Racial/ethnic differences in the prognostic utility of left ventricular mass index for incident cardiovascular disease

Abstract

Background

Evidence exists for racial/ethnic differences in left ventricular mass index (LVMI). How this translates to future cardiovascular disease (CVD) events is unknown.

Hypothesis

The impact of racial/ethnic differences in LVMI on incident cardiovascular outcomes could have potential implications for the optimization of risk stratification strategies.

Methods

Using the prospectively collected database of the Multi‐Ethnic Study of Atherosclerosis (MESA) involving 4 racial/ethnic groups (non‐Hispanic Whites, Chinese, Blacks, and Hispanics) free of CVD at baseline, we assessed for racial/ethnic differences in the relationship between LVMI and incident CVD using a Cox model.

Results

5004 participants (mean age, 62 ± 10 years; 48% male) were included in this study. After an average follow‐up of 10.2 years, 369 (7.4%) CVD events occurred. Significant racial/ethnic differences existed in the relationship between LVMI and incident CVD (P for interaction = 0.04). Notably, the relationship was strongest for Chinese (HR per 10‐unit increase in LVMI: 1.7, 95% CI: 1.1–2.8) and Hispanics (HR per 10‐unit increase in LVMI: 1.9, 95% CI: 1.5–2.2). Non‐Hispanic Whites demonstrated the lowest relationship (HR: 1.3, 95% CI: 1.1–1.5). LVMI values of 36.9 g/m^2.7, 31.8 g/m^2.7, 39.9 g/m^2.7, and 41.7 g/m^2.7 were identified as optimal cutpoints for defining left ventricular hypertrophy (LVH) for non‐Hispanic Whites, Chinese, Blacks, and Hispanics, respectively. In secondary analysis of LVH (vs no LVH) using these optimal cutpoints, we found a similar pattern of association as above (P for interaction = 0.04). For example, compared with those without LVH, Chinese with LVH had HR: 5.3, 95% CI: 1.6–17, whereas non‐Hispanic Whites with LVH had HR: 1.6, 95% CI: 1.2–2.1 for CVD events.

Conclusions

Among 4 races/ethnicities studied, LVMI has more prognostic utility predicting future CVD events for Chinese and Hispanics and is least significant for non‐Hispanic Whites.

1. INTRODUCTION

Heart disease continues to be the leading cause of mortality globally.1 To address this menacing trend in cardiovascular disease (CVD), the importance of accurate risk assessment cannot be overstated. Although several risk factors have been associated with cardiovascular (CV) events, at the center of most of these events is the functional state of the left ventricle (LV)—the major pumping chamber of the heart. LV mass, which is a key determinant of LV function, has been shown to be a strong predictor of major adverse CV events including heart failure (HF), stroke, and coronary heart disease (CHD).2, 3, 4 In randomized trials, therapeutic intervention to regress the LV mass resulted in decrease in CV morbidity and mortality,5, 6, 7 thereby confirming LV mass as an important subclinical marker of CVD events.

Accumulating evidence, however, supports racial/ethnic differences in CV outcomes. For example, in the United States, Blacks tend to have higher rates of first stroke, myocardial infarction, and age‐adjusted CV mortality.8, 9 Although these differences may be related in part to differences in CV risk factors,10, 11, 12 an important commonly missed concept in addressing the role of these risk factors is the interplay between the modifiable risk factors and the nonmodifiable ones, like race/ethnicity. Prior studies have suggested racial/ethnic differences in LV mass13, 14; however, there is a lack of information on how these differences translate to CV outcomes. Given that the LV mass possibly represents a common pathway for various other modifiable cardiac risk factors, including body mass index, blood pressure, diabetes mellitus (DM), smoking, exercise, and dietary pattern, among others,15, 16, 17 identifying racial/ethnic differences in their impact on CV outcome has the potential to further identify racial/ethnic groups in which it has greater utility for risk reclassification as well as those that may benefit from therapeutic intervention to regress LV mass.

