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1 Leukocyte Count as an Independent Predictor of Ischemic Events Armin J. Grau, MD; Alexander W. Boddy, MS; Deborah A. Dukovic, MS; Florian Buggle, MD; Christoph Lichy, MD; Tobias Brandt, MD; Werner Hacke, MD; for the CAPRIE Investigators Background and Purpose Inflammatory markers predict first-time ischemic events. We investigated whether leukocyte and differential counts predict recurrent events and ischemic events in high-risk populations, and whether such events are preceded by acutely exacerbated inflammation. Methods We studied patients with ischemic stroke, myocardial infarction, or peripheral arterial disease who participated in the trial of Clopidogrel versus Aspirin in Patients at Risk of Ischemic Events (CAPRIE), a study that compared the occurrence of ischemic stroke, myocardial infarction, or vascular death under randomized treatment with aspirin or clopidogrel. Leukocyte counts were frequently assessed during followup. Results Compared with the quartile with lowest leukocyte counts at baseline ( /L), patients in the top quartile ( /L) had higher risks for ischemic stroke (relative risk 1.30; P 0.007), myocardial infarction (relative risk 1.56, P 0.001), and vascular death (relative risk 1.51; P 0.001) after adjustment for other risk factors. Neutrophil counts contributed most to increased risk. Assessments of regression dilution effects based on replicate measurements show that these risk associations may underestimate the real associations by 30 to 50%. Treatment with aspirin or clopidogrel did not influence predictive effects by leukocytes. In the week before a recurrent event, but not at earlier time points, the leukocyte count was significantly increased over baseline levels (n 211; mean difference /L; P 0.005). Conclusions Leukocyte counts and mainly neutrophil counts are independently associated with ischemic events in these high-risk populations. An increase of leukocyte counts over baseline levels heralds a period of increased risk lasting about one week. (Stroke. 2004;35: ) Key Words: leukocytes inflammation risk factors myocardial infarction stroke Multiple lines of evidence indicate that inflammation contributes to both initiation and progression of atherosclerosis, and to acute rupture of atherosclerotic plaques with superimposed thrombus formation. 1 Several markers of inflammation have been identified as predictors of ischemic vascular diseases. The leukocyte count predicted the risk of first-time myocardial infarction and ischemic stroke, 2 9 independent from smoking and other vascular risk factors, in a recent metaanalysis. 10 Similarly, levels of C-reactive protein (CRP) were correlated with the risk of ischemic diseases Most previous studies on inflammation and vascular risk investigated healthy subjects. Possibly, the prognostic value of inflammatory parameters is apparent only when the level of conventional risk factors is low but not in cohorts with high-risk of ischemic diseases. 13 However, only a few data exist to indicate whether inflammatory parameters also reflect the risk of ischemic events in high-risk populations and the risk of recurrent ischemic events. 14,15 To address the issue of leukocyte counts as a risk factor in high-risk populations, we used hematological assessments from the trial of Clopidogrel versus Aspirin in Patients at Risk of Ischemic Events (CAPRIE). CAPRIE assessed the relative efficacy of clopidogrel and aspirin in reducing a composite outcome cluster of ischemic stroke, myocardial infarction, or vascular death in patients with previous ischemic diseases. Blood cell counts were frequently assessed during the study. 16 We tested the hypothesis that leukocyte and differential counts predict ischemic events in a high-risk population, and that acute increases in leukocyte counts precede the occurrence of ischemic events in the CAPRIE study population. Furthermore, we investigated whether the predictive role of leukocyte counts is differentially modified by treatment with aspirin or clopidogrel. Methods Study Population The design of the CAPRIE trial was published recently. 16 Briefly, patients with ischemic stroke of presumed atherothrombotic or lacunar origin, patients with myocardial infarction, and patients with Received May 22, 2003; final revision received December 1, 2003; accepted January 9, From Department of Neurology (A.J.G., F.B., C.L., T.B., W.H.), University of Heidelberg, Germany; Sanofi-Synthelabo, Inc (A.W.B., D.A.D.), Malvern, Pennsylvania. Correspondence to Armin J. Grau, MD, Neurologische Klinik, Klinikum der Stadt Ludwigshafen a.rh., Bremserstr. 70, D Ludwigshafen, Germany. graua@klilu.de 2004 American Heart Association, Inc. Stroke is available at DOI: /01.STR

