Rheumatology Advance Access published October 11, 2012RHEUMATOLOGYOriginal article                                        ...
Simon Thornley et al.Thus whether serum urate is causally associated with            test in the 5-year period before thei...
Serum urate and incident CVDFIG. 1 A DAG, characterizing the influences on risk of           recordings and other unobserv...
Simon Thornley et al.TABLE 1 Baseline characteristics, by sex    Characteristic                                           ...
urate))] doubled the relativeminimum of 1. The distributions of observed and imputed      hazard of CVD across the distrib...
Serum urate and incident CVDTABLE 3 Measures of association with CVD from a Cox proportional hazards model                ...
Simon Thornley et al.or to introduce inappropriate confounder adjustments.          the exposure. Some studies have report...
Serum urate and incident CVDmodel with good fit, we stratified by ethnicity rather than      9,458 incident cases and 155,...
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Is serum urate causally associated with incident cardiovascular disease?


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A cohort study of the association between serum urate and cardiovascular disease in a New Zealand population.

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Is serum urate causally associated with incident cardiovascular disease?

  1. 1. Rheumatology Advance Access published October 11, 2012RHEUMATOLOGYOriginal article doi:10.1093/rheumatology/kes269Is serum urate causally associated with incidentcardiovascular disease?Simon Thornley1, Roger J. Marshall1, Rod Jackson1, Dudley Gentles1,Nicola Dalbeth2, Sue Crengle3, Andrew Kerr1,4 and Sue Wells1Abstract Downloaded from http://rheumatology.oxfordjournals.org/ at University of Auckland on October 14, 2012Objective. With studies reporting both positive and negative associations, the influence of serum urate onincident cardiovascular disease (CVD) is uncertain. We sought to determine whether serum urate is caus-ally associated with incident CVD.Methods. Participants were aged 30–80 years and were screened for CVD risk in primary care between2006 and 2009. Participants had blood pressure, lipids, age and ethnic group recorded at assessment,with record linkage providing drug dispensing, hospital diagnoses and laboratory test results. Outcomeswere derived from hospital diagnoses and mortality records until December 2009. Cox models were usedto assess the influence of exposures on outcomes.Results. A total of 78 707 people, free of CVD, were enrolled, and 1328 CVD events occurred duringfollow-up. Serum urate was recorded before baseline assessment in 43% (34 008/78 707) of participants.After adjustment for confounding factors, a 2 S.D. difference in serum urate (0.45 vs 0.27 mmol/l) wasassociated with a hazard ratio (HR) of 1.56 (95% CI 1.32, 1.84). This was more than double that of theequivalent distributional change in high-density lipoprotein cholesterol (adjusted HR 1.22) and one-thirdgreater than that for HbA1c (adjusted HR 1.41).Conclusion. Serum urate is likely to be causally associated with CVD. This supports public health actionto reduce urate levels in populations with significant burdens of the disease.Key words: cardiovascular diseases, risk factors, epidemiology. CLINICAL SCIENCEIntroduction characterizes research on the effect of serum urate on‘Measurement of serum uric acid levels is unlikely to en- the incidence of cardiovascular disease (CVD), reflectedhance usefully the prediction of [coronary heart disease] in these two contrasting quotes from European andCHD, and this factor is unlikely to be a major determinant Japanese researchers, respectively. Meta-analyses of ob-of the disease in general populations’ [1]. ‘These results servational studies [3, 4] have reported some associationshowed that hyperuricaemia has a strong association between hyperuricaemia (serum urate >400 mmol/l) andwith . . . death in all causes, coronary heart disease, . . . and incident CHD. One study [3], for example, reported anindicated that serum uric acid seems to be a considerable increase in risk of CVD (pooled relative risk 1.46; 95%risk factor for reduced life expectancy’ [2]. Uncertainty CI 1.20, 1.73), but the association diminished with adjustment for established risk factors (pooled relative1 Section of Epidemiology and Biostatistics, School of Population risk 1.09; 95% CI 1.03, 1.16). Such factors