2. METHODS

2.1. Participants

This clinically important question was explored using the prospectively collected database of the Multi‐Ethnic Study of Atherosclerosis (MESA), an initiation of the National Heart, Lung, and Blood Institute (NHLBI) that includes participants free of CVD at baseline and followed for >10 years. Details of the design and conduct of MESA have been published elsewhere.18 Briefly, 6814 adults who were free of CVD were enrolled from 6 US cities: Baltimore (Maryland), Chicago (Illinois), Forsyth (North Carolina), Los Angeles (California), New York (New York), and St. Paul (Minnesota). Racial distribution in the full cohort includes 38% non‐Hispanic White, 11% Chinese, 28% Black, and 23% Hispanic. The MESA study also represents the first epidemiologic study that used cardiac magnetic resonance imaging (cMRI) in a large cohort to evaluate subclinical CVD. At baseline examination between 2000 and 2002, data on demographics and CV risk factors were assessed among all participants while cMRI was performed in ~75% of the participants.

The study was approved by the institutional review boards at all participating centers, and all participants gave informed consent. Only participants who underwent cMRI assessment were included in our investigation.

2.2. LV mass assessment

The cMRI protocol and interpretation of LV parameters have been described previously.4, 19 Briefly, using 1.5 T magnets with a 4‐element phased‐array surface coil, all images were captured at resting lung volumes with short (12–15 seconds) breathholding. With the 4‐element phased‐array surface coil placed anteriorly and posteriorly and concomitant electrocardiographic gating and blood pressure monitoring, a series of short‐ and long‐axis cine images was captured to include the entire LV. Contouring of the epicardial and endocardial borders was done semiautomatically at end‐diastole and end‐systole using the MASS software package, version 4.2 (Medis, Leiden, Netherlands). After excluding the papillary muscle, LV mass was calculated as the sum of the myocardial area (ie, difference between endocardial and epicardial areas) multiplied by the slice thickness and image gap in end‐diastole, and then multiplied by the specific gravity of myocardium (1.05 g/mL). The interobserver technical error of measurement percent of the mean (TEM%) was 6.0%, with an intraclass correlation coefficient of 0.98. The intraobserver TEM% was 6.3%, with intraclass correlation coefficient of 0.97.

For the purpose of this study, left ventricular mass index (LVMI) was calculated by dividing the LV mass (in grams) by the participant's height (in meters) raised to allometric power of 2.7, as proposed by de Simone et al.20 Such standardization of LV mass was necessary to adjust for variability by body size, which in turn varies by ethnicity. Compared with other methods of indexation, use of height raised to allometric power has been shown to be better at identifying high‐risk patients.20, 21

2.3. Endpoints

The primary endpoint assessed in this study was any incident CVD event (including CHD, fatal or nonfatal stroke, and other CVD death). In addition, as secondary endpoints we assessed incident CHD events (including myocardial infarction, resuscitated cardiac arrest, angina, and CHD death), HF, atrial fibrillation (AF), and all‐cause mortality. Detailed description of the methods involved in follow‐up and ascertainment of CVD event and mortality in the MESA cohort has been previously published.22 Briefly, after initial examination, trained personnel contacted participants or family members every 9 to 12 months to inquire about CVD events or death. Information about self‐reported CVD events was verified via review of medical records; in case of mortality, cause of death was identified via review of death certificate as well as interview of the next of kin. Final classification of an event was decided independently by 2 physicians who were members of the Morbidity and Mortality Committee. In case of disagreement between the physicians, the final decision was made by the full committee.

2.4. Covariate assessment

Data on baseline demographics and CV risk factors were gathered during initial examination between 2000 and 2002 via standard questionnaire and routine method of assessment. DM was defined per 2003 American Diabetic Association (ADA) fasting criteria as fasting glucose ≥126 mg/dL or use of antidiabetic medication; hypertension (HTN) was defined per Joint National Committee guideline as blood pressure > 140/90 mmHg or use of antihypertensive medication; current smoking was defined as a smoker with most recent smoking within the last 30 days; physical activity (or exercise) was measured through self‐administered questionnaire by calculating the metabolic equivalent‐hours (MET‐hrs) per week; and cholesterol levels were measured in EDTA plasma using standardized cholesterol oxidase method (Roche Diagnostics, Indianapolis, IN) with laboratory coefficient of variation of 1.6% for total cholesterol (TC).

2.5. Statistical analysis

Analyses were conducted in 2 parts. First we assessed racial/ethnic differences in LV mass. Baseline characteristics were compared between race/ethnicity using the χ² test for categorical variables, analysis of variance (ANOVA) for normally distributed continuous variables, and the Kruskal‐Wallis test for continuous variables with skewed distribution. LVMI was calculated for each race/ethnicity as mean ± SD. To evaluate for LV mass differences between race/ethnicity, we used a linear regression model to adjust for important covariates including age, sex, HTN, DM, TC, smoking status, alcohol use, height, weight, physical activity (or exercise), mean arterial pressure, pulse rate, and measures of socioeconomic status (ie, income, education level, and occupation). Statistical significance of the difference between all 4 races/ethnicities was determined by a linear contrast of the regression coefficients from the linear regression model. Subsequently, pairwise comparison was conducted between races/ethnicities with Bonferroni correction for multiple comparisons.

