Dronedarone Amiodarone Comparison Essay

Dronedarone (Multaq, Sanofi-aventis) is less effective than amiodarone in fighting AF but causes fewer adverse effects, according to a new study.

“The critical question for clinical practice,” the study authors write, is whether the safety benefits “justify a retreat from the moderate efficacy afforded by amiodarone.”

In a systematic overview of randomized trials published in the Journal of the American College of Cardiology, Piccini and colleagues at Duke University identified 4 placebo-controlled trials of dronedarone, 4 placebo-controlled trials of amiodarone, and 1 trial of dronedarone versus amiodarone. For every 1,000 patients treated with dronedarone instead of amiodarone, the Duke investigators calculated there would be about 228 more AF recurrences, 9.6 fewer deaths, and 62 fewer adverse events requiring drug discontinuation.

Clinicians are faced with a difficult dilemma, write Paul Chan and colleagues in an accompany editorial. Amiodarone in AF has not been well studied and does not have an approved FDA indication for AF, yet more than two millions amiodarone prescriptions are filled each year for AF, despite its serious and well known side effect profile.

Chan et al note that in the absence of adequately powered and designed randomized trials comparing amiodarone and dronedarone, the Duke analysis should be considered “hypothesis generating.”

In the meantime,” they write, “clinicians will need to balance whether the use of dronedarone, a less efficacious but possibly safer antiarrhythmic drug than amiodarone (in patients without reduced ejection fraction), is justified for their patients with AF.”

Here is recent CardioBrief coverage of dronedarone:


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A variety of anti-arrhythmic drugs (AADs) are used to suppress arrhythmias encountered in clinical practice1. AADs exert their pharmacologic effect by blocking ion channel currents in myocardial cells. Specifically, class III AADs block the delayed potassium rectifier current (IKr) and prolong phase 3 repolarization of the individual cell action potential. While this mechanism of action is aimed at suppressing arrhythmias, it can also predispose to other, potentially more dangerous ones. AADs also have important non-cardiac side effects. Despite being generally safe and well tolerated in the majority of patients, AADs demonstrate various degrees of efficacy in controlling arrhythmias in the clinical setting. The clinical use of AADs has been somewhat disappointing due to limited effectiveness and the occurrence of cardiac and systemic side effects.

Dofetilide is a class III AAD in clinical use for over ten years for the treatment of atrial arrhythmias. It is especially useful in patients with structural heart disease, such as coronary artery disease and congestive heart failure2. This is supported by clinical trials comparing its efficacy and safety to placebo3. Initiation of dofetilide requires hospitalization to ensure rigorous observation and monitoring for long QT, Torsade de Pointes, or other side effects through the first six doses. Patients are then followed up on a routine basis where they are monitored for drug efficacy and side effects.

Dronedarone is an additional class III AAD used for the treatment of atrial arrhythmias. It is a non-iodinated derivative of amiodarone, and it was originally believed to have a more favorable side effect profile compared to the parent drug. Dronedarone’s original approval was based on clinical trials demonstrating increased efficacy compared to placebo4,5. In the European and Australian-American-African trials EURIDIS and ADONIS respectively5, dronedarone significantly prolonged the time to first recurrence in patients with paroxysmal and persistent atrial fibrillation and flutter. However, one placebo-controlled clinical trial, referred to as the Permanent Atrial Fibrillation Outcome Study Using Dronedarone on Top of Standard Therapy (PALLAS), ended prematurely due to safety reasons, as the dronedarone arm showed significantly higher rates of major cardiovascular events6. A recent meta-analysis, comprised of seven placebo-controlled clinical trials, including the PALLAS trial, was implemented to better understand why the PALLAS trial’s findings conflicted with other similar investigations. This analysis reported significant heterogeneity of dronedarone treatment effects and concluded that permanent AF may be the most important predictor of harmful effects potentially caused by dronedarone7. Furthermore, a recent subgroup analysis was performed using the PALLAS trial, and investigators observed a harmful interaction between dronedarone and digoxin in patients with permanent AF, which they felt was partly responsible for the higher death rate observed in the original clinical trial8.