included age,Health, 2Department of Medicine, Faculty of Medicine and Health systolic blood pressure, cholesterol, smoking and eitherSciences, 3Te Kupenga Hauora Maori, School of Population Health,University of Auckland and 4Counties Manukau District Health Board, a diagnosis or other laboratory indices of diabetes.Hospital Road, Otahuhu, Auckland, New Zealand. However, generally it is not clear which factors to adjustSubmitted 19 June 2012; revised version accepted 29 August 2012. for. Some, such as systolic blood pressure, may be on theCorrespondence to: Simon Thornley, Section of Epidemiology and causal pathway between serum urate and CVD, thusBiostatistics, Level 4, School of Population Health, Tamaki Innovation mediating the relationship rather than acting as a confoun-Campus, Corner of Merton and Morrin Roads, Glen Innes, TheUniversity of Auckland, Private Bag 92019, Auckland 1142, New der, since there is evidence that high levels of serumZealand. Email: s.thornley@auckland.ac.nz urate causally influence the onset of hypertension [4, 5].! The Author 2012. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com 1
  2. 2. Simon Thornley et al.Thus whether serum urate is causally associated with test in the 5-year period before their PREDICT assess-CVD remains uncertain. ment; otherwise data for these variables were missing. The prevalence of gout is extremely high, by interna-tional standards, among Maori ($6%) and Pacific people ¯ Outcomes($8%) living in New Zealand [6, 7]. Together these ethnic CVD events (acute coronary syndromes, coronary pro-groups comprise between 20% and 25% of the total popu- cedures, stroke, transient ischaemic attack, haemorrhagelation, so serum urate is measured frequently in New stroke, peripheral vascular disease, peripheral arterialZealand. We have been conducting a large cohort study procedures and congestive heart failure) were identifiedof CVD risk factors that involves linking risk factor data from hospital discharge and mortality records usingderived from primary care-based screening to laboratory International Classification of Disease codes, as previ-results, drug dispensing, hospital admission diagnoses, ously described [11]. They covered the period fromand mortality records. Here we explore the relationship January 2006 to December 2009. The analysis was ofbetween urate levels and the incidence of CVD. the outcome of any CVD event, including immediate death that was coded as caused by such conditions.Methods Downloaded from http://rheumatology.oxfordjournals.org/ at University of Auckland on October 14, 2012Study design Other dataThe PREDICT cohort has been described elsewhere [8, 9]. Patient medications, specifically anti-hypertensive andBriefly, PREDICT is a web-based program for assessing gout medication, were obtained from the New Zealandand managing CVD risk that is integrated with commonly Pharmaceutical Information Database [12], a register ofused general practice electronic medical records in New community dispensing, and were merged with PREDICTZealand. PREDICT generates a standardized cardiovas- records. Anti-hypertensive drugs included b-blockers,cular risk profile on each patient and calculates a 5-year calcium channel blockers, angiotensin convertingpercentage CVD risk based on the patient’s age, gender, enzyme (ACE) inhibitors, a-blockers and thiazide diuretics.ethnic group, blood pressure, total to high-density lipo- Gout medication included allopurinol, colchicine andprotein (HDL) cholesterol ratio, family history of CVD, probenecid.smoking and diabetes status, using Framingham Demographic information was taken from the PREDICTstudy-derived equations [10]. PREDICT clinical informa- database and, in the case of ethnicity, the variable wastion is either entered by the general practitioner at the recorded in both PREDICT and national data sources.time of risk assessment (blood pressure, diabetes Ethnicity data were classified according to a standardizedstatus, family history of CVD, smoking status and family data protocol [13], in which Maori and then Pacific ethnic ¯history of CVD) or derived from practice management groups are prioritized if more than one ethnic group wassoftware from information stored about the patient (age, recorded. Individuals were coded as either Maori, Pacific, ¯gender, ethnic group and total to HDL cholesterol ratio). Indian or Other. The Other group were mainly of NewA risk profile is stored for each patient and is linked to an Zealand