A Study of the Efficacy and Safety of Vernakalant Hydrochloride (MK-6621) in Patients With Atrial Fibrillation (MK-6621-010 AM4): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of the Efficacy and Safety of Vernakalant Hydrochloride (MK-6621) in Patients With Atrial Fibrillation (MK-6621-010 AM4) (NCT01174160), a randomized phase 3 study. The primary outcome is Proportion of Patients With Treatment-induced Conversion of Atrial Fibrillation to Sinus Rhythm.

2. Clinical Question

The study was designed to compare the proportion meeting that endpoint between the randomized arms. The posted counts are 29 of 55 in the Vernakalant IV arm and 7 of 56 in the Placebo arm. The registry comparison reports an unadjusted p-value of <0.001 and a risk-difference estimate with confidence limits. These summaries describe the observed endpoint in the posted results; they do not establish what would happen in a different population or under different treatment conditions.

The trial record identifies atrial fibrillation as the condition and describes the purpose as comparing treatment-induced conversion with placebo. It does not report further primary-population details or a separate subgroup analysis. The research question is therefore best read as a comparison of the recorded endpoint proportions in the two randomized arms, within the registry's specified observation window.

3. Trial Design

The registry describes a Phase III, prospective, randomized, double-blind, placebo-controlled, multicenter study with a parallel-group model. These design features mean that the study planned concurrent treatment groups and that allocation was randomized; the record characterizes masking as double. The two intervention arms reported for the primary outcome are Vernakalant IV and Placebo.

The registry lists enrollment as 123. The posted primary-outcome groups contain 55 participants in the Vernakalant IV arm and 56 in the Placebo arm. These figures are reported separately as recorded; no attempt is made to reconcile them with the enrollment figure. The study status is completed. The record gives a start of 2010-08 and primary completion of 2012-09.

The primary outcome is a count-based binary endpoint: whether a participant experienced treatment-induced conversion of atrial fibrillation to sinus rhythm for a minimum duration of 1 minute within 90 minutes after first exposure. The registry lists one outcome measure and no posted secondary outcome measures. It lists no analyses in the analysis count, while a comparison and arm-level outcome values are available in the results.

The record names Advanz Pharma as sponsor. It does not report the original sample-size justification, the detailed randomization procedure, the allocation ratio planned in the protocol, or the original statistical analysis plan. It also does not report the protocol's intended interim-analysis arrangements. Those omissions limit what can be concluded about planning and analysis choices beyond the design characteristics explicitly recorded.

Randomization and masking are relevant context for interpreting the comparison, but their presence in the registry does not provide all operational details needed to assess implementation. The posted results describe the observed event counts and an unadjusted comparison. No adjusted model or analysis population definition is reported in the registry record, so the comparison should not be described as adjusted or as applying to a particular population beyond the groups shown.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Proportion of Patients With Treatment-induced Conversion of Atrial Fibrillation to Sinus Rhythm, measured over Within 90 minutes after first exposure.

The primary endpoint counts participants whose atrial fibrillation converted to sinus rhythm after treatment and remained converted for a minimum duration of 1 minute. The registry specifies that this was assessed within 90 minutes after first exposure. The result is binary at the participant level: each participant either met the stated event definition or did not, according to the outcome record.

This endpoint is used to describe an early rhythm-conversion outcome. For a binary endpoint, the arm-level event count and the number of participants in that arm allow the observed proportion to be characterized, and the proportions can be compared between randomized arms. The registry reports 29 events among 55 participants in the Vernakalant IV arm and 7 among 56 in the Placebo arm.

The endpoint's definition matters. It concerns conversion sustained for at least the specified duration, not merely a brief change in rhythm, and it is limited to the stated timeframe. It is not a measure of long-term rhythm status, later recurrence, symptoms, quality of life, or other clinical outcomes. Those outcomes are not reported as secondary outcome measures in the registry record.

As a general statistical point, a clearly specified event definition and assessment window help make the comparison interpretable: the event being counted and the time during which it can occur are explicit. That clarity does not remove uncertainty in the estimated proportions, nor does it make this short-term endpoint a substitute for outcomes that the record does not report.

