Concurrent use of long-acting bronchodilators in COPD and the risk of adverse cardiovascular events

Data source

We used the Clinical Practice Research Datalink (CPRD), a primary care database from the UK that contains primary care medical records for over 10 million people enrolled from over 600 practices. Participating general practitioners were trained to record medical information, including demographic data, lifestyle factors and medical diagnoses, using the Read classification. Prescriptions are automatically transcribed using the UK Prescription Pricing Authority Dictionary. The CPRD can be linked for approximately half of the practices to the Hospital Episodes Statistics (HES) database, which provides hospitalisation information. The recorded information on drug exposures and diagnoses was validated and proven to be of high quality [14–16].

Study design

We first formed a base cohort of all new users of long-acting bronchodilators, either a LABA or tiotropium, from January 1, 2001 until August 31, 2012, with new use defined as a first prescription of either drug with none during the previous 2 years. Thus, all patients in this base cohort were required to have at least 2 years of up-to-standard medical history prior to the first cohort-defining prescription to allow the identification of new use. Patients initiating treatment with both bronchodilators on the same date were excluded. To increase the likelihood of a diagnosis of COPD, we only included patients who were 55 years of age or more on the date of this initial prescription. This also increased the representativeness of the study by including as many patients as possible, although we also performed an analysis using the 90% of patients who had a COPD diagnosis prior to or at the time of the initial long-acting bronchodilator.

The study cohorts were formed by identifying all subjects from the base cohort who subsequently received the other long-acting bronchodilator class as a second additional bronchodilator, defined as both bronchodilator prescriptions given simultaneously on the same day. To avoid confounding issues related to more severe patients being the first ones to be prescribed the newer bronchodilator on the market, in this case tiotropium, we only considered subjects who added the other bronchodilator at least 1 year after tiotropium was first used, namely September 25, 2002.

For each subject who was on a LABA and subsequently added tiotropium, we identified a propensity score-matched reference subject who also was on a LABA but remained on a LABA only at the time the subject added the tiotropium prescription, using a prevalent new-user design [17]. The potential reference subjects were selected from the corresponding exposure sets, namely from the base cohort among all subjects who were already on a LABA, who received a LABA prescription within a month of the date tiotropium was added, and who were in the base cohort for the same duration (±3 months) as the combination-exposed subjects. Thus, the time span between base cohort entry (monotherapy initiation) and study cohort entry (addition of the second bronchodilator or matched continuation) was inherently a matching covariate. To allow matching on the propensity to add tiotropium, we used the high-dimensional propensity score (HDPS) technique by identifying all available data (e.g. diagnoses, procedures and medications) in the one-year period prior to the date of the matched set and applying conditional logistic regression to estimate a combination treatment propensity score [18]. In addition to the 500 variables selected by HDPS, the propensity score model forced age, sex, exacerbation in the previous 30 days and presence of the outcome in the 2 years prior to the date of the matched set. Then, for each combination-exposed subject and starting chronologically with the first, we identified one reference subject from the list of potential subjects at that time point, matched on prior ICS use and on the closest propensity score.

An identical approach was used for the subjects who initiated treatment on tiotropium and added a LABA, for whom matched subjects were taken from those who were only on tiotropium at that time. The two cohorts were pooled to form the final study cohort. Subjects were followed up for outcome events occurring during the 1-year span after cohort entry, namely the date of the matched set defined by either the addition of a second bronchodilator or the continuation of a single bronchodilator, with follow-up ending at the earliest of the date of cardiovascular outcome, 1 year after cohort entry, the date of death, August 31, 2013, or the end of coverage in the practice, whichever occurred first.

Outcome events

For myocardial infarction, heart failure and stroke, we identified all subjects with a Read code recorded in the general practitioner (GP)'s diagnostic field for these conditions occurring during the year after cohort entry. The diagnostic codes and algorithms to identify these outcomes have been shown to be highly valid for these outcomes and have been used in several studies using the CPRD [19–25]. In particular, for heart failure, probable cases were defined as a diagnosis of heart failure with either death within 30 days or treatment with at least two medications among the classes ACE/ARB (angiotensin-converting enzyme inhibitors and angiotensin receptor blockers), diuretics and digitalis, whereas possible cases were defined as diagnosis of heart failure and either treatment with one or more medications among the ACE/ARB, diuretics and digitalis classes, or death between 30 and 90 days after diagnosis. For the outcome of arrhythmia, which cannot be based strictly on GP diagnoses, we used the subcohort of the study cohort members that can be linked to the HES database. Thus, arrhythmia was based on hospitalisation diagnoses with ICD-10 codes I46.x-I49.x, R00.0 and R00.1. These definitions from hospitalised data have been used in several studies involving COPD [26, 27].