European descent.encrypted, unique, National Health Index. The indexenables linkage with national health records, such as hos- Analysispital discharge codes, mortality, community drug dis- Statistical analysis centred on developing a survival modelpensing and laboratory test results. Enrollees between for incidence of any CVD event, taking serum urate as aJanuary 2006 and 15 October 2009 were selected for potential predictor. We used a Cox regression model, withthis analysis since full dispensing and coded mortality re- age at event as the time variable rather than time to eventcords were available for this period. Those aged <30 or from baseline enrolment. This approach is increasingly>80 years at the time of screening were excluded. We recommended for observational epidemiological analysisalso excluded people with a history of prior CVD or of CVD [14, 15]. Time, therefore, was considered as leftheart failure, identified by a general practitioner diagnosis truncated (patients are observed conditional on survivalof CVD or hospitalization with CVD in the past 5 years, or up until that point) and right censored. Proportionalthose dispensed a loop diuretic in the 6 months before hazards assumptions were checked using scaledassessment who were assumed to have heart failure. Schoenfeld residuals [16]. Restricted cubic splines were used to investigate the relationship between continuousSerum urate variables and time to event as a check on the modellingThe urate concentration of enrollees in PREDICT were ob- assumption of linearity. HRs for continuous variables weretained by anonymized linkage to community laboratory reported by comparing the relative hazard between thedata in the Diagnostic Medlab database. The database 16th and 84th centiles of the variable (1 S.D. either sidewas the sole provider of laboratory tests, outside hospital, of the mean for a normal distribution) [17]. This allowsto the greater Auckland region until late 2009. If a person direct comparison with relative hazards of binary vari-had had many serum urate measurements, we used the ables, since the 16th and 84th centiles are roughly equiva-one prior to their first PREDICT assessment. Serum urate lent to the one-unit difference between 0 and 1 of a binaryand other laboratory variables (HbA1c and HDL choles- variable. That is, 2 S.D.s on a binary scale with a mean ofterol) were only recorded if a patient had had a laboratory $0.5 is 1.2 www.rheumatology.oxfordjournals.org
  3. 3. Serum urate and incident CVDFIG. 1 A DAG, characterizing the influences on risk of recordings and other unobserved influences (colliders),developing CVD. we believed that including such variables was more likely to result in biased effect estimates than excluding them from the analysis [19]. We also tested for interactions, in particular, between serum urate and gender. From other studies of CVD using similar risk factor profiles, effect estimates have been observed to change with age. These were tested using the likelihood ratio (P < 0.05). When using age at event as the time variable, such interactions may manifest as viola- tions of the proportional hazards assumption. We tested for such violations using the cox.zph function, which calculates tests of the proportional hazards assumption for each cov- ariate by correlating the corresponding set of scaled Schoenfeld residuals with a suitable transformation of Downloaded from http://rheumatology.oxfordjournals.org/ at University of Auckland on October 14, 2012 time, based on the Kaplan–Meier estimate of the survival function [20]. Stratification allowed different baseline haz-Dark font variables are those that are observed, whereasgrey font variables represent those that are unobserved. ards for exposure groups, where the proportional hazardst: variable recorded at baseline; tÀ1: variable recorded assumption was likely to be contravened.before baseline; LDL: low-density lipoprotein cholesterol; Because many serum urate and other laboratory valuesTrigs: serum triglycerides; meds: medications. were missing, we used multiple imputation, so that the modelling results reported were based on averaging model parameters over 10 random imputations [16]. To help decide model structure and which variables to Variables that were used in the multiple imputation mod-include in a model, we sketched a diagram of likely causal elling were gender, serum metabolic markers (creatinine,mechanisms and pathways [a directed acyclic graph HDL