2 1148 Stroke May 2004 peripheral arterial disease were randomized in a double-blind way to receive either clopidogrel (75 mg once daily) or aspirin (325 mg once daily), and were followed for one to three years. Exclusion criteria for patients included age 21 years, uncontrolled hypertension, severe renal or hepatic insufficiency, and present or previous hemostatic and hematologic disorders. The primary endpoint of the study was the occurrence of ischemic stroke, myocardial infarction, or vascular death. Blood counts were assessed weekly in the first 3 months among the initial 500 patients and biweekly among the second 500 patients of the study. After a blinded review of safety data, follow-up visits with hematological assessment took place monthly for the first 3 months and every 4 months thereafter. Three central laboratories received blood samples by overnight courier and performed hematological assessments using automated cell counting systems and manual recounts, if cell counts were pathological or if otherwise required. We excluded all patients from the analyses with any leukocyte count /L or /L or any neutrophil count /L. Low neutrophil counts were not more common under clopidogrel (0.10%) than aspirin (0.17%). We used leukocyte and differential counts from baseline evaluation, unless those values were gained within 28 days after myocardial infarction or ischemic stroke, in order to exclude acute phase effects. In such cases, first values after 4 weeks were used. CAPRIE was accepted by the respective Ethics committees, and patients gave informed consent. Statistical Analysis Subjects were divided into 4 equally sized groups (quartiles) according to their leukocyte or differential counts. Subjects with all 3 randomization events were analyzed together. Annual rates of recurrent events and risk ratios relative to the quartile with the lowest values were calculated in univariate analysis. To adjust for other risk factors, a multivariate analysis including age, nonwhite or white race, gender, body mass index, hypertension, congestive heart failure, cigarette smoking, diabetes mellitus, coronary heart disease (stable or unstable angina pectoris), hematocrit, hyperlipidemia, random treatment assignment, recent or previous myocardial infarction, cerebrovascular event, and peripheral arterial disease was performed. A likelihood ratio test was applied to compare prediction models with and without leukocyte counts. To analyze the possible differential effect of study medication on the predictive role of leukocyte counts, an interaction term (leukocyte count medication) was introduced into the multivariate model. Analysis of variance was used to estimate the influence of various factors on leukocyte counts. Within the framework of the multivariate model, tests for trends were performed to analyze the relationship between leukocyte counts and the risk of recurrent events in subgroups of patients. Parametric and nonparametric methods 17,18 were used to estimate the regression dilution effect resulting from measurement and sampling errors and intraindividual fluctuations of leukocyte counts. Estimates were calculated based on pairs of replicate measurements within the same patient separated by distinct intervals of time (4, 8, 12, and 24 months). Nonparametric estimates are calculated as a ratio of ranges, and parametric estimates are based on the correlation coefficient between measurement pairs. In both cases, a regression dilution ratio estimate (R) is obtained; it is generally less than 1 and provides an estimate of the importance of regression dilution during the exposure period. The regression coefficient, derived from baseline measurements, can be corrected by the factor 1/R to adjust for regression dilution effects. Means and standard deviations for the difference between counts at baseline and last measurement prior to a recurrent