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Relation of red blood cell distribution width to risk of major adverse cardiovascular events, death, and effect of alirocumab after acute coronary syndromes

Open AccessPublished:August 20, 2022DOI:https://doi.org/10.1016/j.jacl.2022.08.004

      Highlights

      • RDW independently associates with risk of MACE and death in patients with recent ACS.
      • RDW adds to information provided by other risk factors and biomarkers, such as hs-CRP.
      • RDW is an existing component of the complete blood count.
      • As such, RDW provides useful predictive information after ACS at no incremental cost.
      Elevated red blood cell distribution width (RDW) is associated with increased risk for major adverse cardiovascular events (MACE) and death in patients with cardiovascular disease. The ODYSSEY OUTCOMES trial compared alirocumab with placebo in 18,924 patients with recent acute coronary syndrome (ACS) and elevated atherogenic lipoproteins despite optimized statin treatment. This post hoc analysis determined whether RDW independently predicts risk of MACE and death in patients after recent ACS, whether RDW influences MACE reduction with alirocumab, and whether alirocumab treatment affects RDW. Associations of baseline RDW with risk of MACE and death were analyzed in the placebo group in adjusted proportional hazards models. Interactions of RDW and treatment on the risk of MACE and death were evaluated. An increasing quartile of RDW was associated with characteristics that predicted risk of MACE and death including age, hypertension, diabetes, atherosclerotic conditions and events, revascularizations, low-density lipoprotein cholesterol, and high-sensitivity C-reactive protein. After adjusting for baseline characteristics associated with the risk of MACE or death, baseline RDW remained independently associated with the risk of MACE and death in the placebo group (hazard ratios [95% confidence intervals] 1.08 [1.02–1.15] and 1.13 [1.03–1.24] per 1% increase of RDW, respectively, both p <0.001). There was no interaction of RDW and treatment on MACE or death, nor did alirocumab affect RDW. RDW was associated with an increased risk of MACE and death, independent of established risk factors.

      Keywords

      Introduction

      Red blood cell distribution width (RDW) reflects the variability in red blood cell volumes. A normal RDW typically ranges from 12–15%, depending upon the testing laboratory.
      • McPherson R.A.
      • Pincus MR.
      Henry's Clinical Diagnosis and Management by Laboratory Methods.
      Elevated RDW has been associated with an increased risk for death and major adverse cardiovascular events (MACE) in patients with a history of cardiovascular disease.
      • Bujak K.
      • Wasilewski J.
      • Osadnik T.
      • et al.
      The prognostic role of red blood cell distribution width in coronary artery disease: a review of the pathophysiology.
      ,
      • Turcato G.
      • Serafini V.
      • Dilda A.
      • et al.
      Red blood cell distribution width independently predicts medium-term mortality and major adverse cardiac events after an acute coronary syndrome.
      The basis for this association is uncertain, but may include abnormal blood rheology or heightened inflammation. Elevated RDW has been associated with reduced red blood cell deformability and decreased microvascular perfusion, and resultant tissue hypoxia might explain increased cardiovascular risk.
      • Patel K.V.
      • Mohanty J.G.
      • Kanapuru B.
      • Hesdorffer C.
      • Ershler W.B.
      • Rifkind JM.
      Association of the red cell distribution width with red blood cell deformability.
      RDW is also associated with markers of inflammation, including high-sensitivity C-reactive protein (hs-CRP),
      • Lippi G.
      • Targher G.
      • Montagnana M.
      • Salvagno G.L.
      • Zoppini G.
      • Guidi GC.
      Relation between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients.
      but RDW was a stronger predictor of cardiovascular mortality than hs-CRP in an analysis from the National Health and Nutrition Examination Survey.
      • Veeranna V.
      • Zalawadiya S.K.
      • Panaich S.
      • Patel K.V.
      • Afonso L.
      Comparative analysis of red cell distribution width and high sensitivity C-reactive protein for coronary heart disease mortality prediction in multi-ethnic population: findings from the 1999-2004 NHANES.
      Prior studies in patients with acute coronary syndrome (ACS) have found an association of RDW with the risks of MACE and death.
      • Turcato G.
      • Serafini V.
      • Dilda A.
      • et al.
      Red blood cell distribution width independently predicts medium-term mortality and major adverse cardiac events after an acute coronary syndrome.
      ,
      • Abrahan L.L.
      • Ramos J.D.A.
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      • Tiongson M.D.A.
      • Punzalan FER.
      Red cell distribution width and mortality in patients with acute coronary syndrome: a meta-analysis on prognosis.
      ,
      • Zhao N.
      • Mi L.
      • Liu X.
      • et al.
      Combined value of red blood cell distribution width and global registry of acute coronary events risk score for predicting cardiovascular events in patients with acute coronary syndrome undergoing percutaneous coronary intervention.
      These studies involved 100 to 2500 patients, and most were conducted in a single center. An analysis of the multicenter EXAMINE trial in 5380 patients with diabetes and ACS showed that RDW was associated with MACE and death.
      • Ferreira J.P.
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      • Mehta C.
      • White W.B.
      • Zannad F.
      Red cell distribution width in patients with diabetes and myocardial infarction: An analysis from the EXAMINE trial.
      However, there is uncertain utility of RDW in estimating prognosis in a broad population of patients with ACS who receive high-intensity lipid-lowering therapy and other contemporary evidence-based treatments, and how the information provided by RDW may add to that offered by other characteristics including hs-CRP.
      Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors reduce the levels of atherogenic lipoproteins and, in large randomized, placebo-controlled trials, have been shown to reduce the risk of MACE when added to statin treatment.
      • Schwartz G.G.
      • Steg P.G.
      • Szarek M.
      • et al.
      Alirocumab and cardiovascular outcomes after acute coronary syndrome.
      ,
      • Murphy S.A.
      • Pedersen T.R.
      • Gaciong Z.A.
      • et al.
      Effect of the PCSK9 inhibitor evolocumab on total cardiovascular events in patients with cardiovascular disease: a prespecified analysis from the FOURIER trial.
      The goals of this post-hoc analysis from the ODYSSEY OUTCOMES trial were to determine whether RDW predicts risk of MACE or death in patients who are clinically stable after a recent ACS, whether RDW predicts the benefit of alirocumab in such patients, and whether alirocumab treatment affects RDW.