cholesterol, triglycerides, HbA1c and urate), age at(DAG)] [18], and used some of the ideas proposed by enrolment, systolic blood pressure, smoking status, dia-Pearl to examine causality. The DAG we constructed betes, ethnic group, death and CVD event, along with anincluded measured and unmeasured influences on CVD interaction between serum urate and sex.risk that we felt were important (Fig. 1). Lines with an end All analyses were done using R software (version 2.14.1)arrow represent a causal link acting in the direction of the [21]. The package rms [22] was used for the Cox regres-arrow. Those lines that are solid represent a link that can sion analysis and the functions aregImpute andpotentially be observed from our data, dashed lines are fit.mult.impute for multiple imputation. The aregImputecausal mechanisms we believe to hold but cannot be function finds transformations that optimize how eachobserved in our data. variable may be predicted from every other variable, From Fig. 1, we considered a diagnosis of gout (derived using additive semiparametric models. The fit.mult.imputefrom dispensing data) as likely to be a mediator of the function was then used to average sets of regressioninfluence of urate on CVD risk. We assumed that lipopro- coefficients and compute variance and covariance, ad-tein concentrations are causally associated with CVD, and justed for the error derived from the uncertainty from im-so they are included in the model. Blood pressure (BP), putation of missing data. This project was approved bymeasured before baseline (BPtÀ1 in Fig. 1) and measured the national Multi Region Ethics Committee in 2007 (MEC/at baseline (BPt), were considered mediators of the influ- 07/19/EXP).ence of urate on CVD risk, and were therefore not con-trolled for in the model. Blood pressure lowering and statin Resultstherapies were considered to represent colliders [18],which may introduce bias from an unobserved variable Table 1 shows the baseline characteristics of thethat would otherwise not influence our analysis, so these PREDICT cohort, that is, when first enrolled in thevariables were excluded. Although certain blood pressure PREDICT database. Men (56%) outnumbered women,medications, such as thiazide diuretics, are known to raise and the mean age was 55 years, with women ratherserum urate, we believe that this is a relatively small influ- older. Pacific people accounted for 23% of the cohort,ence on the causal paths compared with those otherwise Maori 16% and Indian 7%. The remainder of the cohort ¯identified in the DAG. Furthermore, blood pressure and and majority ethnic group, Other, was 86% European, 6%treatment of the condition were regarded as mediators Chinese and 8% composed of a large variety of ethnic(caused by high urate levels), as was a diagnosis of groups. More women than men were diagnosed with dia-gout. In view of these considerations, to block backdoor betes; however, HbA1c levels were equivalent. Men hadpaths, using Pearl’s terminology (adjust for confounding higher levels of serum urate, higher lipid ratios and lowervariables), the regression analysis adjusted for gender, levels of HDL. Women were less likely than men to smokeHbA1c, ethnic group, smoking status and lipoprotein con- cigarettes.centrations (HDL cholesterol). Because post-treatment Urate values were approximately normally distributed,variables are likely to be strongly influenced by baseline with a lower mean in women compared with men.www.rheumatology.oxfordjournals.org 3
  4. 4. Simon Thornley et al.TABLE 1 Baseline characteristics, by sex Characteristic Men Women Total Total 43 815 34 892 78 707 Age at baseline, mean (S.D.), years 52.9 (10.5) 57.1 (9.8) 54.8 (10.4) Ethnic group, n (%) Other 23 971 (54.7) 19 311 (55.4) 43 282 (55.0) Maori ¯ 6578 (15.0) 5696 (16.3) 12 274 (15.6) Pacific 9967 (22.8) 7766 (22.3) 17 733 (22.5) Indian 3299 (7.5) 2119 (6.1) 5418 (6.9) Serum urate, mean (S.D.), mmol/l; n=34 008, (43%) 0.39 (0.09) 0.32 (0.09) 0.36 (0.09) HbA1c (%); n = 33 075 (42%) Mean (S.D.) 6.66 (1.71) 6.68 (1.67) 6.67 (1.69) Diagnosis of diabetes, n (%) 7709 (17.6) 7170 (20.6) 14 879 (18.9) Current smoker, n (%) 8630 (19.7) 5370 (15.4) 14 000 (17.8) Systolic BP, mean (S.D.), mmHg 130.3 (17.0) 131.3 (18.4) 130.8 (17.7) Downloaded from http://rheumatology.oxfordjournals.org/ at University of Auckland on October 14, 2012 Total cholesterol/HDL ratio, mean (S.D.) 4.31 (1.35) 3.72 (1.17) 4.04 (1.31) HDL cholesterol, mean (S.D.), mmol/l; n = 68 