7. Results Posted in the Registry

• Vernakalant IV: 52.7% (29/55) versus 12.5% (7/56) on control; risk difference 40.2 percentage points (95% CI 24.4 to 56.0), risk ratio 4.22 (2.02–8.81); unadjusted two-proportion z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary result is a comparison of a binary outcome between two randomized arms. The outcome is counted when a participant has treatment-induced conversion of atrial fibrillation to sinus rhythm for a minimum duration of 1 minute within 90 minutes after first exposure. For each arm, the record reports the event count and the number of participants. This makes it possible to describe the observed proportion in each arm and compare the groups using absolute and relative measures.

What does a risk difference describe?

A risk difference subtracts one arm's event proportion from the other arm's event proportion. It stays on the absolute-proportion scale: it describes the separation between the groups rather than how many times as large one proportion is relative to another. A value of zero corresponds to equal proportions; values above or below zero indicate the direction of the contrast according to the comparison's specified arm order. The registry reports a risk-difference estimate and confidence limits for the primary comparison. Because the confidence limits do not include zero, they indicate a range of values on one side of the equal-proportions reference under the interval method used.

How do relative measures differ?

A risk ratio divides one event proportion by the other. A ratio of one corresponds to equal proportions, and values above or below one express the direction and relative scale of the comparison. The posted risk ratio is 4.218, with confidence limits from 2.019 to 8.812. An odds ratio compares event odds rather than proportions; odds are formed from the event count relative to the non-event count. The posted odds ratio is 7.808, with confidence limits from 3.012 to 20.24. The odds ratio and risk ratio can differ in magnitude, particularly when event proportions are not small, so each should be interpreted according to its own scale.

These relative estimates indicate a higher observed event frequency in the Vernakalant IV arm than in the Placebo arm. They do not mean that a participant's individual outcome is certain, and they are not predictions for every patient. The absolute measure and the event counts help retain the scale of the observed data, while relative measures express the comparison in multiplicative terms.

What does the p-value add?

The reported unadjusted p-value is <0.001. In general, a p-value assesses how unusual data at least as incompatible with a specified null hypothesis would be if that null hypothesis and the test's assumptions held. It is not the chance that the null hypothesis is correct, and it does not quantify the probability that a result is due to chance. The p-value also does not describe the size of the effect; that is why effect estimates and confidence intervals are important alongside it.

The registry labels the comparison unadjusted. In general, an unadjusted comparison uses the observed group summaries without accounting for other covariates in a model. This can be a direct way to describe the randomized-group contrast, but the record does not provide a model specification or covariate-adjusted estimate. The recalculated comparison is a simple unadjusted re-calculation from the posted summary statistics. The registry has no discrepancy flag for this comparison, so no conflicting sponsor result is identified.

Why do confidence intervals matter?

A confidence interval describes uncertainty around an estimate under a statistical procedure. In repeated use of a procedure under its assumptions, intervals constructed in this way have a specified coverage property. For an individual trial, it is not accurate to interpret the interval as assigning a probability to the fixed true effect. It is useful to inspect both the interval's location and width: the location indicates the range of effects compatible with the estimate, while the width indicates how precisely the effect is estimated.

Intervals for different measures use different null references. For a risk difference, the equal-proportions reference is zero; for a ratio measure, it is one. Whether an interval crosses its reference can help describe statistical compatibility, but it does not settle questions of clinical importance or generalizability. The registry record does not state the interval-construction method, so no method-specific claim is made.

What does over-dispersion mean in general?

Over-dispersion is a general statistical concern when observed variability exceeds what a model's assumed distribution allows. It can make standard errors too small and confidence intervals too narrow if ignored. It is especially discussed for count outcomes and clustered or correlated data. This endpoint is reported as a binary participant count, and the registry does not report an over-dispersion assessment or a model for clustered observations. Therefore, over-dispersion should not be asserted as a feature of this trial's analysis; it is a general concept relevant when evaluating whether a model's assumptions fit its data.