      Materials and methods

      The ODYSSEY OUTCOMES trial (clinicaltrials.gov identifier: NCT01663402) compared alirocumab with placebo in patients with a recent ACS and elevated atherogenic lipoproteins despite optimized statin treatment.
      • Schwartz G.G.
      • Steg P.G.
      • Szarek M.
      • et al.
      Alirocumab and cardiovascular outcomes after acute coronary syndrome.
      Randomization occurred 1−12 months after an ACS, a time when the acute phase response due to the event has waned.
      • Schwartz G.G.
      • Bessac L.
      • Berdan L.G.
      • et al.
      Effect of alirocumab, a monoclonal antibody to PCSK9, on long-term cardiovascular outcomes following acute coronary syndromes: rationale and design of the ODYSSEY outcomes trial.
      The primary MACE outcome was the composite of death due to coronary heart disease, nonfatal myocardial infarction, fatal and nonfatal ischemic stroke, or unstable angina requiring hospitalization.
      • Schwartz G.G.
      • Steg P.G.
      • Szarek M.
      • et al.
      Alirocumab and cardiovascular outcomes after acute coronary syndrome.
      All-cause death was one of several secondary endpoints.
      A standard complete blood count was obtained at randomization and at protocol-specified times thereafter. RDW was calculated as:
      RDW = (standard deviation of red blood cell volume/mean red blood cell volume) × 100.
      Blood lipids and hs-CRP were measured in samples obtained at baseline and at specified times thereafter.
      Demographic and baseline characteristics, for all subjects and by baseline RDW quartile, were summarized by mean and standard deviation (SD) for continuous variables and by proportion for categorical variables. Missing baseline hs-CRP values were imputed by mean value of baseline hs-CRP. Missing baseline RDW values were also imputed by mean value of baseline RDW. The imputation was performed so that all events of MACE or death could be included in the analyses. The associations of baseline RDW and risk of MACE or death in the placebo group were analyzed in proportional hazard models. For each outcome, 2 adjusted models were constructed. The first adjusted model included the variables significantly associated with the outcome, but specifically excluded hs-CRP. The second adjusted model contained all the variables of the first model and additionally was forced to include hs-CRP. Furthermore, the second adjusted model was recapitulated in 2 subsets of the trial cohort: those with baseline hs-CRP at or below the median (1.7 mg/L); and those with baseline hs-CRP above that value. Together, the adjusted models determined whether RDW predicted the risk of MACE or death independently of other clinical and laboratory variables, and whether the information contributed by RDW remained significant when hsCRP was considered. Pearson's coefficient was calculated for the correlation of baseline RDW and hs-CRP, as well as of baseline RDW and low-density lipoprotein cholesterol (LDL-C). The change in RDW from baseline to Months 12, 24, and 36 was analyzed using robust regression due to skewed distribution, including treatment and baseline RDW as covariates. The change in hs-CRP from baseline to Months 12, 24, and 36 was also analyzed, using robust regression due to the skewed distribution. To understand whether a differential treatment effect exists within the range of RDW or hs-CRP, baseline RDW and hs-CRP were divided into quartiles. The incidence rates of MACE and death were calculated for each quartile by treatment groups. Treatment hazard ratios (HRs) with 95% confidence intervals (CIs) for the effect of alirocumab versus placebo on MACE or death were calculated according to quartile of baseline RDW or baseline hs-CRP. Treatment HR were also calculated using proportional hazard models, incorporating stepwise selection of covariates from those listed in Table 1, and either explicitly excluding hs-CRP or forcing its inclusion. Treatment-by-baseline quartile interactions were also assessed. Adverse events were tabulated by treatments and baseline RDW quartiles. The analyses were performed using the intention-to-treat patient population and used SAS 9.4.
      Table 1Baseline characteristics, overall and by RDW quartile.
      CharacteristicAll patients

      (n = 18,924)
      RDW Q1 (11.3–13.3%)

      (n = 5,019)
      RDW Q2 (>13.3–13.8%)

      (n = 4,930)
      RDW Q3 (>13.8–14.4%)

      (n = 4,778)
      RDW Q4 (>14.4–27.5%)

