Apixaban Versus Warfarin in Patients With Left Ventricular Thrombus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Apixaban Versus Warfarin in Patients With Left Ventricular Thrombus (NCT02982590), a randomized phase 3 study. The primary outcome is Percent Change in Left Ventricular Thrombus (LVT) Size.

2. Clinical Question

The trial record describes a prospective randomized comparison, with outcome blinding. Its stated purpose was to compare apixaban with warfarin on thrombus size reduction or resolution over 3 months. The primary endpoint is the percentage change in thrombus size after 12 weeks of treatment, so the principal comparison is between the groups’ mean changes rather than simply the number of participants whose thrombus resolved.

The registry record also lists three secondary outcomes: change in thrombus size by more than 50%, clinically definite cardiac embolic ischemic stroke, and life-threatening bleeding. These outcomes address different aspects of the comparison and should not be treated as interchangeable with the primary measure. Details about how thrombus size was measured, the assessment schedule, and the criteria used to define resolution are not reported in the registry record.

3. Trial Design

This is a randomized, parallel-group phase 3 study recorded as completed. The registry record lists an enrollment of 27 and two treatment groups: warfarin sodium and apixaban. The warfarin description specifies daily dosing adjusted according to INR monitoring, with an aim of INR 2-3. The apixaban description specifies the 5 MG oral tablet for 3 months. The primary outcome timeframe is 3 months, and its description refers to assessment after 12 weeks of treatment.

The record describes the study as single masked and outcome blinded. It does not identify who was masked, how masking was maintained, or whether treatment allocation was concealed. The randomization method and procedures for generating or implementing the allocation are not reported in the registry record. The listed model is parallel, meaning the registry describes participants as assigned to one of the treatment groups rather than to a sequence of both treatments.

The registry record lists the study start as 2016-11 and primary completion as 2018-11. It identifies Universiti Sains Malaysia as the sponsor. Participant flow, withdrawals, adherence, crossovers, and reasons for missing outcome measurements are not reported in the registry record. Nor does the record specify whether the primary analysis followed an intention-to-treat, per-protocol, or other analysis population. The primary outcome data list 13 participants in the warfarin group and 14 in the apixaban group, but the analysis population and handling of missing data are not described.

Although the trial is designated phase 3, the registry record does not give the original sample-size justification or the assumptions used to plan enrollment. The planning illustrations accompanying the posted results are calculations based on observed effects, not evidence of the trial’s original design assumptions.

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.

Population: Gender, Age, Co-morbidities, HAS-BLED score

6. Primary Endpoint

The registry lists the primary outcome as Percent Change in Left Ventricular Thrombus (LVT) Size, measured over 3 months.

The primary endpoint is percent change in left ventricular thrombus size at 3 months, described as the percentage change after 12 weeks of warfarin or apixaban treatment. The registry reports a mean and standard deviation for each group. A change measure preserves information about the degree of change, rather than reducing the result to a yes-or-no classification such as whether the thrombus crossed a specified resolution threshold.

For a size-change outcome, negative values correspond to a decrease from the earlier measurement under the usual interpretation of percentage change. The posted group means are negative in both arms, and the study’s stated purpose is to assess reduction or resolution. The registry record does not report the measurement method, the exact calculation used to form percentage change, or the criteria for resolution, so those details cannot be assessed from the record.

Comparing group means gives a summary of the average change in each randomized group. It does not show how individual participants’ changes were distributed, whether a small number of observations strongly influenced the means, or how many participants achieved complete resolution. Those questions require information beyond the reported means and standard deviations. The primary endpoint is therefore useful for comparing average size change, while the secondary outcomes describe selected thresholds and clinical events.

7. Results Posted in the Registry

• Apixaban: mean -65.08 versus -61.45 on control; difference -3.63 (95% CI -32.62 to 25.36), standardized effect d = -0.10; z-test p = 0.806.

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.

Change of Left Ventricular Thrombosis (LVT) by More Than 50%

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Apixaban: 64.3% (9/14) versus 76.9% (10/13) on control; risk difference -12.6 percentage points (95% CI -46.6 to 21.3), risk ratio 0.84 (0.51–1.37); unadjusted two-proportion z-test p = 0.472.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Apixaban and the control. The interval gives the range of effects that remain compatible with the data.

Clinically Definite Cardiac Embolic Ischemic Stroke

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Apixaban: 7.1% (1/14) versus 0.0% (0/13) on control; risk difference 7.1 percentage points (95% CI -6.3 to 20.6); unadjusted two-proportion z-test p = 0.326.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Apixaban and the control. The interval gives the range of effects that remain compatible with the data.

Life Threatening Bleeding

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Apixaban: 0.0% (0/14) versus 7.7% (1/13) on control; risk difference -7.7 percentage points (95% CI -22.2 to 6.8); unadjusted two-proportion z-test p = 0.290.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Apixaban and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover a threshold for thrombus change, a cardiac embolic ischemic stroke outcome, and life-threatening bleeding. Together they extend the assessment beyond the average percentage change in thrombus size, but they address different questions and have different data structures. The threshold outcome is binary, while stroke and bleeding are recorded as participant counts. Their results cannot be combined into a single measure of benefit or harm.

Across these endpoints, event counts are sparse, including outcomes with no recorded participants in one group. Such data provide limited information for estimating group differences, and apparent contrasts can be highly sensitive to a small change in event counts. The registry reports unadjusted comparisons, but lists no reported analyses for these outcomes. The secondary findings are therefore best regarded as descriptive and uncertain rather than confirmatory.