The reported measures are interpretable as a comparison of arm-level binary results, but the registry record leaves several methodological details unreported: the exact test, interval method, analysis population, missing-data approach, covariate adjustment, and any handling of multiple comparisons. The absence of these details means the statistical procedure cannot be fully reconstructed from the record. The posted effect estimates, intervals, and p-value should be read as the registry's available comparison rather than as a complete account of the analysis plan.

10. Confidence Intervals and Precision

The risk-difference estimate is accompanied by confidence limits, as are the posted risk ratio and odds ratio. The ratio estimates are 4.218 for the risk ratio, with limits from 2.019 to 8.812, and 7.808 for the odds ratio, with limits from 3.012 to 20.24. These ranges communicate uncertainty that a point estimate alone cannot show. The intervals remain on the side of their respective null references that corresponds to a higher observed outcome in the Vernakalant IV arm, but they include a range of possible effect magnitudes.

In general, a confidence interval is a range generated by a statistical procedure to reflect sampling uncertainty. Its width depends on factors such as the amount of information in the data and the variability of the outcome. A narrower interval generally indicates greater precision under the procedure's assumptions; a wider interval indicates less precision. An interval is not a guarantee that the true effect lies within its limits, nor does it show the probability that any particular effect value is true.

The posted counts—29 of 55 and 7 of 56—are the data underlying the arm-level comparison. The unadjusted p-value is <0.001, but that threshold does not make the effect estimate precise by itself. Statistical evidence against equal proportions and precision of the magnitude are related but distinct questions. The intervals are therefore important even when the p-value is small.

The registry does not report the confidence-interval construction method or a separate precision analysis. Interpretation should remain tied to the posted estimates and their stated limits, rather than implying that the interval captures every source of uncertainty, including uncertainty from unreported design or analysis choices.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are illustrative calculations based on the observed effect, not the trial's original design assumptions. The registry record does not report the original sample-size justification. For this binary outcome, the planning values are participants per arm, not total events. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect.

For planning based on 100% of the observed effect, the illustration gives 21 participants per arm for 80% power and 27 participants per arm for 90% power. For 75% of the observed effect, it gives 34 participants per arm for 80% power and 45 participants per arm for 90% power. For 50% of the observed effect, it gives 67 participants per arm for 80% power and 89 participants per arm for 90% power.

In general, power is the chance that a specified statistical procedure will reject its null hypothesis when a particular alternative effect is true, under the assumptions used for the calculation. The 80% and 90% columns indicate different target probabilities of detecting the selected effect under those planning assumptions. A higher target power requires more participants for the same effect, and a smaller effect requires more participants to detect than a larger effect, other assumptions being equal. These figures are not observed power; they are planning illustrations computed from the observed effect. They should not be interpreted as the sample size that the trial originally planned or as evidence about what the original investigators assumed.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.125; treatment proportion p₁ = 0.527; average p̄ = 0.326.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6630 = 1.2994.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5989 = 0.5040.
4. n = (1.2994 + 0.5040)² / (0.4023)² = 20.1, rounded up to 21 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.125                          # control proportion
p1 <- 0.527272727272727                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1174160)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 21 (80% power), 27 (90% power)
 75% of observed effect: n per arm = 34 (80% power), 45 (90% power)
 50% of observed effect: n per arm = 67 (80% power), 89 (90% power)
power.prop.test: 20.1 
Simulated power at n = 21 per arm: 0.844 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists one outcome measure and no posted secondary outcome measures. It does not report an adjustment for multiple comparisons, a hierarchy of hypotheses, or a prespecified multiplicity strategy. With a single posted primary comparison, multiplicity cannot be evaluated across a broader family of outcomes from this record. The absence of posted secondary outcomes does not establish that no other outcomes were considered in the study; it means they are not reported in the registry record.

The analysis count is listed as zero, while the results include arm-level values and an unadjusted comparison. The record does not supply a detailed analysis plan, identify a primary analysis population, or state whether the analysis followed an intention-to-treat, per-protocol, or other population definition. Those labels should not be inferred from the randomized design alone.