Covariates

As the HDPS approach identifies the 500 most likely confounders, we list here the covariates of particular interest that we report and compare with respect to the balance between the two groups. These include age, sex, body mass index (BMI), smoking status and excessive alcohol consumption. Baseline comorbidity, measured in the baseline year prior to study cohort entry, used diagnoses for arrhythmia, cardiomegaly, atherosclerosis, anaemia, hypertension, congenital structural cardiovascular abnormalities, diabetes, thyroid disease, hyperlipidaemia, renal failure and pneumonia, as well as presence of the study outcomes. Additionally, all prescriptions for angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, β-blockers, thiazide diuretics, loop diuretics, antiarrhythmics, digoxin (digitalis), nitrates, statins, clopidogrel, aspirin, insulin, oral hypoglycaemics, nonsteroidal anti-inflammatory drugs, opioid analgesics and acetaminophen given during the 1 year baseline period prior to study cohort entry were identified. In addition, prescriptions for drugs hypothesised to lengthen the QT interval, such as macrolides, antidepressants, cisapride, antipsychotics and so on, were identified [28].

Baseline COPD severity was measured by the number of prescriptions for short-acting β-agonists and anticholinergics, methylxanthines, as well as inhaled corticosteroids (whether alone or combined with the LABA) and oral corticosteroids used during the baseline year prior to study cohort entry. Baseline inhaled corticosteroid use was defined prior to the day of study cohort entry and thus did not include the LABA prescription used to define cohort entry, which may be combined with an inhaled corticosteroid. A new prescription for prednisolone or a physician diagnosis in the 30 days prior to study cohort entry was used to identify recent COPD exacerbations [29].

Data analysis

The crude 1 year cumulative incidence and rate of the outcomes was estimated for the two long-acting bronchodilator groups. The comparative analyses used a time-dependent Cox proportional hazard regression model to perform an as-treated analysis that assesses the effect of current use of the combination or monotherapy exposure on the outcome occurrence. Thus, for the as-treated analysis, patients who switched to the other group during follow-up were censored at that time. Current use was defined as exposure to the initial combination or monotherapy within the 60 day period of the date defined by the risk set of the Cox model. This model included patient characteristics such as age in 10 year categories and sex, as well as the decile of propensity score for each patient obtained from the HDPS model for matching purposes and year of cohort entry. We also adjusted for the use of ipratropium in the year preceding study cohort entry, because an imbalance was observed after propensity score matching and we adjusted for the time since initiation of treatment with the long-acting bronchodilator, even if this was a matching factor because the matching was done within ±3 months.

Several sensitivity analyses were performed. First, to assess potential reverse causality bias from the as-treated analyses, we also used an intention-to-treat (ITT) approach, which compares combination to monotherapy with respect to the outcome occurrence in the subsequent year, irrespective of changes in treatment during this time, using a time-fixed Cox proportional hazard regression model. Second, analyses were stratified by the order that the drug was added, namely adding tiotropium to the initiated LABA and vice versa, a recorded diagnosis of COPD, prior use of ICS and by the presence of a recent COPD exacerbation in the 30 days prior to study cohort entry. Third, analyses were restricted to subjects with no presence of the outcome at baseline and repeated using the probable heart failure definition only. Fourth, the 60 day period used to define current use in the as-treated analyses was repeated with 30 and 90 day periods. Also, to verify the potential protopathic bias [30] from the possibility that a very recent prescription for a bronchodilator may have occurred in relation to dyspnoea related to early stages of myocardial dysfunction rather than a worsening of COPD, we repeated the as-treated analysis after eliminating events occurring in the first 30 and 90 days of follow-up. We also repeated the analyses allowing exposure to the combination during follow-up to be defined as two prescriptions within ±3 days of each other. Lastly, analyses were repeated with a maximum difference in propensity score distance of 0.05. All analyses were conducted using SAS version 9.4.

The study protocol was approved by the Independent Scientific Advisory Committee of the CPRD (Protocol 13_093RA) and the Ethics Committee of the Jewish General Hospital (JGH Protocol #13-096), Montreal, QC, Canada.