least absolute shrinkage and © 2020 American Heart Association, Inc. LETTER TO THE EDITOR Letter by Wu and Zhao Regarding Article, “Effects of Sacubitril-Valsartan Versus Valsartan in Women Compared With Men With Heart Failure and Preserved Ejection Fraction: Insights From PARAGON-HF” Circulation