Currently, dronedarone is restricted or contraindicated in patients with symptomatic heart failure with New York Heart Association (NYHA) class II or III symptoms, recent heart failure hospitalization or left ventricular ejection fraction <40%, largely due to the results of the PALLAS trial9. However, dronedarone may still be an important treatment option for clinicians to consider when treating patients that do not meet these criteria and are subsequently experiencing paroxysmal or persistent AF. Strengthening the available evidence could potentially reduce the trial and error process clinicians maybe be following in prescribing AADs.

To our knowledge only two observational studies have been implemented to compare the efficacy and safety of dronedarone to other anti-arrhythmic drugs10,11. However, only one of these studies was able to directly compare dronedarone and dofetilide. This study suggested the efficacy of dronedarone and dofetilide to be similar, with dronedarone being associated with a great risk of cardiac-related admissions. This evidence could benefit from replication, as the study was restricted to a patient cohort generated from a single university medical center. Thus, further investigation is warranted in improving the generalizability of such findings, further characterizing dronedarone treatment effects in a ‘real world’ clinical setting. In addition, further investigation may also assist in helping us to better understand why the PALLAS trial observed such serious adverse drug events.

Therefore, the goal of this study was to utilize a historical cohort to compare the effectiveness of dronedarone and dofetilide in maintaining normal rhythm. The results of the PALLAS trial were not known during the study period of our analysis and could not have influenced the recommendation or choice of anti-arrhythmic drugs. This study is comprised of a group of patients with comparable clinical characteristics in a large single center university hospital setting. We also compared the side effect profile and discontinuation rates of the two agents.


Design and setting

The University of Utah institutional review board (IRB) approved this study (IRB#39735) and a waiver of informed consent was granted. We employed a historical cohort design using an intention-to-treat analysis designed to compare rates of arrhythmia recurrence and side-effects between dronedarone and dofetilide. Patients dispensed dronedarone or dofetilide were identified from the University of Utah’s hospital pharmacy database from January 2003 to 2010. Clinical pharmacists reviewed all patient charts using a structured template to extract relevant clinical variables including patient characteristics, clinical course, and response to drug therapy. Cohort entry was defined as the time of drug initiation. Patients initiated on either dronedarone or dofetilide that met inclusion criteria were considered on treatment for the drug they were initiated on until the end of follow-up or if they experienced an adverse event that required discontinuation. Inclusion criteria included initiation and long term follow up for drug monitoring at the University of Utah. The time window used to compare the outcomes of atrial arrhythmia recurrence, side effects, and discontinuation rates was restricted to the first year of drug treatment for both groups. Patients were excluded from the analysis if they did not receive their long-term follow-up care at the University of Utah. They were also excluded if they failed to achieve sinus rhythm or experienced significant adverse events leading to drug discontinuation within the first six doses of the medication.


The primary outcome was arrhythmia recurrence within the first year of treatment. Secondary outcomes included a comparison of side effects and drug discontinuation rates. Each patient’s experience on the drug was tracked through progress notes entered into the electronic medical records system. When arrhythmia recurrence was documented in progress notes, the patient was classified as having an event and censored from the recurrence analysis. Patients who did not achieve the primary outcome under drug exposure were censored at the end of the one-year follow-up period. Patients who developed a side effect from drug therapy but continued treatment without arrhythmia recurrence were not censored until the end of the one-year follow-up period. Patients who discontinued therapy due to adverse events were censored at the time of the adverse event.

Covariate selection

Covariates included in the analysis were selected based on patients’ clinical characteristics and comorbidities. These included patient age, gender, prior diagnoses of diabetes, hypertension, coronary artery disease, kidney function, congestive heart failure, concomitant drug treatment, and left ventricular ejection fraction. In addition, arrhythmia history and severity were included with the type of AF (paroxysmal or persistent), prior treatment with other AADs, or catheter ablation.

Statistical analyses

Descriptive statistics were calculated and chi-square or t-tests for equality of means between treatment groups were computed before and after matching. One-to-one nearest neighbor propensity score matching was used to balance potential confounders between treatment groups. An analysis using propensity scores contains two steps: 1) Estimation of the probability of being treated (propensity score) using probit regression, and 2) Incorporation of the propensity score as a matching variable in the outcome model. All statistical analyses, including propensity scores and 1:1 nearest neighbor matching were computed using STATA 11 (STATA corp, College Station, Tx)12.