224 (87%) 1.30 (0.35) 1.55 (0.43) 1.41 (0.41)TABLE 2 Serum urate, by sex, ethnic group, diabetes and FIG. 2 Density plot comparing the distributions ofsmoking status observed (dashed line) and imputed urate values (solid line). Serum urate, mean (S.D.), mmol/l Characteristic Men Women Ethnic group Other 0.37 (0.08) 0.30 (0.08) Maori ¯ 0.41 (0.09) 0.34 (0.09) Pacific 0.42 (0.09) 0.36 (0.09) Indian 0.35 (0.08) 0.29 (0.07) Diabetes Yes 0.37 (0.09) 0.34 (0.09) No 0.39 (0.09) 0.32 (0.08) Current smoker Yes 0.39 (0.09) 0.33 (0.09) No 0.39 (0.09) 0.32 (0.09) Initial model checking revealed that the proportional hazard assumption was not supported for gender and eth-There were, however, 57% missing serum urate levels, nicity. For this reason the model was stratified on these58% missing HbA1c and 13% missing HDL cholesterol. factors, meaning that separate baseline hazards wereNo other data items had missing values. Mean assumed for all permutations of gender and ethnicobserved urate values varied substantially by ethnic group. A gender by urate and ethnic group by urate inter-group, but varied little by diabetes or smoking status action was tested for, but neither was found to be statis-(Table 2). Maori and Pacific ethnic groups were highest, ¯ tically significant.whereas mean levels among the Other and Indian Table 3 shows the results of the Cox regression analysis.ethnic groups were about half to two-thirds of an S.D. In the model, comparing measures at the 16th and 84thlower. centiles showed an HR of 1.56 (95% CI 1.32, 1.84) for A total of 1328 CVD events occurred during follow-up, serum urate. The relative hazard was linear (on the loga-with 167 patients dying during this period. Median follow- rithmic scale), which indicated that an increase in serumup time was 538 days, with a maximum of 1424 and a urate of 0.29 mmol/l [=ln(2)/(
  5. 5. urate))] doubled the relativeminimum of 1. The distributions of observed and imputed hazard of CVD across the distribution of observed urateurate values (Fig. 2) show that the variance is reduced values. In the study population, the association betweenamong imputed compared with observed values, because a 2 S.D. difference in urate level (67% relative increase) onimputed values are regressed to the mean. incident CVD risk was higher than adjusted effects of the4 www.rheumatology.oxfordjournals.org
  6. 6. Serum urate and incident CVDTABLE 3 Measures of association with CVD from a Cox proportional hazards model Comparisona Crude HRb (95% CI) Adjusted HRc (95% CI) Factor High Low Serum uratea, mmol/l 0.45 0.27 1.76 (1.56, 1.99) 1.56 (1.32, 1.84) Non-smoker 1.00 0.00 1.71 (1.50, 1.95) 1.63 (1.43, 1.86) HbA1ca, % 8.00 5.50 1.41 (1.29, 1.54) 1.41 (1.29, 1.55) Serum HDLa, mmol/l 1.03 1.79 1.75 (1.49, 2.04) 1.22 (1.03, 1.45)n = 78 707. aComparisons for the continuous variables are taken at the 84th and 16th centiles (z = 1) for comparability withbinary variables. The binary variables are, by definition, set at 0 and 1. bStratified by sex and ethnic group. cAdjusted for allvariables in the table and stratified by gender and ethnic group. Downloaded from http://rheumatology.oxfordjournals.org/ at University of Auckland on October 14, 2012 For a 60-year-old male smoker in the Other ethnicFIG. 3 Measures of association with CVD from a Cox group with a serum urate level of 0.27 mmol/l, HbA1c ofmodel. 6% and serum HDL cholesterol of 1.34 mmol/l, the 5-year risk of CVD equates to 1 À (0.813/0.871) = 6.7%. If his serum urate is about 2 S.D. greater, that is 0.45 mmol/l, his 5-year cumulative incidence of CVD will increase to 10.1% (about a one-third increase). This calculation is based on an estimate of the baseline survival (S0) of 88.9% at 60 years and 83.8% at 65 years. Discussion We found that, given plausible assumptions, raised serum urate is likely to have a substantial causal effect on the incidence of CVD, of a similar or greater magnitude to the effects of high HbA1c or low HDL cholesterol levels. ACox-modelled survival estimates (with 95% confidence strength of the study was that it was based on a largeintervals) by time for serum urate at the 16th centile cohort, n = 79 707, in which the information had been col-(0.27 mmol/l) compared with the 84th centile (0.45 mmol/l) lected in a systematic and standardized way. An asso-for a non-smoking male in the Other ethnic group, with ciated weakness, however, is the incompleteness of theHDL cholesterol = 1.34 mmol/l and HbA1c = 6%. laboratory data, and