Effects of Eplerenone on Cardiovascular Disease in HIV (MIRACLE HIV Study): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effects of Eplerenone on Cardiovascular Disease in HIV (MIRACLE HIV Study) (NCT02740179), a randomized na study. The primary outcome is Myocardial Perfusion by PET.

2. Clinical Question

3. Trial Design

The MIRACLE HIV Study was a randomized, quadruple-masked, parallel-group trial. The registry lists enrollment of 40 and a completed status. The record gives a start date of 2017-01 and a primary completion date of 2022-03-17. The phase is listed as NA. The sponsor was Massachusetts General Hospital.

Participants were assigned to eplerenone or placebo, with lifestyle modification in both arms. The eplerenone regimen was 50 mg twice daily for 12 months; the placebo arm received placebo twice daily for 12 months. Both groups were also offered counseling regarding diet and healthy activity. These details define the treatment contrast: the difference between the assigned drug strategies against a shared lifestyle-modification background.

The planned primary measure was myocardial perfusion by PET at 12 months, expressed as change from baseline. The primary result population is described as analyses performed on data available. The posted outcome summaries include 14 participants in the eplerenone group and 19 in the placebo group. Those counts describe available outcome data for this analysis; the record does not explain why they differ from the enrollment figure or provide a detailed account of missing outcome data.

The registry lists coronary plaque and several vascular, inflammatory, immune-activation, subclinical-injury, and fibrosis outcomes among the secondary outcome domains. It records 16 outcome measures and 16 analyses, with 13 secondary outcomes posted. The registry record does not report the trial’s original sample-size justification, its detailed randomization procedure, or a full statistical analysis plan. Those omissions limit what can be concluded about planning and prespecification beyond the information explicitly recorded.

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

Analysis population for the primary outcome, as defined in the registry: Analyses performed on data available

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 Myocardial Perfusion by PET, measured over 12 Months.

The primary endpoint measures change in myocardial perfusion from baseline to 12 months. Perfusion was assessed through coronary flow reserve measured by cardiac positron emission tomography. Coronary flow reserve is defined in the registry as the ratio of blood flow during stress, when the coronary arteries are maximally dilated, to blood flow at rest. The endpoint is unitless, and the analysis describes a mean change for each group.

In general, a flow-reserve measure captures how blood flow under stress relates to resting flow. It is used as a physiological indicator of coronary circulation, rather than as a direct count of clinical events. The registry’s rationale connects this measurement to its question about cardiovascular health in people with HIV and the possible relationship between aldosterone and coronary disease-related processes. That rationale explains why perfusion was assessed; it does not establish that a change in the measure predicts a particular clinical outcome in this trial.

The posted group means describe average change, not each participant’s trajectory. A positive mean indicates an average increase from baseline and a negative mean an average decrease, according to the stated change definition. The clinical importance of a particular change is not specified in the registry record. The primary result should therefore be read as a comparison of a measured physiological outcome, with attention to its uncertainty and to the available analysis population.

7. Results Posted in the Registry

• Eplerenone: mean 0.01 versus -0.07 on control; difference 0.08 (95% CI -0.32 to 0.48), standardized effect d = 0.14; z-test p = 0.694.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Assessment of Cardiac Diastolic Function Via Cardiac Imaging

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Eplerenone: mean -13.00 versus 10.00 on control; difference -23.00 (95% CI -41.76 to -4.24), standardized effect d = -0.86; z-test p = 0.016.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Eplerenone than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry identifies a broad set of secondary domains, including coronary plaque, vascular dysfunction, systemic inflammation, immune activation, subclinical injury, and fibrosis. It records 13 secondary outcomes posted and 16 outcome measures and analyses overall. These domains provide additional ways to examine cardiovascular and biological outcomes, but they do not form a single combined measure of treatment effect.

The secondary results should be interpreted as separate endpoint analyses rather than as a unified confirmation or refutation of the primary result. A secondary measure may capture a different biological process, use a different scale, or have different precision. The registry does not provide an overall summary that combines the secondary findings into one estimate. The primary myocardial perfusion result therefore remains a distinct finding, and the secondary outcomes cannot be substituted for it.