Second, we evaluated the impact of racial/ethnic differences in LVMI on our prespecified clinical endpoints: time to first occurrence of CVD, CHD, HF, AF, and all‐cause mortality (in separate analysis). These analyses were done by a Cox proportional hazard model that adjusted for similar covariates as above but with inclusion of a multiplicative interaction term for the continuous form of LVMI and the categorical form of race/ethnicity. Racial/ethnic differences in the relationship between LVMI and each endpoint were considered significant if the Wald test of the joint effect of the interaction term was statistically significant at P < 0.05. Estimates are reported as hazard ratio (HR) and 95% confidence interval (CI) for each endpoint per 10‐unit increase in LVMI within each race/ethnicity. In secondary analysis, we evaluated for the optimal cutpoint for defining left ventricular hypertrophy (LVH) within each race/ethnicity using an outcome‐driven approach, as recommended by the American Society of Echocardiography and the European Association of Echocardiography.21 Using CVD event as the primary outcome of interest, the optimal discriminatory cutpoint was evaluated based on the Youden index,23, 24 which identifies the single cutpoint on the receiver operating characteristics (ROC) curve that maximizes the sum of the sensitivity and specificity‐1. Lastly, racial/ethnic differences in the relationship between LVH and CVD events were evaluated as above.

All analyses were performed using Stata software version 14 (StataCorp, LP, College Station, TX) with level of significance set at 0.05.

3. RESULTS

A total of 5004 participants (mean age, 62 ± 10 years; 48% males) who had cMRI evaluation at baseline examination of MESA were included in this study (Table 1). Racial distribution was 39% non‐Hispanic White, 13% Chinese, 26% Black, and 22% Hispanic. Prevalent comorbidities and CV risk factors tend to be worse in Blacks than in other races. For example, Blacks tend to have higher rates of DM (17%), HTN (57%), and smoking (18%), as well as highest BMI (mean, 29 ± 5.2 kg/m²). On the other hand, TC was highest among Hispanics (mean, 198 ± 36 mg/dL), whereas the rate of alcohol use was highest among Whites. Anthropometric measures were generally lower among Chinese compared with other races/ethnicities. Mean LV mass was 143 ± 38 g among non‐Hispanic Whites, 123 ± 30 g among Chinese, 158 ± 42 g among Blacks, and 146 ± 38 g among Hispanics (Figure 1). There was overall significant difference in LV mass across all 4 races/ethnicities (P < 0.001). However, in pairwise comparison, there was no significant difference between non‐Hispanic Whites and Chinese (P = 0.13), as well as between Blacks and Hispanics (P = 0.68; see Supporting Information Table 1, in the online version of this article). All other pairwise comparisons were statistically significant, even with Bonferroni correction (ie, P < 0.004). Following indexation, mean LVMI was 34.6 ± 7.2 g/m^2.7 for non‐Hispanic Whites, 33.5 ± 6.4 g/m^2.7 for Chinese, 38.3 ± 8.6 g/m^2.7 for Blacks, and 39.4 ± 8.4 g/m^2.7 for Hispanics; and pairwise comparison was similar to the nonindexed LV mass as above.

Table 1.

Baseline characteristics of participants who had cMRI evaluation at the initial examination of MESA, stratified by race/ethnicity