in particular of the serum urate values. To deal with these missing values, we used mul- tiple imputation, which is recommended to reduce bias inequivalent change in the distribution of HbA1c (37% rela- effect estimates when compared with complete-casetive increase) and HDL cholesterol (155% relative analysis [16]. In a sensitivity analysis, using complete-increase). case analysis, our observed effect estimates were similar An illustration of the extent to which a change in serum to those derived from multiple imputation [the adjusted HRurate affects survival is shown in Fig. 3. It gives the of the effect of urate was 1.59 (95% CI 1.32, 1.90), com-Cox-modelled survival plot for a man in the Other ethnic pared with 1.56 in Table 2]. We can only speculate that ifgroup, with HDL cholesterol of 1.34 mmol/l, HbA1c 6% serum urate had been measured in everyone, the effectand a non-smoker, showing the average change asso- estimates would not have differed substantially.ciated with a 2 S.D. difference in serum urate on survival We have also explored sensitivity analyses of multivari-probability. This association (change in urate on survival ate effect estimates (see supplementary data, available atprobability) increases with age. Rheumatology Online). These included carrying out sep- From the model, the cumulative incidence over a spe- arate analyses by gender, with and without imputation ofcified period of time, e.g. the 5-year risk, can be derived missing values, varying the time scale chosen, includingusing the formula: those who had used loop diuretics at baseline assess- ment, and dividing urate values by quintile. Generally Sðt þ Þ 1À these analyses were congruent with the effect estimates SðtÞ reported in Table 3.where t is age of an individual, is the interval over which A positive aspect of the study was that we explicitlythe cumulative incidence is calculated (typically 5 or 10 considered causal paths to determine variables to adjustyears) and S is the survival probability, estimated by the in the model [18]. This process is conceptually appealingCox model. and less likely to underestimate the effect of serum uratewww.rheumatology.oxfordjournals.org 5
  7. 7. Simon Thornley et al.or to introduce inappropriate confounder adjustments. the exposure. Some studies have reported effects ofWhether our DAG is an accurate reflection of the causal serum urate on CVD as a continuous variable. For ex-interaction between the variables in our study may be ample, the Framingham study [23] (n = 6763) found no sig-debated; for example, whether systolic blood pressure is nificant association between serum urate and CHDa mediator of the effect of urate or whether it should be incidence in their adjusted Cox model among men, butincluded as a confounder in regression equations. To ex- a significant increase in risk with women. We found a stat-plore the effects of variable selection based on the DAG, istically significant association between urate and CVD,we carried out a sensitivity analysis, altering the model by without a gender  urate interaction, and so our measures(i) adding a diagnosis of diabetes in the model; (ii) inter- of association were aggregated over the whole popula-changing HDL cholesterol with the total cholesterol/HDL tion. Our study reached similar conclusions to theratio and (iii) adding blood pressure as a potential con- National Health and Nutrition Examination Surveyfounder. The first two changes to the model resulted in (NHANES)-I [24] cohort study (n = 5926), which founda 2% change in the adjusted HR for serum urate. After that serum uric acid levels were significantly associatedinclusion of diabetes, the effect of HbA1c was reduced with CVD mortality after adjustment for known confoun-from 1.41 to 1.36 (comparing individuals with baseline ders. The NHANES study used CVD mortality as its out- Downloaded from http://rheumatology.oxfordjournals.org/ at University of Auckland on October 14, 2012measures of 8.00 and 5.50%). If systolic blood pressure come event while our study used hospital admission oris included, our adjusted effect of urate diminished death from CVD. Its advantages were that it had longslightly [for 0.45 compared with 0.27 mmol/l; the HR follow-up time (16.4 years) and included both white andreduced from 1.56 (95% CI 1.32, 1.84) to HR = 1.48; black participants (not present in the Framingham cohort).