ischemic event (or last measurement for patients with no recurrent events) were calculated according to the number of days the measurement was taken prior to the recurrent event. To assess the significance of the differences, t tests were performed. P values are two-tailed and CI were calculated at the 95% level. Results Among the participants of the CAPRIE trial, patients were included in this analysis (mean age years, male sex: 72%). Qualifying conditions were ischemic stroke (n 6224), myocardial infarction (n 5974), and peripheral arterial disease (n 6360). During a mean follow-up of 1.9 years, 1840 patients (9.9%) suffered from an outcome event including fatal or nonfatal ischemic stroke (n 887), fatal or nonfatal myocardial infarction (n 577), and vascular death (n 655). In univariate analysis, the risk of recurrent ischemic events continuously rose with each increasing quartile of leukocyte and granulocyte counts (Table 1). Current smoking, congestive heart failure, diabetes mellitus, hypertension, caucasian race (P 0.001, respectively), and high body mass index ( 30 kg/m 2 ; P 0.040) were independently associated with higher leukocyte count, whereas age 65 years (P 0.001) was correlated with lower leukocyte counts. In the multivariate analysis, adjusting for vascular risk factors and diseases, hematocrit, and study treatment, the risk of recurrent ischemic events was significantly higher in both upper quartiles of leukocyte counts than in the bottom quartile (Table 1; relative risk highest versus lowest quartile: 1.42; 95% CI, range 1.25 to 1.63). Such relative risks were 1.30 (95% CI, range 1.07 to 1.57) for stroke, 1.56 (95% CI, range 1.22 to 2.00) for myocardial infarction, and 1.51 (95% CI, range 1.20 to 1.89) for vascular death. The neutrophil count was the differential count that contributed most strongly to increased risk, and was a predictive index, particularly for vascular death (relative risk 1.86, Table 2). The monocyte count showed a similar, although weaker, trend. The lymphocyte count was not a significant predictor in multivariate analysis, except for myocardial infarction, a result that could well represent a type 1 error. Other independent risk factors were age, nonwhite race, myocardial infarction or stroke before the qualifying event, congestive heart failure, diabetes mellitus, peripheral arterial disease or coronary heart disease, and smoking (Table 3). The role of neutrophils and monocytes was not modified by adding medication with statins and antiinflammatory drugs to the multivariate model (data not shown). The risk increase was similar under treatment with aspirin and clopidogrel, ie, there was no significant interaction between the predictive role of leukocyte counts and randomized medication in the multivariate model (P 0.50). The fit of the multivariate model without including leukocyte counts ( , 15 df) was significantly improved after addition of leukocyte counts ( , 16 df; difference in likelihood between models, P 0.001). The risk in the highest quartile of leukocyte counts was significantly higher than in the lowest quartile in all subgroups analyzed except in women, patients that never smoked, and diabetics (Table 4). Regression dilution estimates were between 0.65 (24 months interval between measurements) and 0.73 (4 months interval between measurements) for leukocytes; between 0.61 and 0.67 for neutrophils; and between 0.43 and 0.50 for monocytes (nonparametric method 17 ). The results show that by estimating risk using only baseline values, we have probably underestimated the strength of the association between cell counts and the risk of recurrent events by 30 to 35% for leukocyte and neutrophil counts, and 50% for monocyte counts.