One secondary outcome listed in the record is assessment of cardiac diastolic function via cardiac imaging. Its posted group summaries and comparison are separate from the primary outcome. Other secondary results span the domains. A broad inventory of endpoints by itself does not indicate that they all moved in the same direction or that they support a common interpretation.

In general, testing many endpoints increases the chance that some results may appear statistically notable by chance, particularly when no adjustment is made. The registry record does not report a multiplicity adjustment or a prespecified hierarchy for interpreting secondary tests. Therefore unadjusted secondary findings carry less weight as confirmatory evidence than a result from a clearly designated primary endpoint with an appropriate analysis plan. Their value is mainly in describing additional signals that may warrant cautious interpretation, rather than establishing independent conclusions.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Coronary Plaque
• Markers of Vascular Dysfunction
• Markers of Systemic Inflammation hsIL-6
• Markers of Systemic Inflammation hsCRP
• Markers of Immune Activation MCP-1
• Markers of Immune Activation sCD163
• Markers of Subclinical Injury
• Markers of Fibrosis

9. Statistical Interpretation

10. Statistical Methods Explained

The primary result compares mean changes in a continuous measure between two randomized groups. The registry reports means and standard deviations for each arm, along with the result of a two-sided t-test. A simple unadjusted recalculation uses those group summaries to estimate the mean difference and its uncertainty. It is a descriptive statistical reconstruction, not a claim about every detail of the trial’s analysis plan.

What does a mean difference represent?

The mean difference is the average change in the eplerenone group minus the average change in the placebo group. For the primary endpoint, the posted means are 0.01 and -0.07, respectively, and the recalculated mean difference is 0.08. This places the comparison on the original unitless scale of myocardial perfusion change. A difference is an average contrast; it does not mean that every participant’s outcome changed by that amount, or in the same direction.

The standard deviation describes variation among participant measurements within a group. The reported standard deviations are 0.64 for eplerenone and 0.48 for placebo. They are not standard errors of the group means and should not be read as confidence limits around those means. In general, standard deviations describe the spread of individual observations, while standard errors describe uncertainty in an estimated mean or contrast. The registry also lists standard errors for the group means, but the comparison’s interval is the more direct summary of uncertainty in the mean difference.

What does the two-sided test ask?

The registry reports a two-sided t-test with p = 0.72. In general, a two-sided test evaluates how compatible the observed data are with a null model of no group difference, while allowing departures in either direction. A p-value is not the probability that the null hypothesis is true, nor is it a measure of the clinical importance of an effect. A large p-value does not demonstrate equivalence; it indicates that the test did not find strong evidence against its null model.

The recalculated p-value is 0.694, based on a simple unadjusted comparison of the posted summaries. It is close to the registry-reported value of 0.72. The registry does not report a p-value adjustment for the primary test in the record, and the comparison is not described as adjusted for other variables. The method and analytic details beyond the listed t-test are not reported in the registry record.

Why can spread affect the comparison?

In general, larger variability makes a group contrast harder to estimate precisely when the amount of data is unchanged. Here, the group standard deviations are substantial relative to the mean contrast, which is consistent with the wide interval around the recalculated difference. The endpoint analysis counts are 14 for eplerenone and 19 for placebo. These available-data counts are the relevant numbers for interpreting this particular posted summary; they should not be replaced by the overall enrollment figure.

The standard t-test framework relies on assumptions about the outcome distribution and the sampling behavior of the estimated means. Whether the investigators assessed these assumptions, used alternative methods, or made adjustments for any departures is not reported in the registry record. A general explanation of statistical methods cannot establish which diagnostics or procedures were used in this trial.

What does an interval add?

The recalculated mean-difference interval ranges from -0.319 to 0.479. In general, a confidence interval gives a range of effect estimates compatible with the data under the method used. Its width makes the precision of the estimate visible, and whether it includes no difference helps explain the non-significant test result. The registry record does not specify a confidence level for the posted recalculated interval, so a confidence percentage should not be inferred from the record.

