Cardiovascular Drug Use for Prevention and Treatment of CHD
Cardiovascular Drug Use for Prevention and Treatment of CHD
We conducted a population-based analysis on the PHARMO database network, a record linkage system containing drug-dispensing records from community and hospital pharmacies linked with hospital discharge records, as described in detail previously. Cardiovascular drug dispensings between 1998 and 2010 were identified in a dynamic cohort of over 1.4 million residents aged 25 years and over in the Netherlands. Members of a dynamic cohort can leave or can be added over time to the cohort. In our study, individuals could have moved in or moved out of the PHARMO area, could have died, could have turned 25 years of age, or could have been institutionalized. These aspects all lead to inclusion or exclusion out of the study population every year. In order to estimate population-based treatment uptakes of cardiovascular drug use, we used cross-sectional samples of each year, drawn from the number of inhabitants of the well-defined 48 geographical areas of the PHARMO area. The number of inhabitants over 25 years in the PHARMO area increased from 1.0 million in 1998 to 1.2 million in 2010. In the total study period, data from more than 1.4 million unique individuals were analysed. The inhabitants of the PHARMO population are representative for the total Dutch population of that year. The clustering of community pharmacies within the PHARMO areas resulted in drug-dispensing information that contained >95% of all prescriptions dispensed to all the community-dwelling residents.
Drug-dispensing records from hospital pharmacies were linked to hospital discharge records of the same patient from the national hospital discharge register. Hospital discharge records included information concerning primary and secondary diagnoses, performed procedures, and dates of hospital admission and discharge. Hospital discharge diagnoses were coded according to the International Classification of Diseases version 9 (ICD-9). The drug-dispensing records from hospital and community pharmacies contained information concerning the dispensed drug, dispensing date, and the prescription length. All prescription drugs were coded according to the Anatomical Therapeutic Chemical (ATC) classification system. The cardiovascular drug classes of interest were ATC group C (cardiovascular drugs) and group B01 (antithrombotic agents). In the in-hospital treatment of acute coronary syndromes (ACSs), antithrombotics included the in-hospital treatment with the anticoagulant heparin, additional to the antiplatelets aspirin and thienopyridines. In the secondary prevention setting, antithrombotics refers to the use of oral anticoagulants or antiplatelet drugs from community pharmacies (for specification of ATC codes, see Supplementary material online, File 1).
We studied the use of blood pressure-lowering drugs (beta-blockers, ACE-Is/ARBs, CCBs, and diuretics) and lipid-lowering drugs (statins and others) in the eligible population for primary prevention by a previously described method. In brief, we used information on filled prescriptions from community pharmacies to estimate drug use by a point prevalence at one time point in each index year (for primary prevention at 1 October). An individual was defined as user if this time point fell between the dispensing date and theoretical end date of a prescription. The calculated theoretical duration of a prescription was multiplied with 1.1 to correct for early and irregular drug collection from the pharmacy as detailed previously.
To distinguish individuals with established cardiovascular disease from those in the primary prevention population, persons with a cardiovascular-related hospital admission within 5 years and 9 months prior to 1 October in the index year (ICD-9 401–459 or an admission with PCI, CABG, or diagnostic cardiac catheterization performed), or those that were on nitrates (C01DA), digitalis glycosides (C01AA), or antithrombotic drugs (B01) in the index year, were excluded from the primary prevention population. The latter were considered as asymptomatic individuals. The primary prevention population was defined from the total dynamic PHARMO cohort each year separately. We had data available from January 1998 to December 2010. Since 5 years were needed to make sure that no hospital admission for cardiovascular disease had taken place to identify asymptomatic individuals, time trends in cardiovascular drug use for primary prevention were based on the time period between 2003 and 2010.
We studied cardiovascular drug use during hospital stay in individuals from the dynamic PHARMO cohort admitted to the hospital for an acute myocardial infarction (AMI, ICD-9 code 410) and for unstable angina (UA, ICD-9 code 411 or 413). These individuals were identified by linking hospital discharge and hospital pharmacy records. Primary discharge diagnoses were used to select AMI and UA hospital admissions. Recurrent admissions within 3 months in the same individual were excluded. To ensure enrolment status, individuals were required to have at least one filled prescription from the hospital pharmacy during their hospitalization. Drug use was defined as at least one prescription within a drug class during hospital stay. Drugs evaluated were antithrombotic drugs (heparin, aspirin, thienopyridines), vasodilators, blood pressure-lowering drugs (beta-blockers, CCBs, ACE-Is/ARBs, diuretics), and lipid-lowering drugs. Time trends in in-hospital treatment were studied for the period between 1998 and 2010.