3 Grau et al Leukocytes and Ischemic Events 1149 TABLE 1. Annual Events and Risk Ratios in Univariate and Multivariate Analysis All Outcome Events (ischemic stroke, myocardial infarction, and vascular death) combined Parameter Cell Counts ( 10 9 /L) in Quartiles Events/Year Univariate Analysis Risk Ratio Relative to Quartile 1 (95% CI) P Value Multivariate Analysis Risk Ratio Relative to Quartile 1 (95% CI) P Value Leukocytes ( ) ( ) ( ) ( ) ( ) ( ) Neutrophils ( ) ( ) ( ) ( ) ( ) ( ) Monocytes ( ) ( ) ( ) ( ) ( ) ( ) Lymphocytes ( ) ( ) ( ) ( ) ( ) ( ) 0.53 The leukocyte count measured by chance within 7 days (mean 4 2) before a recurrent event was significantly higher than individual baseline values (n 211; /L, P 0.005) (Figure 1). The neutrophil count mainly contributed to increased leukocyte counts ( /L, P 0.009). TABLE 2. Leukocyte counts assessed at earlier time points before recurrent ischemia, and last values in patients without a second event were not different from baseline. Differences to baseline were higher in patients tested within 8 days before a recurrent event than in those tested earlier before an event (P 0.05). Annual Vascular Death, Ischemic Stroke, Myocardial Infarction and Risk Ratios in Multivariate Analysis Vascular Death (n 651) Fatal and Non-fatal Ischemic Stroke (n 884) Fatal and Non-fatal Myocardial Infarction (n 575) Parameter Cell Counts ( 10 9 /L) in Quartiles Event/Year Risk Ratio Relative to Quartile 1 (95% CI) Events/Year Risk Ratio Relative to Quartile 1 (95% CI) Event/Year Risk Ratio Relative to Quartile 1 (95% CI) Leukocytes ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) Neutrophils ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) Monocytes ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) Lymphocytes ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )

4 1150 Stroke May 2004 TABLE 3. Risk Factors for Ischemic Events. Multivariate Analysis Factor Relative Risk 95 % Confidence Interval P Value Age (per 10 years) Body mass index (per 10 kg/m 2 ) Non-caucasian Race Female Gender Hypertension Prior Myocardial Infarction Prior Stroke Congestive Heart Failure Current smoking (vs never smokers) Diabetes mellitus Peripheral Arterial Disease Coronary Heart Disease Hyperlipidemia Hematocrit Neutrophils (per 10 9 /L) Monocytes (per 10 9 /L) Discussion These prospective data show that in a high-risk population, leukocyte counts, and particularly neutrophil counts, independently predict ischemic events within a high-risk population and recurrent ischemic events. Most important, this study demonstrates for the first time that within one week, but not at earlier periods before an ischemic event, leukocyte counts are significantly elevated over baseline levels. Traditional risk factors for ischemic vascular diseases do not explain all epidemiological features of these diseases. 6 Increasing evidence indicates that inflammatory parameters are associated with the risk of future ischemic events. In a recent metaanalysis, the risk ratio between subjects in the upper and the lower tertile was 1.4 for leukocyte counts, 1.7 for CRP, and 1.8 for fibrinogen indicating similar predictability of these indexes. 10 Some studies have shown that TABLE 4. Difference in leukocyte counts between baseline and last measurement before a recurrent event or at study s end leukocyte counts independently predict recurrent coronary events. 14,15 Our results extend previous knowledge by showing that leukocyte counts are also associated with the risk of stroke and vascular death in patients with previous ischemic diseases. Furthermore, our data indicate that the neutrophil count is the most important predictor for recurrent events, whereas the role of monocytes is smaller. Assessments of regression dilution effects show that our analyses based on single baseline measurements may lead to a considerable underestimation of the predictive role of leukocyte counts, although the values calculated are only approximate regarding multivariate models. 19 These regression dilution effects were probably caused mainly by short- and medium-term factors that interact with leukocyte counts, eg, sampling and measurement errors (possibly greatest in monocyte counts), acute infections, and diurnal and seasonal fluctuations of leukocyte counts that show increasing values between morning and noon and higher values in winter than in summer months. 20,21 Analyses derived from baseline values probably Relative Risk of Ischemic Events in Different Risk Groups. Multivariate Analysis Quartile of Leukocyte counts ( 10 9 /L) P for Risk Factor n ( 5.86) ( ) ( ) ( 8.22) trend Men ( ) 1.21 ( ) 1.49 ( ) Women ( ) 1.04 ( ) 1.15 ( ) Age 65 years ( ) 1.25 ( ) 1.44 ( ) Age 65 years ( ) 1.16 ( ) 1.58 ( ) Current smoker ( ) 1.29 ( ) 1.48 ( ) Ex-smoker ( ) 1.26 ( ) 1.55 ( ) Never smoked ( ) 0.99 ( ) 1.24 ( ) Diabetes mellitus ( ) 1.05 ( ) 1.20 ( ) No diabetes mellitus ( ) 1.17 ( ) 1.42 ( ) Aspirin ( ) 1.18 ( ) 1.45 ( ) Clopidogrel ( ) 1.13 ( ) 1.33 ( ) 0.001