      (n = 4,197)
      p value
      Age, years, mean ± SD58.6 ± 9.357.3 ± 9.258.2 ± 9.258.9 ± 9.160.2 ± 9.6<0.001
      Male, n (%)4,762 (25.2)1,182 (23.6)1,153 (23.4)1,181 (24.7)1,246 (29.7)<0.001
      Body mass index, kg/m2, mean ± SD28.5 ± 4.928.2 ± 4.528.5 ± 4.728.6 ± 4.928.7 ± 5.4<0.001
      Hemoglobin A1c, %, mean ± SD6.2 ± 1.26.2 ± 1.36.1 ± 1.26.2 ± 1.26.3 ± 1.2<0.001
      Current smoker, n (%)4,560 (24.1)1,213 (24.2)1,221 (24.8)1,153 (24.1)973 (23.2)0.368
      Hypertension, n (%)12,249 (64.7)3,103 (61.8)3,117 (63.2)3,070 (64.3)2,959 (70.5)<0.001
      Diabetes, n (%)5,444 (28.8)1,297 (25.8)1,266 (25.7)1,391 (29.1)1,490 (35.5)<0.001
      Family history of coronary artery disease, n (%)6,773 (35.8)1,868 (37.2)1,770 (35.9)1,721 (36.0)1,414 (33.7)0.005
      Myocardial infarction, n (%)3,633 (19.2)888 (17.7)938 (19.0)937 (19.6)870 (20.7)0.003
      Percutaneous coronary intervention, n (%)3,241 (17.1)822 (16.4)823 (16.7)820 (17.2)776 (18.5)0.043
      Coronary artery bypass graft, n (%)1,047 (5.5)249 (5.0)244 (4.9)274 (5.7)280 (6.7)<0.001
      Ischemic stroke, n (%)524 (2.8)107 (2.1)119 (2.4)149 (3.1)149 (3.6)<0.001
      Peripheral artery disease, n (%)759 (4.0)153 (3.0)143 (2.9)216 (4.5)247 (5.9)<0.001
      Heart failure, n (%)2,814 (14.9)650 (13.0)707 (14.3)687 (14.4)770 (18.3)<0.001
      LDL-C, mg/dL, mean ± SD92.4 ± 31.091.1 ± 28.892.4 ± 30.792.3 ± 31.493.9 ± 33.2<0.001
      hs-CRP, mg/L, median (Q1, Q3)1.7 (0.8, 4.0)1.3 (0.7, 3.0)1.5 (0.7, 3.4)1.7 (0.8, 4.0)2.3 (1.0, 5.3)<0.001
      RDW, %, median (Q1, Q3)13.8 (13.3, 14.4)13.0 (12.8, 13.2)13.6 (13.5, 13.7)14.1 (14.0, 14.3)14.7 (14.7, 15.5)<0.001
      eGFR, mL/min/1.73 m2, mean ± SD79.7 ± 19.381.5 ± 18.080.7 ± 19.079.2 ± 19.376.8 ± 20.6<0.001
      Hemoglobin, g/L, mean ± SD141.9 ± 13.9144.6 ± 12.3143.7 ± 12.6142.2 ± 13.3136.2 ±15.9<0.001
      eGFR, estimated glomerular filtration rate; hs-CRP, high-sensitivity C-reactive protein; LDL-C, low-density lipoprotein cholesterol; RDW, red blood cell distribution width; Q, quartile; SD, standard deviation.