Missing-data handling is not reported in the registry record. In general, missing outcome information can affect a binary comparison if participants with unavailable outcomes are treated differently or excluded. Without information about outcome availability, imputation, or sensitivity analyses, it is not possible to assess whether missing data could have changed the estimate. No claim is made that missing data occurred or did not occur.

The record also does not report interim analyses, stopping rules, or adjustments related to repeated looks at accumulating data. These are distinct from the multiple-outcome issue and cannot be presumed from the study's Phase III designation. The reported p-value should therefore be read as the posted unadjusted result, not as evidence that multiplicity or interim monitoring was addressed in a particular way.

As a general principle, statistical conclusions are easiest to interpret when outcomes, analysis populations, missing-data methods, and multiplicity procedures are prespecified and reported. The registry contains limited information on those topics. This limitation constrains assessment of the analysis's robustness but does not alter the stated arm counts or the comparison that the record reports.

14. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 1% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: dyspnoea (3.6%), chest pain (3.6%), cerebral infarction (3.6%), arrhythmia (1.8%), sick sinus syndrome (1.8%).

The registry reports serious adverse events in 6 participants at risk in the Vernakalant IV group and 6 participants at risk in the Placebo group. For other adverse events, the recorded figures are 23 in each group, with 55 participants at risk in the Vernakalant IV group and 56 in the Placebo group. The registry does not report deaths for these groups; death counts are not reported in the registry record.

The registry lists serious-event terms with percentages: Dyspnoea, 3.6%; Chest pain, 3.6%; Cerebral infarction, 3.6%; Arrhythmia, 1.8%; Sick sinus syndrome, 1.8%; and Acute renal failure, 1.8%. The record does not specify in this listing which treatment arm each term belongs to, so these percentages should not be attributed to a particular arm. They are terms recorded in the serious-event listing, not a comparison of arm-specific risks.

Safety counts describe events captured under the registry's reporting framework. They do not by themselves establish whether an event was caused by treatment, and the record does not provide enough detail to assess causality, timing, severity grading, or exposure-adjusted rates. The similar reported counts should not be interpreted as proof of equivalent safety. This is a description of the posted safety information, not a treatment recommendation.

15. What the Result Does, and Does Not, Mean

The result concerns a narrowly defined short-term event: treatment-induced conversion of atrial fibrillation to sinus rhythm sustained for a minimum duration of 1 minute within 90 minutes after first exposure. In the posted results, 29 of 55 participants in the Vernakalant IV group met that endpoint, compared with 7 of 56 in the Placebo group. The registry comparison reports an unadjusted p-value of <0.001 and effect estimates with confidence intervals. Taken together, the observed counts and comparison indicate a higher recorded conversion proportion in the vernakalant arm for this trial outcome.

That finding does not mean every participant in the intervention arm converted, or that conversion was impossible in the placebo arm. It does not establish what would happen for an individual participant, in another population, or under a different treatment protocol. It also does not describe how long sinus rhythm was maintained after the specified minimum duration, whether atrial fibrillation later recurred, or whether other health outcomes changed. Those outcomes are not reported in the registry record.

A small p-value is not a measure of clinical importance, and the relative estimates should be read alongside the event counts and confidence intervals. Statistical evidence, effect magnitude, precision, safety, and applicability are related but separate considerations. The registry's information about the primary comparison does not answer every question about those topics.

The safety record includes counts of serious and other adverse events and a list of serious-event terms. It does not provide the detailed context needed to determine causation or compare event-specific risks by arm. Nor does the registry report an analysis population definition, missing-data approach, or full statistical plan. These limitations mean the result should be understood as a comparison of the posted endpoint data, not as a comprehensive evaluation of all possible benefits and harms.

No medical advice follows from this statistical description. The record supports interpretation of the trial's posted outcome and safety summaries only; it does not establish effects outside the studied comparison or outcomes that were not reported.