Propensity scores are typically used to model the probability of being treated, and for this reason, they are used to calculate the average treatment effect in the treated. Since we are comparing two treatments, we modeled the probability of being treated with dronedarone – the newer agent being compared to the older therapy, dofetilide. In propensity score matching, it has been argued that inference should be restricted to areas where propensity scores overlap between treatment groups. For this reason, results are reported with and without imposition of common support (Figure 1). When the common support option is used, treatment observations (in this case dronedarone users) whose propensity score is higher than the maximum or less than the minimum propensity score of dofetilide users are dropped. Crude, covariate adjusted, and propensity score matched Cox-Proportional Hazard models were used to estimate hazard ratios for the difference in recurrence rates between treatments. Missing values for continuous measures were imputed using individual-level regression equations. Analyses were performed with and without imputed values and leaving the variables out of the equations all together. The hazard ratios; nevertheless, were not impacted in any meaningful way, and for this reason, we reported analyses with imputed values.

Figure 1. Distribution of propensity scores and illustration of common support.


Patient characteristics

During the period of January 2003 to September 2009, 162 patients were observed to have initiated dofetilide, while 71 patients were observed to have initiated dronedarone between September 2009 and September 2010. Direct comparison of baseline characteristics between the two drug groups described in Table 1 showed more females in the dronedarone group (40.9% vs. 25.9%, p=0.02). Dronedarone patients also had an older average age (68±12 vs. 62±13; p=0.001), a higher left ventricular ejection fraction (58±12 vs. 47±15; p<0.001), and were more likely to have undergone catheter ablation (53.5% vs. 24.1%; p<0.001). By contrast, a higher prevalence of congestive heart failure was seen in the dofetilide group (42.6% vs. 19.7%; p<0.001). An increased use of concomitant drug therapy was also observed in the dofetilide group with a higher use of beta-blockers, angiotensin-converting-enzyme inhibitors, aldosterone antagonists, and digoxin. The proportion of patients with paroxysmal atrial fibrillation was similar between the two groups (43.6% vs. 48.9%; p=0.48).

Table 1. Baseline characteristics of treatment groups before restriction to inclusion criteria.

P value
Age (yrs)62±1368±120.001
Gender (%female)25.9%40.9%0.02
Coronary Disease32.1%43.7%0.20
Congestive heart failure42.6%19.7%0.003
LV ejection fraction47±1558±12<0.001
Serum Creatinine1.04±0.241.00±0.270.27
Prior AAD43.8%49.3%0.44
Paroxysmal AF (%)43.6%48.9%0.48
Prior ablation24.1%53.5%<0.01
Beta blockers61.1%56.5%0.04
Calcium channel
Aldosterone antagonists6.8%12.7%0.004

Acute effectiveness and side effects

Patients initiated on either drug had to achieve normal sinus rhythm in order to be maintained on long-term treatment and be included in the evaluation of recurrence. Sinus rhythm was present upon drug initiation in 70 dofetilide patients (43.2%) compared to 37 dronedarone patients (55.2%; p=0.09). Forty-five patients (27.8%) converted to sinus rhythm with dofetilide loading compared to 15 dronedarone patients (21.3%; p=0.32). Direct current cardioversion was used to achieve sinus rhythm, when drug loading failed to achieve this, in 19 dofetilide patients (11.7%) compared to 7 dronedarone patients (9.9%; p=0.67). In total, sinus rhythm was achieved in 134 dofetilide patients (82.7% of initial cohort) and 59 dronedarone patients (83.1% of initial cohort; p=0.94). In addition, if patients developed significant side effects upon drug initiation, the drugs were discontinued and not used for long-term arrhythmia suppression. Gastrointestinal side effects were significantly higher in the dronedarone group (11.3% vs. 1.9%; p<0.01) while QT prolongation was significantly increased in the dofetilide group (13% vs. 1.4%; p<0.001).

Long-term effectiveness

Adequate follow-up information was available on 127 of 162 patients in the dofetilide group, and 59 of 71 patients treated in the dronedarone group. The average number of office visits during the first year of drug treatment was 4.5±1.2 for dofetilide patients compared to 4.2±1.7 for dronedarone patients (p=0.17). Fifty-nine patients (46.5%) experienced recurrence in the dofetilide group within the first year of treatment compared to 42 patients (71.2%) of dronedarone patients (Figure 2). A Kaplan Meier survival curve showing the difference in arrhythmia recurrence over the first year of treatment visually illustrates the difference in recurrence rates between dronedarone and dofetilide (Figure 3). Recurrence rates per 1000-days are reported in Table 2. A Cox proportional hazard model with the treatment drug assignment as the predictor variable was used to compare the two agents (Table 3). The hazard for one-year recurrence with dronedarone was 2.7 (95% CI: 1.79, 3.99; p-value<0.01) times larger than the hazard for dofetilide. The findings for the traditional covariate-adjusted model were similar, where the hazard ratio was 2.9 (95% CI: 1.74, 4.88; p-value<0.001).