      Results

      Baseline characteristics of all patients, both overall and by RDW quartile, are shown in Table 1. RDW had a skewed distribution driven by an excess of higher values so that the mean of 13.9% was greater than the median of 13.8% (quartile [Q] 1, Q3 = 13.3%, 14.4%). Increasing quartile of RDW was associated with greater prevalence of characteristics predictive of the risk of MACE or death, such as age, hypertension, diabetes, and history of atherosclerotic conditions, events, and procedures. An increasing quartile of RDW was associated with levels of hs-CRP or LDL-C; however, these variables were also predictive of MACE and death.
      Patients were followed for a median (Q1, Q3) of 2.8 (2.3, 3.4) years; 1,955 patients had MACE (alirocumab 903, placebo 1,052) and 726 died (alirocumab 334, placebo 392). Baseline RDW and hs-CRP were positively associated (Pearson correlation for log-transformed variables 0.1586, p <0.001), and RDW was weakly but significantly correlated with baseline LDL-C (Pearson correlation for log-transformed variables 0.0218, p = 0.0027).
      In unadjusted analyses depicted in Fig. 1, the risk of MACE or death in the placebo group increased nominally with baseline levels of RDW or hs-CRP. Table 2 shows that, in the placebo group, the unadjusted risk of MACE and death increased monotonically across quartiles of RDW and hs-CRP. For RDW, the risk of MACE was 1.8 times higher in quartile 4 than in quartile 1 (5.7 versus 3.1 per 100 patient-years) and the risk of death was 2.3 times higher in quartile 4 than in quartile 1 (2.3 versus 1.0 per 100 patient-years). Similarly, for hs-CRP, the risk of MACE was 1.7 times higher in quartile 4 than quartile 1 (5.4 versus 3.1 per 100 patient-years) and the risk of death was 2.6 times higher in quartile 4 than quartile 1 (2.2 versus 0.8 per 100 patient-years).
      Fig. 1
      Fig. 1Incidence rates of (A) MACE and (B) all-cause death per 100 person-years, according to baseline RDW value and hs-CRP quartile. ALI, alirocumab; hs-CRP, high-sensitivity C-reactive protein; MACE, major adverse cardiovascular event; PBO, placebo; Q, quartile; RDW, red blood cell distribution width.
      Table 2Increased risk of MACE or death with increasing baseline RDW level and hs-CRP level. HRs are unadjusted. CI, confidence interval; HR, hazard ratio; hs-CRP, high-sensitivity C-reactive protein; MACE, major adverse cardiovascular events; RDW, red blood cell distribution width; Q, quartile. *RDW: minimum = 11.3%; Q1 = 13.3%; median = 13.8%; Q3 = 14.4%; maximum = 27.50%. hs-CRP: minimum = 0.20 mg/L; Q1 = 0.82 mg/L; median = 1.70 mg/L; Q3 = 3.96 mg/L; maximum = 252.00 mg/L.
      EndpointQuartile*Rate (per 100 person-years)HR (95% CI) within each quartile
      AlirocumabPlacebo
      RDW
      MACEQ12.63.10.83 (0.68, 1.01)
      Q23.13.70.84 (0.70, 1.01)
      Q33.84.40.86 (0.73, 1.03)
      Q44.95.70.86 (0.73, 1.01)
      DeathQ10.71.00.68 (0.47, 0.99)
      Q20.91.10.87 (0.63, 1.21)
      Q31.41.60.90 (0.68, 1.18)
      Q42.12.30.89 (0.70, 1.14)
      hs-CRP
      MACEQ12.73.10.86 (0.70, 1.05)
      Q22.93.90.76 (0.63, 0.92)
      Q33.44.30.79 (0.66, 0.94)
      Q45.25.40.98 (0.84, 1.14)
      DeathQ10.80.80.94 (0.65, 1.37)
      Q21.01.30.79 (0.57, 1.08)
      Q31.11.50.74 (0.55, 1.00)
      Q42.12.20.94 (0.74, 1.18)
      Table 3 shows the results of unadjusted and adjusted models for MACE and death in the placebo group. For each outcome, the first model adjusted for variables associated with the outcome except that hs-CRP was specifically excluded. The second (fully adjusted) model forced the inclusion of hs-CRP, as well as other variables significantly associated with the outcome. In the unadjusted model and both adjusted models, baseline RDW was significantly (p <0.001) associated with the risk of MACE or death in the placebo group. The fully adjusted model demonstrated HR (95% CI) of 1.08 (1.01–1.15) and 1.14 (1.04–1.26) per 1% increase of RDW for MACE and death, respectively. An analysis stratified by baseline hs-CRP ≤1.7 mg/L (median) or >1.7 mg/L was conducted using the fully adjusted model. In the subgroup with baseline hs-CRP above median, there was a significantly greater risk of MACE and death per 1% increase in RDW, with HR (95% CI) of 1.09 (1.00, 1.18) and 1.21 (1.07, 1.36), respectively. In the subgroup of patients with baseline hs-CRP ≤ median, a 1% increase in RDW was associated with a directionally similar but numerically smaller HR for MACE and death of 1.06 (0.96, 1.17) and 1.02 (0.85, 1.22), respectively.
      Table 3Risk of MACE and death per 1% increase of RDW in the placebo group.
      ModelHR (95% CI) for MACEHR (95% CI) for death
      Unadjusted1.20 (1.15, 1.27)1.33 (1.25, 1.42)
      Model 1: Adjusted for variables predictive of outcome, specifically excluding hs-CRP1.11 (1.05, 1.17)1.17 (1.07, 1.27)
      Model 2: Adjusted for variables predictive of outcome, and hs-CRP1.08 (1.01, 1.15)1.14 (1.04, 1.26)
      Model 2 in subgroup of patients with baseline hs-CRP <=1.71.06 (0.96, 1.17)1.02 (0.85, 1.22)
      Model 2 in subgroup of patients with baseline hs-CRP >1.71.09 (1.00, 1.18)1.21 (1.07, 1.36)
      Adjustment variables were those significantly associated with the risk of MACE or the risk of death. In Model 1 these variables were age, sex, hypertension, diabetes, smoking status, prior myocardial infarction, stroke, coronary bypass grafting, peripheral artery disease, baseline LDL-C, eGFR, hemoglobin A1c, hemoglobin, and body mass index. In Model 2, the adjustment variables were those of Model 1 and hs-CRP.
      CI, confidence interval; eGFR, estimated glomerular filtration rate; HR, hazard ratio; hs-CRP, high-sensitivity C-reactive protein; LDL-C, low-density lipoprotein cholesterol; MACE, major adverse cardiovascular event; RDW, red blood cell distribution width.
      As shown in Fig. 1 and Table 2, alirocumab reduced the risk of MACE and death consistently versus placebo in each baseline RDW and hs-CRP quartile. There were no interactions of RDW quartile or hs-CRP quartile and treatment on MACE (p = 0.99 and p = 0.16) or death (p = 0.64 and p = 0.59). The absolute reduction in the risk of MACE with alirocumab versus placebo increased across quartiles of RDW from 0.5 to 0.8 per 100 patient-years, but similar trends were not apparent for reduction in death according to RDW quartile, or for absolute reduction in either MACE or death according to hs-CRP quartile.
      A stepwise Cox regression model to determine the treatment effect of alirocumab according to baseline RDW selected the following baseline variables as significantly associated with the risk of MACE in addition to RDW: age, sex, current smoking, hypertension, diabetes, family history of coronary artery disease, prior myocardial infarction, prior percutaneous coronary intervention, prior coronary artery bypass graft, ischemic stroke, peripheral artery disease, heart failure, LDL-C, hemoglobin, hemoglobin A1c, and estimated glomerular filtration rate. A second model for MACE forced the inclusion of hs-CRP in addition to the variables included in the first model. Results of both adjusted models were consistent with those of the unadjusted model (Table 2) in showing significant association of baseline RDW with incidence of MACE or death in the placebo group but not with the treatment effect of alirocumab.
      RDW decreased from baseline in both treatment groups but not significantly. Treatment with alirocumab or placebo did not affect RDW level over time (Table 4).
      Table 4Treatment effects of alirocumab and placebo on RDW and hs-CRP.
      TimepointAlirocumab

      (n = 9,451)
      Placebo

      (n = 9,443)
      Difference, LSM (SE) [95% CI]p value
      Baseline RDW, %, median (Q1, Q3)n = 9,393

      13.80 (13.30, 14.40)
      n = 9,375

      13.80 (13.30, 14.40)
      RDW change from baseline, LSM (SE)
      Month 12n = 7,561

      −0.18 (0.01)
      n = 7,861

      –0.16 (0.01)
      –0.02 (0.01)