5 Grau et al Leukocytes and Ischemic Events 1151 underestimate the true association by as much as 30 to 50% in different cell counts. The large number of subjects in the CAPRIE trial provides a unique opportunity for subgroup analyses. We found that leukocyte counts were significant predictors for recurrent events in men but not in women. The reason for this gender difference is not understood at present. There is a strong interaction between smoking and leukocyte counts. 22 In our study, the leukocyte count had a predictive role independent from smoking, but the risk increase along leukocyte counts was more pronounced in current smokers and exsmokers than in patients who never smoked. The mechanisms linking leukocyte counts to cardiovascular risk are insufficiently understood. Cellular inflammation and, mainly, monocytes/macrophages play an important role in atherogenesis. 1 An increased number and stronger activation of circulating leukocytes could actively contribute to atherogenesis and organ ischemia by increased adhesion to and damage of the endothelium, and by disturbance of microvascular flow. 6 However, neutrophils that contributed most to increased risk do not play an important role in atherogenesis, whereas the number of monocytes that actively promote the process of atherosclerosis was not as important as a predictor. It is also possible that the injury of active atherogenesis causes an inflammatory response with high leukocyte counts being only a risk marker of the atherosclerotic process. Finally, increased leukocyte counts can reflect the role of chronic infectious diseases that themselves may contribute to cardiovascular risk. 23 Aspirin was shown to prevent stroke and myocardial infarction most efficiently in subjects with high levels of CRP. 11 This indicates that aspirin may partly exert its preventive potential by antiinflammatory effects. Our initial hypothesis that the predictive role of leukocyte counts is attenuated by aspirin, as compared with clopidogrel, was not supported by the results. Recent studies suggest that clopidogrel may also modulate inflammatory pathways, 24 and such features of clopidogrel could possibly explain the lack of difference to aspirin. It is an intriguing result of our study that leukocyte counts are significantly increased over baseline levels in the one week before a recurrent event, whereas measurements at earlier time points remained stable. Such additional acute increase heralds an imminent risk for the patient. Inflammatory parameters are increased after ischemia. 25 In light of our results, this may not only be a reaction to tissue damage but may partly originate in processes initiated before the infarction. Exacerbated inflammation plays an important role in the rupture of atherosclerotic plaques as a frequent cause of arterial thrombosis 26 and such local processes may be reflected by increased systemic inflammation. Unstable angina pectoris is accompanied by upregulated inflammation 25 and this may partly explain elevated leukocyte counts before myocardial infarction. Alternatively, acute infection that was identified as a trigger factor for myocardial infarction and ischemic stroke could explain the rise in leukocyte counts. 27,28 It is a limitation of our study that data on acute infection are not available and that it does not provide further insight into mechanisms linking leukocyte counts to ischemic events. The following conclusions can be drawn from our data. First, leukocyte counts and (mainly) neutrophil counts both independently predict the risk of ischemic events in a highrisk population and, also, the risk of secondary events in patients with previous ischemic diseases. Second, the predictive role of leukocyte counts was not modified by aspirin as compared with clopidogrel. Third, an acute increase of leukocyte counts over baseline levels heralds a period of increased risk that lasts approximately one week. Acknowledgements The authors wish to thank Sanofi-Synthelabo, Paris, and, particularly, Dr Isabelle Thizon-de Gaulle (Sanofi-Synthelabo) for invaluable help for this study. A.W.B and D.A.D. are employed by Sanofi-Synthelabo, the company that launched the CAPRIE trial; however, no conflict of interest arises from this fact regarding the presented data on leukocyte count and risk of recurrent events. References 1. Ross R. Atherosclerosis an inflammatory disease. N Engl J Med. 1999; 340: Friedman GD, Klatsky AL, Siegelaub AB. The leukocyte count as a predictor of myocardial infarction. N Engl J Med. 1974;290: Zalokar JB, Richard JL, Claude JR. Leukocyte count, smoking, and myocardial infarction. N Engl J Med. 1981;304: Prentice RL, Szatrowski TP, Fujikura T, Kato H, Mason MW, Hamilton HH. Leukocyte counts and coronary heart disease in a Japanese cohort. Am J Epidemiol. 