	Total, N = 5004	Non‐Hispanic White, n = 1957	Chinese, n = 654	Black, n = 1284	Hispanic, n = 1109	P Value
Age, y	62 ± 10	62 ± 10	62 ± 10	62 ± 9.9	60 ± 10	<0.001
Male sex, %	48	47	49	45	50	0.14
DM, %	12	5.7	12	17	16	<0.001
HTN, %	42	36	37	57	40	<0.001
TC, mg/dL	194 ± 35	195 ± 35	192 ± 31	190 ± 37	198 ± 36	<0.001
Height, m	1.7 ± 0.1	1.7 ± 9.6	1.6 ± 8.4	1.7 ± 9.6	1.6 ± 9.2	<0.001
Weight, lbs	173 ± 38	175 ± 37	138 ± 24	188 ± 38	170 ± 33	<0.001
BMI, kg/m2	28 ± 4.9	27 ± 4.7	24 ± 3.2	29 ± 5.2	29 ± 4.5	<0.001
BSA, m2	1.8 ± 0.22	1.9 ± 0.22	1.7 ± 0.17	1.9 ± 0.21	1.8 ± 0.18	<0.001
Smoker, %	13	11	5.4	18	14	<0.001
Current alcohol use, %	69	78	68	60	64	<0.001
Exercise, MET‐hr/wk, median (IQR)	50 400 (9900 – 126000)	63 000 (18900 – 135000)	44 100 (0 – 88200)	57 600 (10800 – 138600)	37 800 ( 0 – 107550)	<0.001
SBP, mm Hg	125 ± 21	122 ± 20	123 ± 21	131 ± 21	126 ± 22	<0.001
MAP, mm Hg	99 ± 14	97 ± 14	97 ± 14	103 ± 14	99 ± 14	<0.001
Pulse pressure, mm Hg	54 ± 17	52 ± 16	52 ± 17	56 ± 17	54 ± 18	<0.001
Pulse rate, bpm	64 ± 10	63 ± 10	65 ± 9.0	64 ± 10	64 ± 10	<0.001
LV mass, g	145 ± 40	143 ± 38	123 ± 30	158 ± 42	146 ± 38	<0.001

Abbreviations: BMI, body mass index; BSA, body surface area; cMRI, cardiac magnetic resonance imaging; DM, diabetes mellitus; HTN, hypertension; IQR, interquartile range; LV, left ventricular; MAP, mean arterial pressure; MESA, Multi‐Ethnic Study of Atherosclerosis; MET‐hr, metabolic equivalent‐hours; SBP, systolic blood pressure; SD, standard deviation; TC, total cholesterol.

Data are presented as mean ± SD unless otherwise indicated.

Figure 1.

Left ventricular mass, mean ± SD, stratified by ethnicity. There was overall difference among all ethnic groups (P < 0.001), although there was no significant difference between the non‐Hispanic White and Chinese groups (P = 0.13) as well as between the Black and Hispanic groups (P = 0.68) in subgroup analyses. P values were derived after adjusting for age, sex, HTN, DM, TC, smoking status, alcohol use, height, weight, physical activity (or exercise), MAP, and pulse rate in a multivariable regression model. Abbreviations: DM, diabetes mellitus; HTN, hypertension; MAP, mean arterial pressure; SD, standard deviation; TC, total cholesterol

After a mean‐follow up of 10.2 years, there were 369 (7.4%) CVD events (including 268 [5.4%] CHD events), 122 (2.4%) cases of HF, 274 (5.5%) cases of AF, and 348 (7%) incidents of all‐cause mortality. Over the study period, rates of incident CVD, CHD, and AF were highest among non‐Hispanic Whites; HF and all‐cause mortality were highest among Blacks; but the risk of these endpoints tended to be lower among Chinese (see Supporting Information, Table 2, in the online version of this article). When we evaluated the association between LVMI and CVD events, we found significant racial/ethnic differences in this relationship (P for interaction = 0.04). Specifically, the relationship was strongest among Chinese and Hispanics (HR [per 10‐unit increase in LVMI]: 1.7, 95% CI: 1.1–2.8, and HR: 1.9, 95% CI: 1.5–2.2, respectively). The relationship was weakest for non‐Hispanic Whites (HR: 1.3, 95% CI: 1.1–1.5). Similarly, based on ROC analysis, LVMI had the most prognostic utility among Chinese and Hispanics, with area under the ROC curve of 0.67 and 0.66, respectively (Figure 2). On the other hand, the area under the ROC curve was lowest for non‐Hispanic Whites, at 0.59. In secondary analysis, LVMI cutpoints of 36.9 g/m^2.7, 31.8 g/m^2.7, 39.9 g/m^2.7, and 41.7 g/m^2.7 were identified as the optimal cutpoints for predicting CVD events among non‐Hispanic Whites, Chinese, Blacks, and Hispanics, respectively. Further analysis of LVH (vs no LVH) using these optimal cutpoints also showed a stronger relationship with CVD events among Chinese (HR: 5.3, 95% CI: 1.6–17) and Hispanics (HR: 3.1, 95% CI: 1.7–4.3; Figure 3), and there were significant racial/ethnic differences (P for interaction = 0.04). Overall, we found similar results when we restricted analysis to only CHD events.