      [–0.04, 0.00]
      0.055
      Month 24n = 6,458

      –0.25 (0.01)
      n = 6,813

      –0.23 (0.01)
      –0.02 (0.01)

      [–0.04, 0.00]
      0.13
      Month 36n = 3,133

      –0.27 (0.01)
      n = 3,323

      –0.29 (0.01)
      0.02 (0.02)

      [–0.01, 0.05]
      0.25
      Baseline hs-CRP, mg/dL, median (Q1, Q3)n = 8,924

      1.61 (0.78, 3.79)
      n = 8,933

      1.67 (0.79, 3.94)
      hs-CRP change from baseline, LSM (SE)
      Month 4n = 8,352

      −1.40 (0.01)
      n = 8,334

      –1.43 (0.01)
      0.04 (0.02)

      [0.00, 0.07]
      0.032
      Month 12n = 7,579

      −1.46 (0.01)
      n = 7,932

      –1.52 (0.01)
      0.06 (0.02)

      [0.02, 0.10]
      0.002
      Month 24n = 138

      –1.03 (0.01)
      n = 159

      –0.92 (0.10)
      –0.11 (0.15)

      [–0.41, 0.18]
      0.463
      Month 36n = 535

      –1.46 (0.06)
      n = 548

      –1.54 (0.06)
      0.09 (0.083)

      [–0.08, 0.25]
      0.303
      CI, confidence interval; hs-CRP, high-sensitivity C-reactive protein; LSM, least squares mean; RDW, red blood cell distribution width; SD, standard deviation; SE, standard error.