Finally, statistical significance, precision, and clinical importance are distinct. The p-value addresses compatibility with a null model under a specified test; the interval reflects uncertainty in the estimated difference; and clinical importance requires context about what changes in this measure mean. A threshold for a clinically important change is not reported in the registry record.

11. Confidence Intervals and Precision

The recalculated mean difference in myocardial perfusion change is 0.08, with interval limits of -0.319 and 0.479. The range includes zero and extends to both negative and positive values. Accordingly, the posted data do not pin down the direction of the difference, and they allow a broad range of possible magnitudes on the unitless outcome scale.

An interval is useful because it displays uncertainty around an estimate rather than reducing the result to whether a p-value crosses a threshold. In general, narrower intervals indicate greater precision, while wider intervals indicate that the data leave more uncertainty about the effect. The interval is wide relative to the point estimate. This is consistent with the variation in the group measurements and the available endpoint-analysis counts of 14 and 19.

The interval limits are from the simple recalculation of posted summary statistics. The registry record does not report a confidence level for this interval, so it should not be labeled with a particular confidence percentage. The record also does not provide a registry-reported interval for the primary comparison. The sponsor’s recorded test result is p = 0.72, while the recalculated unadjusted p-value is 0.694.

Precision is not the same as bias, and an interval does not account for every limitation in a study. It reflects uncertainty under the method used and the data analyzed. The registry does not report enough detail to assess all assumptions, missing-data handling, or potential sources of systematic error. The interval should therefore be understood as uncertainty around this particular summary comparison, not as a complete account of uncertainty about every possible cardiovascular effect.

12. 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 expressed as participants per arm, not as total events. They are illustrations based on the observed primary effect, rather than the trial’s original design assumptions. The calculation uses a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. The trial’s own original sample-size assumptions are not reported in the registry record.

The 80% power column gives the illustrative participants per arm for a design with an 80% chance of detecting the specified effect under the stated planning assumptions, if that effect were the true effect and the model assumptions held. The 90% power column gives the corresponding per-arm planning figure for a 90% chance. These are prospective planning concepts, not measures of what the completed trial achieved.

For planning at 100% of the observed effect, the figures are 750 participants per arm for 80% power and 1,004 participants per arm for 90% power. For planning at 75% of the observed effect, the figures are 1,333 and 1,784 participants per arm, respectively. For planning at 50% of the observed effect, the figures are 2,998 and 4,014 participants per arm, respectively. The pattern illustrates that smaller effects require more participants to detect, all else equal.

These calculations use the observed effect as a planning reference, which can be uncertain, especially when estimated from limited data. They are not observed power and should not be read as a retrospective verdict on whether the trial was adequate. They also do not reveal the justification or target used when the trial was originally designed.

13. 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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 0.080; pooled standard deviation σ = 0.553.
2. n = 2 × (1.96 + 0.842)² × 0.553² / 0.080² = 749.4, rounded up to 750 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
delta <- 0.08                      # observed difference in means
sigma <- 0.552764314239599                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(2740179)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 750 (80% power), 1,004 (90% power)
 75% of observed effect: n per arm = 1,333 (80% power), 1,784 (90% power)
 50% of observed effect: n per arm = 2,998 (80% power), 4,014 (90% power)
power.t.test: 750.4 
Simulated power at n = 750 per arm: 0.799 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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.

14. Analyses Reported by the Sponsor

The registry’s own primary analysis reports a two-sided t-test with p = 0.72. The recalculation from the posted group summaries gives a mean difference of 0.08, an interval from -0.319 to 0.479, and an unadjusted p-value of 0.694. The difference between the p-values is small, and both analyses lead to the same broad reading: the posted primary comparison is not statistically significant.

The recalculation is a simple, unadjusted reconstruction based on the reported means, standard deviations, and analysis counts. It is useful for interpreting the size and uncertainty of the group contrast, but it does not incorporate any analysis details that are absent from the registry record. The registry does not provide a full analysis specification or a registry-reported confidence interval for this comparison.