We followed closed cohorts of individuals admitted for ACSs (i.e. AMI or UA) in 1998, 2003, and 2007 with respect to drug use 3 months (T3), 12 months (T12), and 36 months (T36) after the date of hospital discharge (T0). These time points were specifically chosen to make optimal use of the available data (1998–2010), enabling us to study time trends in drug use between the beginning, middle, and end of the study period, and at shorter and longer intervals from hospital discharge. The denominator was based on patients who were alive at hospital discharge. Individuals were excluded from the denominator at their disappearance from the database, which could be due to moving out of the PHARMO area, death, or institutionalization. Information on drug dispensings at T3, T12, and T36 was obtained from community pharmacy data and presented at cohort level. We used the same definition of drug use as in primary prevention, with T3, T12, and T36 as time points for the estimation of drug use in secondary prevention of CHD.
Treatment uptakes of cardiovascular drugs were presented as the percentage of users of the different drug classes within the patient groups and population groups, and plotted using yearly intervals. In secondary prevention, we analysed combination therapy by the number of drugs that was used from the four preventive drug classes (i) antithrombotics, (ii) lipid-lowering drugs, (iii) beta-blockers, and (iv) other blood pressure-lowering drugs than beta-blockers (ACE-Is, ARBS, CCBs, or diuretics). We age-standardized treatment uptakes for primary prevention to the asymptomatic population of 2010 aged 25 years and over, using a direct method with 10-year age groups. Treatment uptakes during in-hospital treatment and secondary prevention were standardized to the age distribution of the ACS population in 2010.
Differences in the use of cardiovascular drugs by age, gender, and over time were evaluated by using generalized estimating equation (GEE) models. These models were used to account for the correlation in treatment uptakes over time within individuals. We adjusted for differences in age, gender, and calendar year and in secondary prevention and in-hospital treatment also for the diagnosis of the hospital admission (AMI or UA). Interaction terms between calendar year and age or gender were added to the models to assess the presence of changes in age and gender differences over time. All analyses were performed using PROC GENMOD in SAS Enterprise Guide version 4.3 (SAS Institute, Cary, NC, USA).
Methods
Data Source
We conducted a population-based analysis on the PHARMO database network, a record linkage system containing drug-dispensing records from community and hospital pharmacies linked with hospital discharge records, as described in detail previously. Cardiovascular drug dispensings between 1998 and 2010 were identified in a dynamic cohort of over 1.4 million residents aged 25 years and over in the Netherlands. Members of a dynamic cohort can leave or can be added over time to the cohort. In our study, individuals could have moved in or moved out of the PHARMO area, could have died, could have turned 25 years of age, or could have been institutionalized. These aspects all lead to inclusion or exclusion out of the study population every year. In order to estimate population-based treatment uptakes of cardiovascular drug use, we used cross-sectional samples of each year, drawn from the number of inhabitants of the well-defined 48 geographical areas of the PHARMO area. The number of inhabitants over 25 years in the PHARMO area increased from 1.0 million in 1998 to 1.2 million in 2010. In the total study period, data from more than 1.4 million unique individuals were analysed. The inhabitants of the PHARMO population are representative for the total Dutch population of that year. The clustering of community pharmacies within the PHARMO areas resulted in drug-dispensing information that contained >95% of all prescriptions dispensed to all the community-dwelling residents.
Drug-dispensing records from hospital pharmacies were linked to hospital discharge records of the same patient from the national hospital discharge register. Hospital discharge records included information concerning primary and secondary diagnoses, performed procedures, and dates of hospital admission and discharge. Hospital discharge diagnoses were coded according to the International Classification of Diseases version 9 (ICD-9). The drug-dispensing records from hospital and community pharmacies contained information concerning the dispensed drug, dispensing date, and the prescription length. All prescription drugs were coded according to the Anatomical Therapeutic Chemical (ATC) classification system. The cardiovascular drug classes of interest were ATC group C (cardiovascular drugs) and group B01 (antithrombotic agents). In the in-hospital treatment of acute coronary syndromes (ACSs), antithrombotics included the in-hospital treatment with the anticoagulant heparin, additional to the antiplatelets aspirin and thienopyridines. In the secondary prevention setting, antithrombotics refers to the use of oral anticoagulants or antiplatelet drugs from community pharmacies (for specification of ATC codes, see Supplementary material online, File 1).