      Discussion

      This post hoc analysis from the ODYSSEY OUTCOMES trial demonstrates that RDW is positively associated with risk of MACE and death among patients who are clinically stable after a recent ACS. These associations remained significant after adjustment for other variables predictive of MACE or death, including demographic and medical history characteristics, LDL-C, and particularly hs-CRP. Alirocumab had no effect on RDW levels and reduced the risk of cardiovascular events when compared with placebo, irrespective of RDW level.
      The present data add to the findings in previous analyses in several notable ways. First, RDW provided robust prognostics in a large, multinational population of patients with ACS, most of whom (89%) received high-intensity statin therapy and the remainder who received maximum tolerated statin therapy. The trial population was also characterized by high utilization of other evidence-based therapies, including coronary revascularization and treatment with dual antiplatelet therapy, inhibitors of the renin-angiotensin system, and beta blockers. Second, in contrast to some prior observational cohort analyses, the outcomes reported here were blindly adjudicated. Third, the patients in the ODYSSEY OUTCOMES trial were randomized a minimum of 1 month after the qualifying ACS, thus at a time when acute phase effects on inflammatory markers such as hs-CRP should have waned.
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      Finally, both RDW and hs-CRP have been proposed as inflammatory markers that provide useful prognostic information after ACS and in chronic coronary heart disease. Our findings in fully adjusted models indicate that RDW contributes information on risk of MACE and death beyond that provided by hs-CRP, particularly among patients with elevated hs-CRP levels.
      Historically, RDW was used as a means of anemia classification. In 2007, investigators from the North American Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity trial found an association between RDW level and cardiovascular death or hospitalization from heart failure in patients without anemia.
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      • Melzer D.
      Red cell distribution width and common disease onsets in 240,477 healthy volunteers followed for up to 9 years.
      • Patel K.V.
      • Ferrucci L.
      • Ershler W.B.
      • Longo D.L.
      • Guralnik JM.
      Red blood cell distribution width and the risk of death in middle-aged and older adults.
      In each case, the results demonstrated that an elevated RDW level was associated with an increased risk of MACE or death. The ODYSSEY OUTCOMES trial, consistent with existing literature, confirmed the association of RDW levels with CVD. Additionally, alirocumab significantly reduced CVD events at all RDW levels compared with placebo.
      Despite robust associations of RDW with risk of MACE or death in fully adjusted analyses, the current data cannot determine whether RDW is a marker of other conditions that affect cardiovascular disease risk or if it reflects an abnormality of red blood cells that is directly related to the pathogenesis of MACE or death following ACS. In the former category, elevated RDW has been associated with chronic inflammatory conditions, and in the present analysis was indeed correlated with levels of hs-CRP. Other studies have correlated RDW with levels of interleukin-6 and fibrinogen.
      • Lippi G.
      • Targher G.
      • Montagnana M.
      • Salvagno G.L.
      • Zoppini G.
      • Guidi GC.
      Relation between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients.
      ,
      • Forhecz Z.
      • Gombos T.
      • Borgulya G.
      • Pozsonyi Z.
      • Prohaszka Z.
      • Janoskuti L.
      Red cell distribution width in heart failure: prediction of clinical events and relationship with markers of ineffective erythropoiesis, inflammation, renal function, and nutritional state.
      ,
      • Vaya A.
      • Sarnago A.
      • Fuster O.
      • Alis R.
      • Romagnoli M.
      Influence of inflammatory and lipidic parameters on red blood cell distribution width in a healthy population.
      ,
      • Sharma R.
      • Agrawal VV.
      The relationship between red blood cell distribution width (RDW CV) and C reactive protein (CRP) with the clinical outcomes in non-ST elevation myocardial infarction and unstable angina pectoris: a 6 months follow up study.
      As the life span of a red blood cell is roughly 120 days, elevated RDW levels may reflect inflammation over a period of months, unlike acute phase reactants such as hs-CRP or fibrinogen that reflect recent or ongoing inflammation. In the latter category, abnormal red blood cell morphology as marked by elevated RDW may be accompanied by reduced red cell deformability, and thereby microvascular dysfunction and compromised tissue perfusion.
      • Patel K.V.
      • Mohanty J.G.
      • Kanapuru B.
      • Hesdorffer C.
      • Ershler W.B.
      • Rifkind JM.
      Association of the red cell distribution width with red blood cell deformability.
      ,
      • Simchon S.
      • Jan K.M.
      • Chien S.
      Influence of reduced red cell deformability on regional blood flow.
      ,
      • Passos A.
      • Sherwood J.M.
      • Kaliviotis E.
      • Agrawal R.
      • Pavesio C.
      • Balabani S.
      The effect of deformability on the microscale flow behavior of red blood cell suspensions.
      In healthy adults the omega-3 index, also known to affect membrane fluidity and deformability, was found to be inversely associated with RDW.
      • McBurney M.I.
      • Tintle N.L.
      • Harris WS.
      Omega-3 index is directly associated with a healthy red blood cell distribution width.
      Furthermore, RDW may be inversely associated with fractional flow reserve independent of the severity of a coronary stenosis, also implying an adverse effect on microvascular function.
      • Acikgoz S.K.
      • Acar B.
      • Aydin S.
      • et al.
      Red cell distribution width can predict the significance of angiographically intermediate coronary lesions.
      Medications that may lower both RDW and hs-CRP levels include eicosapentaenoic acid
      • Tajima E.
      • Abe S.
      • Watanabe R.
      • et al.
      Effects of purified eicosapentaenoic acid on red blood cell distribution width and vascular endothelial function in patients with coronary artery disease.
      and colchicine.
      • Seckin H.Y.
      • Butun I.
      • Bas Y.
      • Takci Z.
      • Kalkan G.
      Effects of colchicine treatment on mean platelet volume and the inflammatory markers in recurrent aphthous stomatitis.
      Both of these agents also reduce cardiovascular risk,
      • Tardif J.C.
      • Kouz S.
      • Waters D.D.
      • et al.
      Efficacy and safety of low-dose colchicine after myocardial infarction.
      ,
      • Bhatt D.L.
      • Steg P.G.
      • Miller M.
      • et al.
      Cardiovascular risk reduction with icosapent ethyl for hypertriglyceridemia.
      but the association of levels and changes in RDW and treatment benefit have not been reported.
      The present analysis of the ODYSSEY OUTCOMES trial shows that both RDW and hs-CRP levels are associated with an increased risk of MACE and death after a recent ACS. Although hs-CRP and RDW may both reflect inflammatory stimuli, they may predict risk of cardiovascular disease
      • Veeranna V.
      • Zalawadiya S.K.
      • Panaich S.
      • Patel K.V.
      • Afonso L.
      Comparative analysis of red cell distribution width and high sensitivity C-reactive protein for coronary heart disease mortality prediction in multi-ethnic population: findings from the 1999-2004 NHANES.
      ,
      • Loprinzi PD.
      Comparative evaluation of red blood cell distribution width and high sensitivity C-reactive protein in predicting all-cause mortality and coronary heart disease mortality.
      and death
      • Veeranna V.
      • Zalawadiya S.K.
      • Panaich S.
      • Patel K.V.
      • Afonso L.
      Comparative analysis of red cell distribution width and high sensitivity C-reactive protein for coronary heart disease mortality prediction in multi-ethnic population: findings from the 1999-2004 NHANES.
      ,
      • Loprinzi PD.
      Comparative evaluation of red blood cell distribution width and high sensitivity C-reactive protein in predicting all-cause mortality and coronary heart disease mortality.
      independently. When we controlled for baseline variables associated with MACE, including hs-CRP and LDL-C, RDW levels remained strongly predictive of cardiovascular events. Because RDW is provided with a standard complete blood count, this incremental information entails no added cost to medical care.
      Although vascular inflammation influences atherosclerosis, and anti-inflammatory therapies have reduced MACE (canakinumab [CANTOS clinical trial],
      • Ridker P.M.
      • Everett B.M.
      • Thuren T.
      • et al.
      Antiinflammatory therapy with canakinumab for atherosclerotic disease.
      colchicine),
      • Tardif J.C.
      • Kouz S.
      • Waters D.D.
      • et al.
      Efficacy and safety of low-dose colchicine after myocardial infarction.
      alirocumab lowered levels of atherogenic lipoproteins and significantly reduced cardiovascular morbidity and mortality without a significant effect on markers of inflammation such as hs-CRP and RDW. These results support the notion that atherogenic lipoproteins and inflammatory targets are independent targets of therapy to reduce the risk of MACE.
      • Ference B.A.
      • Ginsberg H.N.
      • Graham I.
      • et al.
      Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. Evidence from genetic, epidemiologic, and clinical studies. A consensus statement from the European Atherosclerosis Society Consensus Panel.
      ,
      • Jarcho J.A.
      • Keaney JF.
      Proof that lower is better — LDL cholesterol and IMPROVE-IT.

      Limitations

      In this analysis, adjustments were made only for baseline prognostic factors, and we did not consider any time-varying covariates affected by the course of treatment. This approach was used for the preservation of randomization and to prevent introduction of bias due to differential outcomes. We cannot exclude the possibility of residual confounding by factors not considered in this analysis. The mechanisms responsible for the association of RDW with cardiovascular risk remain uncertain and warrant further investigation.

      Conclusions

      This analysis of ODYSSEY OUTCOMES data shows that both RDW and hs-CRP are biomarkers that independently associate with the risk of cardiovascular events and death following an ACS. RDW, a routine element of laboratory data obtained in almost every patient, may therefore add to risk stratification and treatment decisions in patients with ACS. An RDW value of 14% or higher (approximately the highest quartile in this analysis) identifies patients at very high risk for MACE and death following ACS, despite optimized statin treatment and other evidence-based therapies.