(95% CI 1.25, 1.75)]. The authors reported age-adjusted HRs for cardiovascu- Family history of ischaemic heart disease may also be lar mortality in participants aged 45–54 years that wereconsidered a confounder of the relationship between similar to ours: 1.28 (95% CI 1.08, 1.52) in men and 1.43urate and CVD. For this study, family history of CVD was (95% CI 1.16, 1.37) in women for each 0.06 mmol/l rise inrecorded as a history of CHD or ischaemic stroke in a serum urate level. Our study, using age as thefirst-degree relative (father or brother 55 years, mother time-to-event variable, is likely to adjust for the effect ofor sister 65 years). When this variable was added, how- age more accurately than the more traditional methodsever, the point and interval estimate for serum urate re- used in the NHANES study, which aggregated age intomained unchanged (see supplementary data, available at 15-year intervals. Despite these differences in methods,Rheumatology Online). this study was concordant with our findings. The nature of the cohort, composed of a generally high Our study provides statistical evidence that elevatedCVD risk population rather than a designed sample, is also serum urate is likely to cause CVD. Biological evidencea potential weakness. The high prevalence of diabetes also supports our findings, highlighting the role of serum($20%) reported among the cohort along with the urate in the pathogenesis of endothelial injury [25]. If thisgender distribution favouring men was expected. causal relationship is true, attention turns to what deter-Nevertheless, there is substantial heterogeneity in the mines serum urate, and how serum urate may be lowered,risk profile of the study population, so there is no reason either by lifestyle modification, or through drug treatment.to believe that the lack of representativeness was an im- In addition to the role of purine-rich foods, fructose intakeportant problem for these analyses. may also contribute to hyperuricaemia through increased Using age as the outcome variable in the Cox model hepatic synthesis of purines [26, 27]. This gives impetusimposes an assumption that entry into the study is inde- for public health action to limit intake of sugar, the dom-pendent of age. This is unlikely to be true here, given that inant source of fructose in the diet, as well as purine-richnational CVD screening guidelines recommend initiation foods. In addition, this finding raises the question ofof screening at specified ages, which differ for varying whether pharmaceutical reduction of urate levels, withethnic groups. However, use of age in survival modelling urate-lowering therapy such as allopurinol, can reduceis now the recommended approach for cohort studies that CVD risk. Such an idea is strengthened by the results ofestimate CVD incidence [15]. This choice of time scale is a small (n = 65) cross-over trial of allopurinol therapy injustified because the use of age at event results in less patients with symptomatic, effort-dependent angina.bias of effect estimates compared with time to event [16]. Treatment with 600 mg of allopurinol per day forThis method is increasingly recommended if the period of 6 weeks increased the time to S-T segment depressionobservation is the time from birth to event, as it is when by 43 s (95% CI 31, 58) compared with otherwise equiva-modelling CVD risk, rather than time from intervention to lent treatment with placebo [28].event, as it is in a randomized trial [15]. Maori and Pacific people in this study had mean levels ¯ There are some differences and similarities between our of serum urate $15% higher than Others, Indians andresults and other studies. Some studies report the asso- other Asians. We speculate that dietary rather than gen-ciation between raised serum urate in a binary fashion etic differences are more likely to account for these differ-(presence or absence of hyperuricaemia) [3]. In our ences, because New Zealand Maori almost all share ¯study we found evidence of a log-linear relationship be- significant ancestry with New Zealand Europeans due totween urate concentration and CVD risk, so studies that widespread intermarriage, yet their mean urate valuesemployed a cut-off are likely to underestimate the effect of vary substantially. In our regression analysis, to obtain a6 www.rheumatology.oxfordjournals.org