16. Why This Trial Matters Statistically

This trial illustrates how a binary clinical endpoint can be described from event counts in randomized groups. The primary outcome has a clear event definition and timeframe: conversion to sinus rhythm for at least 1 minute within 90 minutes after first exposure. Reporting both the event counts and group sizes lets readers understand the basis of the comparison rather than relying on a p-value alone.

It also illustrates why absolute and relative measures answer different questions. The risk difference describes the separation between observed proportions, while the risk ratio and odds ratio express relative contrasts on different scales. Their confidence intervals show uncertainty around each measure. Looking across these summaries is more informative than treating any single statistic as a complete account of the result.

The registry reports an unadjusted p-value of <0.001 and intervals whose limits lie on the side associated with a higher event proportion in the Vernakalant IV group. Statistical evidence is therefore clear for the posted comparison, but precision and clinical interpretation still require attention to the interval widths, the outcome definition, and the study population. A statistically small p-value does not resolve whether an effect is important for a clinical decision.

The record also highlights the limits of registry reporting. It gives the randomized, double-blind, placebo-controlled, parallel design and basic arm results, but does not report the full analysis plan, missing-data procedures, population definition, or original sample-size justification. Those omissions make it harder to evaluate analysis choices and generalizability independently.

Finally, the planning illustrations demonstrate that sample-size requirements depend on the effect targeted and the desired power. They are based on the observed effect and should not be mistaken for the trial's original planning or for observed power. Separating design information, observed results, uncertainty, and planning assumptions is central to careful statistical reading.

17. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several details that would support a fuller assessment are not reported in the registry record. The eligibility criteria and the primary analysis population are not described in the outcome information, limiting assessment of which patients the posted comparison represents. The record does not provide the original sample-size justification or the detailed statistical analysis plan, so the planning basis and prespecified analysis choices cannot be verified.

Missing-data methods, outcome availability, and sensitivity analyses are not reported. The exact test and confidence-interval construction method are also not identified. No adjusted analysis is described, and the record does not report interim analyses or a multiplicity strategy. These omissions restrict evaluation of robustness and of how the nominal comparison relates to any broader set of analyses.

The primary endpoint is limited to conversion within 90 minutes after first exposure and requires sinus rhythm for a minimum duration of 1 minute. The record does not report longer-term rhythm outcomes or other secondary outcomes. Accordingly, the primary result cannot be extended to outcomes outside its definition and timeframe.

Safety reporting is also limited. The registry gives serious and other adverse-event counts and selected serious-event terms, but does not provide event-specific arm attribution in the listed terms, causal assessments, or the detail needed to compare rates over exposure time. Death counts are not reported in the registry record. The available information supports a description of posted safety counts, not a complete safety profile.

The enrollment figure and the arm-level outcome group sizes are recorded as separate values. They are presented as listed, without attempting to reconcile them. These limitations concern what can be assessed from the registry record and should not be taken as evidence that any particular unreported procedure or event did or did not occur.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: A Study of the Efficacy and Safety of Vernakalant Hydrochloride (MK-6621) in Patients With Atrial Fibrillation (MK-6621-010 AM4) — NCT01174160.
• Registry record last updated 2015-12-15; status last verified 2015-11.
• Results first posted 2015-12-15.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

The registry describes NCT01174160 as a completed Phase III, prospective, randomized, double-blind, placebo-controlled, multicenter, parallel-group study of vernakalant hydrochloride in patients with atrial fibrillation. Advanz Pharma is listed as sponsor. The record gives a start of 2010-08, primary completion of 2012-09, and enrollment of 123.

The primary outcome was treatment-induced conversion of atrial fibrillation to sinus rhythm for a minimum duration of 1 minute within 90 minutes after first exposure. The posted counts are 29 of 55 in the Vernakalant IV group and 7 of 56 in the Placebo group. The comparison reports an unadjusted p-value of <0.001, along with risk-difference, risk-ratio, and odds-ratio estimates and confidence limits.

The registry lists serious and other adverse-event counts, but does not report death counts. It does not report secondary outcome measures, the original sample-size justification, or several analysis details, including missing-data handling and the analysis population. The statistical interpretation is therefore limited to the posted primary comparison and safety summaries.