1 - European Heart Journal

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Chronic obstructive pulmonary disease and sudden cardiac death: the Rotterdam Study
Lies Lahousse, Maartje N. Niemeijer, Marten E. van den Berg, Peter R Rijnbeek, Guy F. Joos,
Albert Hofman, Oscar H. Franco, Jaap W. Deckers, Mark Eijgelsheim, Bruno H. Stricker, Guy
G. Brusselle
Online data supplement
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Online methods
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Online figures
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Online tables
Figure S1:Time of sudden cardiac death in subjects with COPD and without COPD.
Figure S2: Cumulative incidence function of sudden cardiac death (Gray’s test; p=0.0006)
and other death (Gray’s test; p<0.0001) according to COPD status.
Figure S3: Cumulative incidence function of sudden cardiac death (Gray’s test; p=0.0002)
and other death (Gray’s test; p<0.0001) according to COPD exacerbator status (no
COPD, COPD without frequent exacerbations, COPD with frequent
exacerbations).
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ONLINE METHODS
Setting
The Rotterdam Study is a prospective population-based cohort study, which started in 1990 in
the Ommoord district, in the city of Rotterdam, the Netherlands. All inhabitants of the Ommoord
district, aged 55 years of age and older were invited to participate (n=10215). At baseline, from
1990 through 1993, 7983 participants (response rate 78%) were included. In 2000, an additional
3011 participants, out of 4472 invitees, were enrolled (response rate 67%). This extension
consisted of all persons living in the study district who had become 55 years of age or had moved
into the study district. A second similar extension of the cohort was initiated in 2006, in which 3
932 participants (out of 6057 invitees; response rate 65%), aged 45 years and older were
included. Follow-up examinations are conducted periodically, approximately every 4 to 5 years.
Examinations consist of a home interview and an extensive set of tests at a specially built
research facility in the study district. Besides this, participants are continuously monitored for
major morbidity and mortality through linkage of general practitioners and municipality records
to the study base. The Rotterdam Study was approved by the medical ethics committee according
to the Population Study Act Rotterdam Study executed by the Ministry of Health, Welfare and
Sport of the Netherlands. The study population consisted of participants who gave informed
consent for follow-up.
High-sensitivity C-reactive protein (hsCRP) serum level measurement
HsCRP serum levels were measured as previously described.(1) Non-fasting blood was collected
at baseline and stored at -80°C until CRP measurement. Storing temperature did not affect
stability of CRP. HsCRP measurements were performed on all blood samples using a rate near-
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infrared particle immunoassay (Immage Immunochemistry System; Beckman Coulter, San
Diego, CA).
Covariables
Information on covariables was obtained through interview (i.e. smoking and alcohol use),
laboratory, medical files, or physical examination (i.e. height, weight, systolic and diastolic
blood pressure, myocardial infarction, heart failure, revascularization procedures, diabetes
mellitus, atrial fibrillation, heart-rate corrected QT (QTc) interval and statin use) at the regular
visits of the study participants to the Rotterdam Study research center. Pack years of cigarette
smoking were computed as duration of self-reported smoking (years) multiplied by the number
of daily smoked cigarettes, divided by 20. Body mass index was calculated as weight in
kilograms divided by height in meters squared. Systolic (SBP) and diastolic blood pressure
(DBP) were measured in sitting position at the right upper arm. The average of 2 consecutive
measurements was taken. Hypertension was defined as a SBP >140 mmHg, DBP >90 mmHg, or
use of blood pressure lowering medication for the indication hypertension. Myocardial infarction
was adjudicated based on a combination of symptoms, ECG measurements and enzyme markers.
Heart failure diagnosis was adjudicated in accordance with the guidelines of the European
Society of Cardiology and included typical signs or symptoms of heart failure confirmed by
objective evidence of cardiac dysfunction, as described in more detail previously(2, 3). A
revascularization procedure is either a percutaneous coronary intervention or a coronary artery
bypass graft. Diabetes mellitus was defined as fasting glucose above 6.9 mmol/L, non-fasting
glucose above 11.0 mmol/L, the use of blood glucose lowering medication, or a previous
diagnosis of diabetes mellitus. Atrial fibrillation is ascertained from electrocardiogram
measurements as well as medical records. QTc interval according to Bazett’s formula was
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derived from a standard electrocardiogram. Medication dispensing data was obtained from all
seven fully computerized pharmacies in the study district. Information on all filled prescriptions
from January 1st 1991 onwards were available and included information on the product name, the
Anatomical Therapeutic Chemical code (ATC-code) of the World Health Organisation, the
dispensing date, the prescribed dosing regimen and the amount dispensed. More detailed
information on the methods of data collection and definitions of cardiac outcomes have been
previously described(4).