1982;116: Grimm RH, Neaton JD, Ludwig W. Prognostic importance of the white blood cell count for coronary, cancer, and all-cause mortality. JAMA. 1985;254: Ernst E, Hammerschmidt DE, Bagge U, Matrai A, Dormandy JA. Leukocytes and the risk of ischemic diseases. JAMA. 1987;257: Kannel WB, Anderson K, Wilson PWF. White blood cell count and cardiovascular disease. Insights from the Framingham Study. JAMA. 1992;267: Gillum RF, Ingram DD, Makuc DM. White blood cell count and stroke incidence and death. The NHANES I epidemiologic follow-up study. Am J Epidemiol. 1994;139: Brown DW, Giles WH, Croft JB. White blood cell count: an independent predictor of coronary heart disease mortality among a national cohort. J Clin Epidemiol. 2001;54: Danesh J, Collins R, Appleby P, Peto R. Association of fibrinogen, C-reactive protein, albumin, or leukocyte count with coronary heart disease: meta-analyses of prospective studies. JAMA. 1998;279: Ridker PM, Cushman M, Stampfer MJ, Tracy RP, Hennekens CH. Inflammation, acetylsalicylic acid, and the risk of cardiovascular disease in apparently healthy men. N Engl J Med. 1997;336: Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000;342: Maseri A. Inflammation, atherosclerosis, and ischemic events exploring the hidden side of the moon. Editorial. N Engl J Med. 1997;336: Schlant RC, Forman S, Stamler J, Canner PL. The natural history of coronary heart disease: prognostic factors after recovery from myocardial infarction in 2789 men. The 5-year findings of the Coronary Drug Project. Circulation. 1982;66: Lowe GDO, Machado SG, Krol WF, Barton BA, Forbes CD. White blood cell count and haematocrit as predictors of coronary recurrence after myocardial infarction. Thromb Haemost. 1985;54: CAPRIE Steering Committee. A randomised, blinded, trial of clopidogrel versus aspirin in patients at risk of ischaemic events. Lancet. 1996; 348: Clarke R, Shipley M, Lewington S, Youngman L, Collins R, Marmot M, Peto R. Underestimation of risk associations due to regression dilution in

6 1152 Stroke May 2004 long-term follow-up of prospective studies. Am J Epidemiol. 1999;150: Frost C, Thompson S. Correcting for regression dilution bias: comparison of methods for a single predictor variable. J R Stat Soc Ser A. 2000;163: Davey Smith G, Phillips AN. Inflation in epidemiology: The proof and measurement of association between two things revisited. BMJ. 1996; 312: Fisch IR, Freedman SH. Smoking, oral contraceptives, and obesity. Effects on white blood cell count. JAMA. 1975;234: Woodhouse PR, Khaw KT, Plummer M,Foley A, Meade TW. Seasonal variations of plasma fibrinogen and factor VII activity in the elderly: winter infections and death from cardiovascular disease. Lancet. 1994; 343: Corre F, Lellouch J, Schwartz D. Smoking and leukocyte counts: results of an epidemiological survey. Lancet. 1971;2: Muhlestein JB. Chronic infection and coronary artery disease. Med Clin North Am. 2000;84: Hermann A, Rauch BH, Braun M, Schror K, Weber AA. Platelet CD40 ligand (CD40L) subcellular localization, regulation of expression, and inhibition by clopidogrel. Platelets. 2001;12: Whicher J, Biasucci L, Rifai N. Inflammation, the acute phase response and atherosclerosis. Clin Chem Lab Med. 1999;37: Shah PK. Plaque disruption and thrombosis: potential role of inflammation and infection. Cardiol Rev. 2000;8: Meier CR, Jick SS, Derby LE, Vasilakis C, Jick H. Acute respiratory-tract infections and risk of first-time acute myocardial infarction. Lancet. 1998;351: Grau AJ, Buggle F, Heindl S, Steichen-Wiehn C, Banerjee T, Maiwald M, Rohlfs M, Suhr H, Fiehn W, Becher H, Hacke W. Recent infection as a risk factor for cerebrovascular ischemia. Stroke. 1995;26:

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