  8. 8. Serum urate and incident CVDmodel with good fit, we stratified by ethnicity rather than 9,458 incident cases and 155,084 controls: prospectiveevaluating the effects of this variable. However, because study and meta-analysis. PLoS Med 2005;2:e76.CVD incidence and prevalence are significantly higher in 2 Tomita M, Mizuno S, Yamanaka H et al. DoesMaori and Pacific peoples compared with Europeans ¯ hyperuricemia affect mortality? A prospective cohort[29–31], future work will evaluate whether variations in study of Japanese male workers. J Epidemiol 2000;10:serum urate levels account for ethnic variations in the 403–9.prevalence of CVD. In conclusion, serum urate is asso- 3 Kim SY, Guevara JP, Kim KM, Choi HK, Heitjan DF,ciated with incident CVD and is likely to be a significant Albert DA. Hyperuricemia and coronary heart disease: afactor in the disease’s causal pathway. systematic review and meta-analysis. Arthritis Care Res 2010;62:170–80. ¨ 4 Sundstrom J, Sullivan L, D’Agostino RB, Levy D, Rheumatology key messages Kannel WB, Vasan RS. Relations of serum uric acid to . Substantial uncertainty exists about the effect of longitudinal blood pressure tracking and hypertension serum urate on CVD. incidence. Hypertension 2005;45:28–33. . After making causal assumptions, we found a 5 Feig DI, Soletsky B, Johnson RJ. Effect of allopurinol on strong association between urate and CVD. Downloaded from http://rheumatology.oxfordjournals.org/ at University of Auckland on October 14, 2012 blood pressure of adolescents with newly diagnosed es- . Urate differs substantially between ethnic groups, sential hypertension. JAMA 2008;300:924–32. and may explain differences in CVD burden. 6 Winnard D, Kake T, Gow P et al. Debunking the myths to provide 21st century management of gout. N Z Med J 2008;121:79–85.Acknowledgements 7 Winnard D, Wright C, Taylor WJ et al. National prevalence of gout derived from administrative health data inThe authors would like to thank the National Health Board Aotearoa New Zealand. Rheumatology 2012;51:901–9.Analytic Services and Diagnostic Medlab Ltd for supplying 8 Bannink L, Wells S, Broad J, Riddell T, Jackson R. Web-anonymized data. They would also like to thank affiliated based assessment of cardiovascular disease risk in rou-general practitioners and practice nurses and patients be- tine primary care practice in New Zealand: the first 18,000longing to the ProCare Network, Auckland PHO Ltd, patients (PREDICT CVD-1). N Z Med J 2006;119:U2313.HealthWest, East Health Services, National Maori ¯ 9 Wells S, Kerr A, Broad J, Riddell T, Kenealy T, Jackson R.Hauora Coalition, Alliance, Te Tai Tokerau and Manaia The impact of New Zealand CVD risk chart adjustmentsPHOs. for family history and ethnicity on eligibility for treatment (PREDICT CVD-5). N Z Med J 2007;120:U2712.PREDICT was developed by a collaboration of clinical epi-demiologists at the University of Auckland, IT specialists 10 Anderson KM, Odell PM, Wilson PW, Kannel WB.at Enigma Publishing Ltd (a private provider of online Cardiovascular disease risk profiles. Am Heart J 1991; 121(1 Pt 2):293–8.health knowledge systems), primary health care organiza-tions, non-governmental organizations (New Zealand 11 Riddell T, Wells S, Jackson R et al. Performance ofGuidelines Group, National Heart Foundation, Diabetes Framingham cardiovascular risk scores by ethnic groupsNew Zealand, Diabetes Auckland), several district health in New Zealand: PREDICT CVD-10. N Z Med J 2010;123: 50–61.boards and the Ministry of Health. The PREDICT softwareplatform is owned by Enigma Publishing Ltd (PREDICT is 12 New Zealand Health Information Service. Pharmaceuticala trademark of Enigma Publishing Ltd). Information Database (PHARMS). Wellington, New Zealand: New Zealand Health Information Service, 2011.Funding: This research was supported by a grant from the 13 Ministry of Health. Ethnicity data protocols for the healthNational Heart Foundation of New Zealand and a Health and disability sector. Wellington, New Zealand: Ministry ofResearch Council Clinical Research Training Fellowship Health, 2004.(grant number 11/145). 14 Conroy RM, Pyorala K, Fitzgerald AP et al. Estimation ofDisclosure statement: N.D. has received consultancy fees ten-year risk of fatal cardiovascular disease in Europe: thefrom Takeda, Ardea Biosciences, Metabolex and SCORE project. Eur Heart J 2003;24:987–1003.Novartis. All other authors have declared no conflicts of ´ ´ 15 Thiebaut ACM, Benichou J. Choice of time-scale in Cox’sinterest. model analysis of epidemiologic cohort data: a simulation study. Stat Med 2004;23:3803–20. 16 Harrell FE. Regression modeling strategies. 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