Table 2.

Relationship between LVMI and clinical endpoints within each race/ethnic group^a

	Non‐Hispanic White, HR (95% CI)	Chinese, HR (95% CI)	Black, HR (95% CI)	Hispanic, HR (95% CI)	P for Interaction
CVD	1.3 (1.1–1.5), P = 0.02	1.7 (1.1–2.8), P = 0.02	1.4 (1.2–1.6), P = 0.01	1.9 (1.5–2.2), P < 0.001	0.04
CHD	1.3 (0.99–1.5), P = 0.05	1.3 (0.71–2.2), P = 0.40	1.4 (1.0–1.63), P = 0.01	2.0 (1.4–3.0), P < 0.001	0.03
HF	2.8 (1.8–4.4), P < 0.001	3.2 (1.1–9.3), P = 0.03	1.7 (1.3–2.2), P < 0.001	3.7 (2.3–5.9), P < 0.001	0.08
AF	1.6 (1.2–2.0), P < 0.001	1.6 (0.72–3.6), P = 0.25	1.3 (0.93–1.7), P = 0.13	2.0 (1.3–3.0), P = 0.002	0.36
All‐cause mortality	1.1 (0.79–1.4), P = 0.76	1.8 (0.99–3.3), P = 0.06	1.3 (1.1–1.6), P = 0.009	1.8 (1.4–2.5), P < 0.001	0.45

Abbreviations: AF, atrial fibrillation; CHD, coronary heart disease; CI, confidence interval; CVD, cardiovascular disease; HF, heart failure; HR, hazard ratio; LVMI, left ventricular mass index.

^aEstimates represent HR (with 95% CI) for each clinical endpoint per 10‐unit increase in LVMI.

Figure 2.

ROC curves for the univariate association between LVMI and incident CVD events in non‐Hispanic Whites (first row), Chinese (second row), Blacks (third row), and Hispanics (fourth row). Left panels are area under the ROC curves. Right panels represent variation in sensitivity and specificity according to LVMI values, with LVMI cutpoints of 36.9 g/m^2.7, 31.8 g/m^2.7, 39.9 g/m^2.7, and 41.7 g/m^2.7 (indicated by the vertical red lines) representing the optimal cutpoints for defining LVH for non‐Hispanic Whites, Chinese, Blacks, and Hispanics, respectively. Abbreviations: CVD, cardiovascular disease; LVH, left ventricular hypertrophy; LVMI, left ventricular mass index; ROC, receiver operating characteristic

Figure 3.

Cumulative incidence of CVD events, according to presence or absence of LVH (P for interaction = 0.04). Abbreviations: CVD, cardiovascular disease; HR, hazard ratio; LVH, left ventricular hypertrophy

When we evaluated secondary endpoints of HF, AF, and all‐cause mortality, the association between LVMI and these endpoints tended to be stronger for Chinese and Hispanics than for other races (Table 2). For example, these are the associations between LVMI and incident HF for the different race/ethnicities: Chinese (HR: 3.2, 95% CI: 1.1–9.3) and Hispanic (HR: 3.7, 95% CI: 2.3–5.9), compared with non‐Hispanic White (HR: 2.8, 95% CI: 1.8–4.4) and Black (HR: 1.7, 95% CI: 1.3–2.2). However, we did not find a statistically significant racial/ethnic difference when we tested for interaction for all 3 secondary endpoints (P for interaction ≥0.08).

4. DISCUSSION

In this multi‐ethnic population of asymptomatic patients free of CVD at baseline, we found significant racial/ethnic differences in LVMI. Namely, LVMI was generally higher for Blacks and Hispanics than for non‐Hispanic Whites and Chinese. In addition, there were significant racial/ethnic differences in the relationship between LVMI (or LVH) and incident CVD (including CHD). Specifically, we found that the relationship between LVMI (or LVH) and these endpoints was strongest for Chinese and Hispanics but less so for non‐Hispanic Whites. On the other hand, we did not find significant racial/ethnic differences in the relationship between LVMI and incident HF, AF, and all‐cause mortality.