Figure 2. Diagram of patients included in the study illustrating initial and long-term effectiveness and discontinuation.

Figure 3. Difference in arrhythmia recurrence over the first year of treatment between dronedarone and dofetilide.

Table 2. Arrhythmia recurrence rates per 1000-days.

Patients with
Time to
Incident rate0.00210.0063
Incident per
1000 days

Table 3. Cox Proportional Hazard ratios comparing recurrence rates between dronedarone and dofetilide.

PSi matched,
No CSk
PSi matched,

Propensity score matching was also used to adjust for potential confounders. As seen in Supplementary material Table 1, significant differences existed in baseline characteristics between the 127 dofetilide and 59 dronedarone patients. The matching procedures were able to balance these covariates. This table also presents post-matching means and p-values when matches were restricted to regions of common support or not. The propensity score matched survival models produced similar hazard ratios to the crude and standard regression approaches. Shown in Table 3, the hazard for one-year recurrence in the dronedarone group was 2.9 (95% CI: 1.78, 4.84; p-value<0.00) times larger than the hazard for the dofetilide group when matching was not restricted to areas of common support and 2.4 (95% CI: 1.44, 4.07; p-value<0.00), when matching was restricted to areas of common support.

Drug tolerability and discontinuation

During long-term follow-up, drug discontinuation due to concern with side effects was observed significantly more frequently in dofetilide patients compared to dronedarone patients (31 patients (24.4%) vs. 5 patients (8.5%); p<0.01). QT interval prolongation and ventricular arrhythmias (ventricular premature beats, sustained, and non-sustained ventricular tachycardia) were the most frequent causes of drug discontinuation in the dofetilide group (16 patients (10.2%), compared to 2 patients (3.4%) in the dronedarone group (p=0.11)). One patient in the dronedarone group demonstrated polymorphic ventricular tachycardia suggesting Torsade de Pointes. Gastrointestinal side effects were more frequent in the dronedarone group (6 patients (10.2%)) compared to the dofetilide group (2 patients (1.5%); p=0.03).


Our study compares the effectiveness and side effect profile of two class III anti- arrhythmic agents dronedarone and dofetilide. We demonstrate that dronedarone is associated with a significantly higher arrhythmia recurrence rate compared to dofetilide after one year of usage. However, we observed dofetilide to be associated with a significantly higher rate of serious side effects, specifically QT interval prolongation and ventricular arrhythmia.

Rational for observational design

The ideal way to compare the efficacy and tolerability of these two agents is a prospective randomized controlled trial, where all clinical covariates would be balanced through randomization and any patient would have an equal probability of being assigned to receive one of the two agents. The majority of current literature that has examined the efficacy and tolerability of dronedarone are placebo-controlled clinical trials. Due to the premature ending of the PALLAS trial, coupled with difficulties in the patient enrollment process surrounding cost and monitored care, an observational study design utilizing historical data is a reasonable and ethically appropriate alternative in comparing these agents. In addition, such a design can better reflect treatment effects that may occur in a ‘real world’ clinical setting, as clinical trials are performed in a highly controlled environment, often comprised of choice patient candidates.

Current evidence comparisons

Our findings do not fully reflect the findings from the aforementioned University of Pittsburgh Medical Center (UPMC) observational investigation. This may be in part due to the fact that our measures of drug tolerability and safety differed. In addition, our sample sizes were not comparable and we did not examine multiple AADs, such as amiodarone and sotalol. Our lack of comparisons and subsequent smaller sample sizes are two notable limitations of our design. However, some may argue that UPMC design may be susceptible to chance statistical associations due to the multiple comparisons being made in their multivariate analyses. Furthermore, we attempted to handle statistical differences in baseline patient characteristics differently than the UPMC study: by means of the nearest neighbor one-to-one propensity score, which assisted us in reducing the effects of potential selection biases.