Primary Prevention
We studied the use of blood pressure-lowering drugs (beta-blockers, ACE-Is/ARBs, CCBs, and diuretics) and lipid-lowering drugs (statins and others) in the eligible population for primary prevention by a previously described method. In brief, we used information on filled prescriptions from community pharmacies to estimate drug use by a point prevalence at one time point in each index year (for primary prevention at 1 October). An individual was defined as user if this time point fell between the dispensing date and theoretical end date of a prescription. The calculated theoretical duration of a prescription was multiplied with 1.1 to correct for early and irregular drug collection from the pharmacy as detailed previously.
To distinguish individuals with established cardiovascular disease from those in the primary prevention population, persons with a cardiovascular-related hospital admission within 5 years and 9 months prior to 1 October in the index year (ICD-9 401–459 or an admission with PCI, CABG, or diagnostic cardiac catheterization performed), or those that were on nitrates (C01DA), digitalis glycosides (C01AA), or antithrombotic drugs (B01) in the index year, were excluded from the primary prevention population. The latter were considered as asymptomatic individuals. The primary prevention population was defined from the total dynamic PHARMO cohort each year separately. We had data available from January 1998 to December 2010. Since 5 years were needed to make sure that no hospital admission for cardiovascular disease had taken place to identify asymptomatic individuals, time trends in cardiovascular drug use for primary prevention were based on the time period between 2003 and 2010.
In-hospital Treatment
We studied cardiovascular drug use during hospital stay in individuals from the dynamic PHARMO cohort admitted to the hospital for an acute myocardial infarction (AMI, ICD-9 code 410) and for unstable angina (UA, ICD-9 code 411 or 413). These individuals were identified by linking hospital discharge and hospital pharmacy records. Primary discharge diagnoses were used to select AMI and UA hospital admissions. Recurrent admissions within 3 months in the same individual were excluded. To ensure enrolment status, individuals were required to have at least one filled prescription from the hospital pharmacy during their hospitalization. Drug use was defined as at least one prescription within a drug class during hospital stay. Drugs evaluated were antithrombotic drugs (heparin, aspirin, thienopyridines), vasodilators, blood pressure-lowering drugs (beta-blockers, CCBs, ACE-Is/ARBs, diuretics), and lipid-lowering drugs. Time trends in in-hospital treatment were studied for the period between 1998 and 2010.
Secondary Prevention
We followed closed cohorts of individuals admitted for ACSs (i.e. AMI or UA) in 1998, 2003, and 2007 with respect to drug use 3 months (T3), 12 months (T12), and 36 months (T36) after the date of hospital discharge (T0). These time points were specifically chosen to make optimal use of the available data (1998–2010), enabling us to study time trends in drug use between the beginning, middle, and end of the study period, and at shorter and longer intervals from hospital discharge. The denominator was based on patients who were alive at hospital discharge. Individuals were excluded from the denominator at their disappearance from the database, which could be due to moving out of the PHARMO area, death, or institutionalization. Information on drug dispensings at T3, T12, and T36 was obtained from community pharmacy data and presented at cohort level. We used the same definition of drug use as in primary prevention, with T3, T12, and T36 as time points for the estimation of drug use in secondary prevention of CHD.
Data Analyses
Treatment uptakes of cardiovascular drugs were presented as the percentage of users of the different drug classes within the patient groups and population groups, and plotted using yearly intervals. In secondary prevention, we analysed combination therapy by the number of drugs that was used from the four preventive drug classes (i) antithrombotics, (ii) lipid-lowering drugs, (iii) beta-blockers, and (iv) other blood pressure-lowering drugs than beta-blockers (ACE-Is, ARBS, CCBs, or diuretics). We age-standardized treatment uptakes for primary prevention to the asymptomatic population of 2010 aged 25 years and over, using a direct method with 10-year age groups. Treatment uptakes during in-hospital treatment and secondary prevention were standardized to the age distribution of the ACS population in 2010.
Differences in the use of cardiovascular drugs by age, gender, and over time were evaluated by using generalized estimating equation (GEE) models. These models were used to account for the correlation in treatment uptakes over time within individuals. We adjusted for differences in age, gender, and calendar year and in secondary prevention and in-hospital treatment also for the diagnosis of the hospital admission (AMI or UA). Interaction terms between calendar year and age or gender were added to the models to assess the presence of changes in age and gender differences over time. All analyses were performed using PROC GENMOD in SAS Enterprise Guide version 4.3 (SAS Institute, Cary, NC, USA).
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