There is no material discrepancy flagged between the recalculation and the sponsor’s own analysis. The sponsor’s reported analysis remains the registry’s formal result, while the recalculation offers an additional summary of the posted data. Neither p-value measures clinical importance, and neither establishes equivalence. The interval is informative about the uncertainty of the estimated difference and includes values on both sides of no difference.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 16 outcome measures and 16 analyses, including a primary endpoint and secondary outcomes across several cardiovascular and biological domains. When multiple outcomes are tested, the chance of at least one apparently notable result can increase if each test is considered separately. In general, multiplicity methods aim to control that issue, for example by adjusting thresholds or by specifying an ordered testing strategy. The registry record does not report whether such a method was planned or used for the secondary outcomes.

The primary analysis is reported as a two-sided t-test with p = 0.72. The record does not state whether the primary test was part of a formal multiplicity strategy, nor does it describe a hierarchy among secondary outcomes. This absence does not establish that no adjustment or hierarchy existed; it means those details are not reported in the registry record. Secondary p-values should consequently be interpreted cautiously and not as a collection of independent confirmations.

The primary population is described as analyses performed on data available. The posted endpoint counts are 14 for eplerenone and 19 for placebo, while the record lists overall enrollment of 40. The registry does not explain the difference between enrollment and the counts in this outcome analysis, detail the reasons data were unavailable, or report an imputation or other missing-data method. It is therefore not possible to determine from the registry record whether missingness could have influenced the estimate.

The record also does not provide a complete analysis-population definition, such as whether the primary analysis followed an intention-to-treat principle or used a different population rule. It does not report covariate adjustment, missing-data sensitivity analyses, or diagnostics for assumptions of the test. These omissions do not show that such procedures were absent from the full study conduct; they limit what can be assessed from the registry record. Interpretations should be confined to the posted available-data summaries and the reported test.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: medical condition leading to death (5.0%).

The adverse-event record lists serious adverse events affecting 1 participant in the eplerenone group and 0 in the placebo group. The numbers at risk for serious adverse events are 20 in each group. Deaths are listed as 1 in the eplerenone group and 0 in the placebo group. These are descriptive registry counts; they do not establish that treatment caused an event or death.

For other adverse events, the record lists 12 affected participants in the eplerenone group and 11 in the placebo group, with 20 at risk in each group. These figures are distinct from the serious-event counts. The listed top serious-event term is “Medical condition leading to death,” with 5.0%. The registry record does not provide additional details about the event or its relationship to treatment.

Event counts in a small trial can be highly uncertain and should not be treated as stable comparative risk estimates. The record does not report further details on event definitions, severity beyond the serious-event category, timing, duration, or adjudication. Nor does it provide a statistical comparison of adverse-event rates in the posted information. Safety counts should therefore be read descriptively and in the context of the limited information recorded.

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

The primary result describes a comparison of average change in myocardial perfusion at 12 months for the available outcome data. The estimated mean difference is 0.08, and the interval from -0.319 to 0.479 includes no difference as well as values in either direction. The registry’s two-sided test reports p = 0.72. Together, these statistics indicate uncertainty: the posted analysis does not establish a statistically significant difference, but it also does not show that the treatments are equivalent.

The result is specific to coronary flow reserve measured by cardiac PET and to the registry’s definition of change from baseline. It is not a direct test of every cardiovascular outcome. The study background discusses aldosterone and cardiovascular processes in people with HIV, while the registry lists other outcomes such as coronary plaque and markers of vascular dysfunction and inflammation. Conclusions about those distinct measures require their own evidence and should not be inferred from the primary result alone.

Statistical significance does not decide whether a difference is clinically important. The registry record does not state a threshold for a meaningful change in the unitless perfusion measure. Conversely, a non-significant result does not show that a clinically important effect is impossible; the interval is broad and leaves substantial uncertainty about the contrast.

The analysis is based on data available for the primary outcome, and the registry does not explain the missing-data process. The trial’s enrollment figure and the endpoint analysis counts are not interchangeable. The record also does not report a full statistical analysis plan, including detailed missing-data or multiplicity procedures. These limits mean the result should be read as a description of the posted analysis, rather than as a complete account of every possible treatment effect or every analysis performed.