Our study shows that dofetilide is more effective than dronedarone in preventing atrial arrhythmia recurrence in a ‘real world’ clinical setting. The probability of maintaining sinus rhythm with dofetilide at one year was 53.5% in our cohort. This is comparable to the reported probability of around 60% at 2 years in the DIAMOND-CHF trial, which successfully studied patients with congestive heart failure, in addition to their atrial fibrillation. Our rate of atrial fibrillation recurrence in the dronedarone group was comparable to that observed in the DIONYSOS trial [71.2% (n=71) vs. 63.5% (n=249); two sample test of proportions p=0.18]13. On the contrary, the University of Pittsburgh Medical Center (UPMC) retrospective cohort analysis reported dofetilide and dronedarone to have similar efficacy10. It is important to note that the DIONYSOS study findings are also in agreement with a portion of the findings from the UPMC study, suggesting amiodarone to be superior to dronedarone in preventing arrhythmia recurrence.

We also have demonstrated that dronedarone is better tolerated than dofetilide, which would appear to be contrary to what the PALLAS trial would suggest. This may in part be due to the multiple differences in baseline characteristics between patients in the PALLAS trial and those in our analysis, most notably in age, gender, and heart failure status. Moreover, unlike the PALLAS trial, none of our patients had permanent AF when drug therapy was initiated. Furthermore, despite the higher incidence of gastrointestinal side effects observed in our dronedarone group, this did not lead to higher rates of discontinuation. In our particular cohort, dronedarone was most likely continued because prescribing providers at the time were less concerned about life threatening side effects with this agent. Ventricular arrhythmias associated with long-term use of dofetilide were estimated at 10.2%, which is very similar to the rate observed in the DIAMOND-CHF trial (7.0%, including ventricular fibrillation, Torsade de Pointes, monomorphic, and polymorphic ventricular tachycardia). Side effects associated with dofetilide, specifically QT interval prolongation and subsequent pro-arrhythmia, led to a higher rate of drug discontinuation.


The findings in our study fill an important gap in the medical literature and demonstrate the comparative effectiveness of dronedarone to anti-arrhythmic agents other than amiodarone using observational data. Amiodarone is known as the most effective agent available, but other agents are often needed when long-term amiodarone use leads to subsequent side effects13,14. Furthermore, these findings suggest that dronedarone may actually be a well-tolerated treatment regimen for those with paroxysmal or persistent AF, after normal sinus rhythm has been achieved. However, clinicians should take into consideration patient-specific characteristics in order to reduce the risk of adverse events and complications. Despite the relatively small sample size of patients included in our study, our results are robust and provide important clinical evidence that will aid providers in managing patients with atrial fibrillation. Randomized prospective trials designed to compare the two agents may be difficult to conduct at this time and further observational studies, possibly from multiple centers, will continue to strengthen the evidence generated from this study.

Data availability

Raw datasets are not available due to the regulations surrounding patient data; University of Utah IRB approval and agreement to all related data use policies is required. This data can be obtained by contacting the authors, University of Utah IRB, and Department of Internal Medicine, with the University of Utah. Instructions for applying for IRB approval are available on the following University of Utah ERICA website (http://irb.utah.edu/guidelines/erica-assistance/access-instructions.php). An individual must first obtain a University of Utah ID (uNID) number as outlined and instructed on the ERICA website. The Department of Internal Medicine, within the University of Utah, will then approve the request for issuing an individual with a uNID. Once a uNID is obtained, the individual can then create a UU IRB ERICA account. Upon completion of self-registering in ERICA, the individual can be granted access to the study and de-identified data via the University of Utah IRB number that can be obtained from the authors.

Author contributions

NA conceived the study, carried out the research, and prepared initial drafts of the manuscript. FB assisted in designing the study, provided critical review, and participated in editing the manuscript. MG and DS assisted with the data collection, provided critical review, and participated in editing the manuscript. ZB polished initial manuscript drafts, added critical epidemiologic review, and prepared the manuscript for submission. BS provided oversight and critical review of the study design prior to implementation, assisted in carrying out the research and analysis, and participated in drafting sections of the manuscript relevant to his expertise.

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

Supplementary material

Table 1. The distribution of baseline covariates before and after 1:1 nearest neighbor matching.

The distributions have been summarized with and without restricting matching to areas of common support.

VariableMeanP value
No Common
No Common


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