      Conflicts of Interest

      P.M.M. reports receipt of research grants to his institution for the participation in the ODYSSEY OUTCOMES trial, as well as financial fees for serving as a medical monitor for the trial and associated support for travel related to trial meetings from Sanofi; consulting and speaking fees from Regeneron Pharmaceuticals, Inc. and Amgen; consultant fees from Esperion, Kaneka, and Stage II innovations; speaker fees from Amarin; advisor fees from Novartis for serving on their advisory committee; research grants to his institution from Ionis, FH Foundation, GB Life Sciences, Aegerion, Amgen, Kowa, Novartis, and Regeneron Pharmaceuticals, Inc.. P.G.S. reports grants and nonfinancial support (co-chair of the ODYSSEY OUTCOMES trial; as such, he received no personal fees, but his institution has received funding for the time he has devoted to trial coordination, and he has received support for travel related to trial meetings) from Sanofi; research grants and personal fees from Bayer (Steering Committee MARINER, grant for epidemiological study), Merck (speaker fees, grant for epidemiological studies), Sanofi (co-chair of the ODYSSEY OUTCOMES trial; co-chair of the SCORED trial; consulting, speaking), Servier (Chair of the CLARIFY registry; grant for epidemiological research), and Amarin (executive steering committee for the REDUCE-IT trial [Disease Reduction of Cardiovascular Events With Icosapent Ethyl–Intervention Trial]; consulting); and personal fees from Amgen, Bristol-Myers Squibb, Boehringer Ingelheim, Pfizer, Idorsia, Myokardia, Novo Nordisk, Novartis, Regeneron Pharmaceuticals, Inc. and AstraZeneca. P.G.S. also has a European application number/patent number, issued on October 26, 2016 (no. 15712241.7), for a method for reducing cardiovascular risk, all royalties assigned to Sanofi. A.M.Z. reports receiving fees for serving on a steering committee for the ODYSSEY OUTCOMES trial from Sanofi, and advisory board and speaker fees from Sanofi, Amgen, Boehringer Ingelheim, Bayer, Novartis, Pfizer, AstraZeneca, and Vifor. H.D.W. reports grant support paid to his institution for serving on a Steering Committee for the ODYSSEY OUTCOMES trial (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) from Sanofi-Aventis and Regeneron Pharmaceuticals, Inc. for the ACCELERATE study (A Study of Evacetrapib in High-Risk Vascular Disease) from Eli Lilly and Company, for the STRENGTH trial (Outcomes Study to Assess Statin Residual Risk Reduction With EpaNova in High CV Risk Patients With Hypertriglyceridemia) from Omthera Pharmaceuticals, for the CAMELLIA-TIMI study (A Study to Evaluate the Effect of Long-term Treatment With BELVIQ [Lorcaserin HC] on the Incidence of Major Adverse Cardiovascular Events and Conversion to Type 2 Diabetes Mellitus in Obese and Overweight Subjects With Cardiovascular Disease or Multiple Cardiovascular Risk Factors) from Eisai Inc, for the HEART-FID study (Randomized Placebo-Controlled Trial of FCM as Treatment for Heart Failure With Iron Deficiency) from American Regent, and for the ISCHEMIA Trial (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches) and the MINT Trial (Myocardial Ischemia and Transfusion) from the National Institutes of Health USA. He also received grants to his institution and personal fees as Steering Committee member for the dal-GenE study (Effect of Dalcetrapib vs. Placebo on CV Risk in a Genetically Defined Population With a Recent ACS) from DalCor Pharma UK Inc, for the AEGIS-II study (The Safety and Tolerability of CSL112, a Reconstituted, Infusible, Plasma-Derived Human ApoA-I, After Acute Myocardial Infarction: The ApoA-I Event reducinG in Ischemic Syndromes I) from CSL Behring, for the SCORED trial (Effect of Sotagliflozin on Cardiovascular and Renal Events in Patients With Type 2 Diabetes and Moderate Renal Impairment Who Are at Cardiovascular Risk) and the SOLOIST-WHF trial (Effect of Sotagliflozin on Cardiovascular Events in Patients With Type2 Diabetes Post Worsening Heart Failure) from Sanofi-Aventis Australia Pty Ltd, and for the CLEAR Outcomes Study (Evaluation of Major Cardiovascular Events in Patients With, or at High Risk for, Cardiovascular Disease Who Are Statin Intolerant Treated With Bempedoic Acid [ETC-1002] or Placebo) from Esperion Therapeutics Inc. H.D.W. was on the Advisory Boards for CSL Behring and Genentech, Inc. (an affiliate of F. Hoffmann-La Roche Ltd, “Roche”; Lytics Post-PCI Advisory Board at European Society of Cardiology. M.L. is an employee of Sanofi and may hold shares and/or stock options in the company. J.M. and G.M. are employees of Regeneron Pharmaceuticals, Inc. J.W.J. reports research grants from the Netherlands Heart Foundation, the Interuniversity Cardiology Institute of the Netherlands, and the European Commission Seventh Framework Programme; and research support from Amgen, Astellas, AstraZeneca, Daiichi- Sankyo, Lilly, Merck-Schering-Plough, Pfizer, Roche, and Sanofi. R.A.H. reports research grants (all DSMB related) from AstraZeneca, Janssen, and Bristol-Myers Squibb, serving on advisory boards for Gilead (uncompensated) and WebMD; and serving on the boards of directors (unpaid) for the American Heart Association and Stanford HealthCare. S.G.G. reports research grants from Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, CSL Behring, Daiichi-Sankyo/American Regent, Eli Lilly, Novartis, Pfizer, Regeneron Pharmaceuticals, Inc., and