Racial/ethnic differences in CV morbidity and mortality have been widely documented.8, 25, 26 However, most of these differences have been widely attributed to differences in CV risk factors or access to healthcare,10, 27 but with little attention to biological differences. In our study, we demonstrated racial/ethnic differences in LVMI among asymptomatic adults. In addition, we showed that this biological difference has prognostic implications in predicting future adverse CV events independent of other traditional CV risk factors. Notably, we adjusted for the potential confounding influence of these CV risk factors to provide a clearer understanding of racial/ethnic differences. Although the exact potential mechanism for this racial/ethnic difference is not known, nor can it be fully tested in the current analysis, several potential mechanisms likely play a role. For example, genetic variation between races likely culminates in differential outcomes or responses to adverse stimuli.28, 29, 30 For example, accumulating evidence suggests racial differences in response to CV drugs,31 as well as in the relationship between blood pressure component and incident CVD.32 Though differences in LVMI may be partly explained by differences in CV risk factors (eg, HTN and DM were higher among Blacks and Hispanics who had high LVMI compared with non‐Hispanic Whites and Chinese), the stronger relationship between LVMI and clinical endpoints in Hispanics compared with Blacks could not be explained by difference in distribution of risk factors or magnitude of the LVMI, which were similar between these 2 races. Therefore, other unmeasured factors such as genetic variation likely contribute. More studies, however, are needed to clearly delineate the exact cause of these racial/ethnic differences.

Racial/ethnic differences in the association between CV risk factors and CVD endpoints have been reported in the literature.32, 33, 34, 35 However, little is known about the impact of racial/ethnic differences in LVMI. Studies from multi‐ethnic populations including MESA, the National Health and Nutrition Examination Survey (NHANES), and the Cardiovascular Health Study have demonstrated an association between LVMI and incident HF, stroke, CHD, and CV mortality.3, 4, 36 However, potential ethnic differences in these associations were ignored in most of the analyses. Havranek et al., in a study of the relationship between electrocardiographic LVH and CV mortality,37 demonstrated racial/ethnic differences somewhat similar to ours. Specifically, they found that the association between LVH and 10‐year CV mortality was higher in Blacks and Latinos than among Whites. However, the Chinese population was not included in the study. To our knowledge, our findings represent the first empirical evidence of the impact of racial/ethnic differences in LVMI on future CV events.

Our findings have important clinical implications. First, they suggest that the role of LV mass for CV risk stratification varies by race/ethnicity: Chinese and Hispanics are more likely to benefit from risk prediction or stratification with LV mass than are other races. Hence, compared with other races, LV mass may have better utility when included in an ethnic‐specific risk‐stratification algorithm or a model for Chinese and Hispanics. Alternatively, these groups may benefit more from LV mass regression to reduce adverse CV events than other races. This may be very important in deciding the optimal antihypertensive choice in lowering CV events for these 2 races/ethnicities,5 especially if this theory is confirmed in future randomized trials. Second, our study highlights the need for cautious interpretation of studies evaluating the predictive ability of LVMI. Careful evaluation of the racial/ethnic distribution of the study population needs to be considered for a valid and unbiased interpretation of the study estimates.

4.1. Study limitations

Potential limitations of our study also need to be considered. First, due to the observational nature of the study, it is not possible to claim a causal link between LVMI and the clinical endpoints examined in this study. However, we mitigated against potential confounding of the result by adjusting for important covariates in our analysis. Second, compared with other races/ethnicities, the sample size was relatively small for the Chinese group, and this, in a way, might have underpowered the analysis for Chinese, especially for other secondary endpoints in which there was no statistically significant association with LVMI. Third, this study did not evaluate for LV remodeling. We believe racial/ethnic differences in the prognostic utility of LV remodeling are also an important but separate concept that should be evaluated in future studies primarily designed to do so.

5. CONCLUSION

We found significant racial/ethnic differences in the relationship between LVMI and incident CVD (including CHD). Notably, the relationship was strongest among Chinese and Hispanics compared with other races. Therefore, LVMI may have differential prognostic utility in predicting future CV events between races/ethnicities. Future studies are needed to explore whether therapeutic interventions to regress LV mass demonstrate similar racial/ethnic differences in their impact on incident CV events.

Conflicts of interest

The authors declare no potential conflicts of interest.

Supporting information

Table S1. P‐values for pairwise comparison of left ventricular mass index between the four racial/ethnic groups

Table S2. Rates of clinical endpoint for each race/ethnic group after a mean follow up of 10.2 years

Akintoye E, Mahmoud K, Shokr M, et al. Racial/ethnic differences in the prognostic utility of left ventricular mass index for incident cardiovascular disease. Clin Cardiol. 2018;41:502–509. 10.1002/clc.22914