Statistical analysis
We performed a sensitivity analysis by exclusion of persons with prevalent heart failure and
myocardial infarction. Since we were interested in how COPD affects SCD in general terms, Cox
models for the hazard on SCD that treat other death as censored were perfectly valid.(5)
Nevertheless, with regard to the competing risk of non-SCD, we performed a sensitivity analysis
using the data augmentation method and unstratified model described by Lunn & McNeil(6) to
estimate the hazard ratio (HR) of SCD in comparison with non-SCD. Although it should be
mentioned that if the proportionality assumption is not satisfied, then the stratified Lunn-McNeil
model should be used, which is identical to the Cox cause-specific model.(7) Furthermore, since
we were also interested in the incidence of SCD, we estimated the cumulative incidence function
(CIF)(8) from the competing risk data and performed the Gray’s test for equality of CIFs.(9, 10).
The CIF is a summary curve, showing the cumulative event rates over time due to a particular
cause(8, 11). The Gray’s test is developed for the comparison of the cumulative incidence of
events among different groups(9). Follow-up time was determined as the time between study
entry (i.e. for subjects without COPD or with prevalent COPD) or incident COPD date (i.e. for
subjects with incident COPD) and death or end of study (January 1st 2011). This definition
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includes the time at risk for sudden cardiac death. However, we also performed a sensitivity
analysis adding the time between cohort entry and incident COPD to the control follow-up time.
A two-sided p-value below 0.05 was considered statistically significant. Statistical analyses were
performed using R Statistical Software (Foundation for Statistical Computing, Vienna, Austria)
and SPSS, version 20.0 (IBM Corp., Somers, NY, USA).
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SUPPLEMENT REFERENCES
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van Durme Y, Verhamme KMC, Aarnoudse A, Van Pottelberge GR, Hofman A,
Witteman JCM, Joos GF, Brusselle GG, Stricker BHC. C-Reactive Protein Levels, Haplotypes,
and the Risk of Incident Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med
2009; 179(5):375-382.
2.
Swedberg K, Cleland J, Dargie H, Drexler H, Follath F, Komajda M, Tavazzi L, Smiseth
OA, Gavazzi A, Haverich A, Hoes AW, Jaarsma T, Korewicki J, Levy S, Linde C, LopezSendon JL, Nieminen MS, Pierard L, Remme WJ, Task Force for the Diagnosis, Treatment of
Chronic Heart Failure of the European Society of Cardiology. Guidelines for the diagnosis and
treatment of chronic heart failure: executive summary (update 2005): The Task Force for the
Diagnosis and Treatment of Chronic Heart Failure of the European Society of Cardiology. Eur
Heart J 2005; 26(11):1115-1140.
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Leening MJG, Kavousi M, Heeringa J, van Rooij FJA, Verkroost-van Heemst J, Deckers
JW, Mattace-Raso FUS, Ziere G, Hofman A, Stricker BHC, Witteman JCM. Methods of data
collection and definitions of cardiac outcomes in the Rotterdam Study. Eur J Epidemiol 2012;
27(3):173-185.
4.
Leening MJ, Kavousi M, Heeringa J, van Rooij FJ, Verkroost-van Heemst J, Deckers
JW, Mattace-Raso FU, Ziere G, Hofman A, Stricker BH, Witteman JC. Methods of data
collection and definitions of cardiac outcomes in the Rotterdam Study. Eur J Epidemiol 2012;
27(3):173-185.
5.
Pintilie M. Competing risks: A practical perspective: Wiley; 2007.
6.
Lunn M, McNeil D. Applying Cox regression to competing risks. Biometrics 1995;
51(2):524-532.
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7.
Lim HJ, Zhang X, Dyck R, Osgood N. Methods of competing risks analysis of end-stage
renal disease and mortality among people with diabetes. Bmc Medical Research Methodology
2010; 10.
8.
Zhang MJ, Zhang X, Scheike TH. Modeling cumulative incidence function for competing
risks data. Expert Rev Clin Pharmacol 2008; 1(3):391-400.
9.
Gray RJ. A Class of K-Sample Tests for Comparing the Cumulative Incidence of a
Competing Risk. Annals of Statistics 1988; 16(3):1141-1154.
10.
Kim HT. Cumulative incidence in competing risks data and competing risks regression
analysis. Clin Cancer Res 2007; 13(2 Pt 1):559-565.
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Prentice RL, Kalbfleisch JD, Peterson AV, Jr., Flournoy N, Farewell VT, Breslow NE.
The analysis of failure times in the presence of competing risks. Biometrics 1978; 34(4):541-554.
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Table S1: Chronic obstructive pulmonary disease and the hazard on sudden cardiac death
according to the severity of airflow limitation. (n=5661)
Model adjusted for age & sex
Categorical,
all versus normal lung function
Mild COPD (GOLD I, n=393)
HR
95% CI
3.25
1.48-7.18
0.003
Moderate COPD (GOLD II, n=385)
3.31
1.52-7.22
0.003
Severe COPD (GOLD III, n=74)
3.76
0.86-16.43
0.079
P-value
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