Sanofi; honoraria from Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, CSL Behring, Daiichi-Sankyo/American Regent, Eli Lilly, Esperion, Ferring Pharmaceuticals, GlaxoSmithKline, HLS Therapeutics, JAMP Pharma, Janssen/Johnson & Johnson, Merck, Novartis, Novo Nordisk A/C, Pendopharm, Pfizer, Regeneron Pharmaceuticals, Inc., Sanofi, Servier, Valeo Pharma, Canadian Heart Research Centre and MD Primer, Canadian VIGOUR Centre, Cleveland Clinic Coordinating Centre for Clinical Research, Duke Clinical Research Institute, New York University Clinical Coordinating Centre, and PERFUSE Research Institute; and serving as a consultant or on advisory boards (or both) for Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, CSL Behring, Ferring Pharmaceuticals, HLS Therapeutics, JAMP Pharma, Janssen/Johnson & Johnson, Merck, Novartis, Pendopharm, Pfizer, Regeneron Pharmaceuticals, Inc., Sanofi, Servier, and Valeo Pharma. R.D. reports research grants from Sanofi, DalCor Pharmaceuticals, Population Health Research Institute, Duke Clinical Research Institute, the TIMI group, Amgen, Cirius, Montreal Health Innovations Coordinating Center, and Lepetit; and personal fees, as a member of the Executive Steering Committee, from Amgen and Cirius. V.A.B. reports grant support from Sanofi, AstraZeneca, DalCor, Esperion, Bayer, Novartis, and Amgen, all paid direct to her institution; and personal fees from Sanofi and Pfizer. D.L.B. discloses grants from Sanofi and Regeneron during the conduct of the study, as well as, outside of the submitted work, grants from 89Bio, Acesion Pharma, Afimmune, Aker Biomarine, Amarin, Amgen, AstraZeneca, Beren, Boehringer Ingelheim, Boston Scientific, Bristol-Myers Squibb, Cardax, CellProthera, Cereno Scientific, Chiesi, Contego Medical, Eisai, Ethicon, Faraday Pharmaceuticals, Ferring Pharmaceuticals, Forest Laboratories/AstraZeneca, Fractyl, Garmin, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Javelin, Lexicon, Lilly, The Medicines Company, Medtronic, Moderna, MyoKardia/BMS, NirvaMed, Novartis, Novo Nordisk, Owkin, Pfizer, PhaseBio, PLx Pharma, Recardio, Regeneron, Reid Hoffman Foundation, Roche, Sanofi Aventis, Stasys, and Synaptic; personal fees from American College of Cardiology, Arnold & Porter law firm, Assistance Publique-Hôpitaux de Paris, Bayer, Belvoir Publications, Boehringer Ingelheim, Canadian Medical and Surgical Knowledge Translation Research Group, Cleveland Clinic, Cowen and Company, CSL Behring, DRS.LINQ, Duke Clinical Research Institute, Elsevier, Harvard Clinical Research Institute (now Baim Institute for Clinical Research), HMP Global, Journal of the American College of Cardiology, K2P, Level Ex, Mayo Clinic, Medtelligence/ReachMD, MJH Life Sciences, Mount Sinai School of Medicine, Piper Sandler, Population Health Research Institute, Slack Publications, Society of Cardiovascular Patient Care, TobeSoft, and WebMD; other financial support from American College of Cardiology, Biotronik, Boehringer Ingelheim, Boston Scientific, Boston VA Research Institute, Cardax, CellProthera, Cereno Scientific, Clinical Cardiology, CSI, FlowCo, Janssen, Medscape Cardiology, Merck, MyoKardia/BMS, NirvaMed, Novartis, Novo Nordisk, PhaseBio, Philips, PLx Pharma, Regado Biosciences, St. Jude Medical (now Abbott), Svelte, Takeda, and VA; and non-financial support from American College of Cardiology, American Heart Association, and Society of Cardiovascular Patient Care. M.S. reports serving as a consultant or on advisory boards (or both) for CiVi, Resverlogix, Baxter, Esperion, Lexicon, Sanofi, and Regeneron Pharmaceuticals, Inc. J.G. and L.K.G. report no conflicts. G.G.S. reports research support to the University of Colorado from AstraZeneca, Resverlogix, Roche, Sanofi, and The Medicines Company; he is coinventor of pending US patent 62/806,313 (“Methods for Reducing Cardiovascular Risk”) assigned in full to the University of Colorado.

      Funding

      Supported by Regeneron Pharmaceuticals, Inc.

      Role of the funding source

      The trial was funded by Sanofi and Regeneron Pharmaceuticals, Inc . The protocol and statistical analysis plan were conceived by the academic Executive Steering Committee, developed in conjunction with the sponsors, and approved by responsible regulatory authorities and ethics committees. Duke Clinical Research Institute led blinded end point adjudication. An independent committee monitored trial safety and efficacy data. The manuscript was drafted by the first author with input from all authors. The Executive Steering Committee decided to publish the paper and takes responsibility for the completeness and accuracy of the data.

      Contributors

      All authors gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy. Patrick M. Moriarty and Gregory G. Schwartz drafted the manuscript; contributed to conception or design; and contributed to acquisition, analysis, or interpretation. Jennifer McGinniss analyzed the data and wrote the methods section. All other authors contributed to conception or design; contributed to acquisition, analysis, or interpretation; and critically revised the manuscript.

      Acknowledgments

      The authors thank the patients, study coordinators, and investigators who participated in this trial. Richa Attre, PhD, MPH, Regeneron Pharmaceuticals, Inc. provided editorial review and support.

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