The most defensible interpretation is narrow: the registry reports no statistically significant primary group difference in change in myocardial perfusion, and the recalculated estimate is imprecise. The data neither establish a clear difference nor establish no difference.

18. Why This Trial Matters Statistically

This trial illustrates why a clinical result should be read through its estimate, uncertainty, analysis population, and endpoint definition rather than through a p-value alone. The primary p-value is not statistically significant, but that does not answer how large the group contrast might be. The recalculated interval, extending from -0.319 to 0.479 around an estimate of 0.08, shows that the direction and magnitude remain uncertain.

The endpoint is a continuous physiological measure, so the comparison is expressed as a difference in average change rather than as a difference in event counts. Understanding that distinction matters: myocardial perfusion by PET is not itself a clinical event, and an estimate on this scale should not be translated into a claim about all cardiovascular outcomes. The record’s broader set of secondary domains also underlines that a single primary measure cannot represent every aspect of cardiovascular health.

The trial record offers a useful contrast between overall enrollment and available data for the primary analysis. The enrollment figure is 40, while the posted outcome analysis contains 14 participants in the eplerenone group and 19 in the placebo group. The record does not explain this difference. That makes transparent reporting of the analysis population and missing-data handling important for assessing precision and possible selection effects.

The posted sample-size planning illustrations also show how the number of participants needed depends on the effect size a future study aims to detect. Those figures are not the original design plan and are not observed power. Separating planning calculations from trial results prevents an observed estimate from being mistaken for a definitive design target. Overall, the record highlights the value of clear estimands, uncertainty intervals, multiplicity plans, and complete reporting of analyzed data.

19. 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.

The main limitation for interpreting the primary result is its imprecision. The recalculated interval spans negative and positive differences, so the data do not determine a clear direction or magnitude. The available-data analysis counts are 14 for eplerenone and 19 for placebo, and the registry does not explain why these differ from enrollment of 40 or describe how missing outcome data were handled.

The registry record does not report the original sample-size justification, detailed eligibility criteria, participant characteristics, or a full statistical analysis plan. It does not specify the confidence level for the recalculated interval. Details about the randomization procedure, the exact masking roles, outcome-assessment procedures, and any covariate adjustments are also not reported in the registry record. These gaps limit assessment of design execution and the assumptions behind the posted comparison.

The record lists numerous secondary outcomes but does not report whether multiplicity was controlled, how endpoints were prioritized, or whether all analyses were prespecified. This is relevant because isolated secondary findings can be less reliable when many outcomes are examined. The record does not provide a unified summary across secondary endpoints.

The primary endpoint is a physiological measure rather than a clinical event, and the registry does not state a threshold for a clinically important change. Follow-up for the stated treatment regimen is 12 months; the record does not establish what the result means beyond that timeframe. These considerations do not invalidate the posted results, but they constrain how broadly they can be interpreted. The most appropriate reading remains specific to the endpoint, available-data population, follow-up, and methods recorded.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Effects of Eplerenone on Cardiovascular Disease in HIV (MIRACLE HIV Study) — NCT02740179.
• Registry record last updated 2023-06-06; status last verified 2023-06.
• Results first posted 2023-06-02.
• 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.

23. Record Summary

The MIRACLE HIV Study was a completed randomized, quadruple-masked, parallel-group trial comparing eplerenone with placebo, with lifestyle modification in both groups. Eplerenone was given as 50 mg twice daily for 12 months, and placebo was given twice daily for 12 months. Overall enrollment was 40.

The primary endpoint was change from baseline to 12 months in myocardial perfusion assessed by coronary flow reserve on cardiac PET. The posted means were 0.01 for eplerenone and -0.07 for placebo. The recalculated unadjusted mean difference was 0.08, with an interval from -0.319 to 0.479. The registry’s two-sided test reported p = 0.72.

The primary analysis did not establish a statistically significant group difference, and the interval indicates substantial uncertainty. The registry describes the analysis population as data available; detailed missing-data handling, the original sample-size justification, and multiplicity procedures are not reported in the registry record.