These outcomes do not replace the primary comparison of mean percentage change. A threshold outcome categorizes the size-change result and may discard information about how far above or below the threshold an individual result lies. Clinical events address outcomes distinct from thrombus size and may be too infrequent in a small study to give precise comparisons. Each contributes context, but none alone resolves the uncertainty in the primary endpoint.

Unadjusted secondary results carry less weight when several outcomes are examined because multiple comparisons increase the chance of a seemingly noteworthy finding arising without a corresponding underlying difference. The registry record does not report a multiplicity strategy, a hierarchy of endpoints, or confirmatory criteria. Nor does it provide analysis details that would establish these findings as prespecified confirmatory tests. They should be interpreted cautiously and alongside the primary estimate and its uncertainty, not as independent proof of a treatment difference.

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

• Change of Left Ventricular Thrombosis (LVT) by More Than 50%
• Clinically Definite Cardiac Embolic Ischemic Stroke
• Life Threatening Bleeding

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: each participant’s thrombus size is represented as a percentage change, and the registry summarizes each treatment group with a mean and standard deviation. A mean gives the arithmetic average of the recorded values. A standard deviation describes how spread out participant values are around that group mean. Neither statistic describes the full distribution, and the standard deviation should not be read as the uncertainty in the estimated mean difference.

What does the mean difference represent?

The posted mean difference is the apixaban group mean minus the warfarin group mean. It is reported as -3.63 in the percentage-change measure. A negative contrast means the apixaban group’s mean change is more negative than the warfarin group’s mean change. Because the endpoint records percentage change, this is a difference on that change scale, not a difference in the number of participants with resolution. The group means and the contrast summarize average outcomes; they do not show how much participants’ results overlap.

What does the confidence interval add?

A confidence interval expresses the uncertainty around an estimated contrast using a procedure with a stated long-run coverage property. In repeated use under its assumptions, the procedure would produce intervals containing the target value at the stated rate. It is not a range containing a fixed proportion of individual outcomes, nor does it assign a probability to the true value after the data have been observed. The reported interval, -32.62 to 25.36, includes zero and values on either side. It therefore leaves considerable uncertainty about the direction and size of the group difference.

How should the p-value be read?

The unadjusted p-value is 0.806. In general, a p-value measures how unusual data at least as discrepant as those observed would be under a specified null model and its assumptions. It is not the probability that the null hypothesis is true, and it does not measure the probability that chance alone caused the result. A p-value also does not indicate whether an effect is clinically important. Here, the interval and the small outcome groups are important alongside the p-value: the estimate is not precise enough to support a confident conclusion about the between-group difference.

Why does variability matter?

General explanation: when participant outcomes vary substantially, the group mean can be estimated less precisely unless there is enough information to offset that variability. Over-dispersion is a related concern in count or binary data: observed variability can exceed what a simple model assumes, which can make model-based uncertainty too small if the extra variation is ignored. The primary endpoint is continuous, and the record reports standard deviations, but it does not provide diagnostic information about distributional assumptions or model checks. The summaries alone cannot establish whether those assumptions were appropriate.

For binary endpoints, a participant either meets the stated outcome definition or does not. Counts and percentages summarize how often the outcome occurred in each group, while a risk difference contrasts the groups’ observed proportions. With very few events, the estimated contrast can be unstable and its uncertainty wide. General methods for binary data also depend on choices such as confidence-interval construction and whether any adjustment is made. The registry record does not report detailed methods for these secondary comparisons.

The posted p-values for the primary and secondary outcomes are unadjusted. No multiplicity adjustment or prespecified testing sequence is reported in the registry record. When several outcomes are examined, unadjusted tests do not account for the opportunity to observe a seemingly notable result among multiple comparisons. This is one reason to treat secondary findings as exploratory unless a suitable analysis plan and interpretation are documented. The registry record lists zero reported analyses, so the posted summary statistics should not be mistaken for a fully described sponsor analysis.

11. Confidence Intervals and Precision

The primary mean-difference estimate is -3.63, and its 95% confidence interval ranges from -32.62 to 25.36. The interval is wide relative to the point estimate and crosses zero. Values toward its negative end represent a larger mean change in the negative direction for apixaban relative to warfarin; values toward its positive end represent a difference in the other direction. The data therefore do not pin down either the direction or the magnitude of the contrast with much precision.

Precision is distinct from whether an estimate is statistically significant. A narrow interval would indicate that the estimated contrast is more tightly constrained under the analysis assumptions; a broad interval leaves more plausible values. Here, the interval includes both a potentially sizable negative difference and a positive difference. This means the posted result is compatible with a range of between-group effects, not only with no difference.

The group standard deviations, 43.95 for warfarin and 31.34 for apixaban, indicate appreciable spread in the observed percentage changes. With 13 participants in the warfarin outcome group and 14 in the apixaban outcome group, the estimates are based on a limited number of observations. These features help explain why the uncertainty matters, but the record does not provide enough detail to assess the distribution of values, missing observations, or sensitivity to analysis choices.

Confidence intervals for the secondary outcomes are also broad where reported. Their endpoints and estimates are not repeated; the essential point is that event counts are sparse and the uncertainty limits strong conclusions. The record does not report a formal precision target or a clinically meaningful difference threshold for the primary endpoint. Consequently, it is not possible to judge from the registry whether the interval excludes differences that investigators considered important.

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 participants per arm, not total participants and not total events. They are illustrations based on the observed effect, rather than the trial’s own original design calculations. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set at the listed fraction of the observed effect. The record does not report the assumptions used for the original trial design.

The 80% power column describes the illustrative number of participants per arm calculated to give an 80% chance of detecting the specified effect under those assumptions if that effect were the true one. The 90% column describes the corresponding calculation for a 90% chance. These are planning concepts: power is tied to an assumed effect, variability, analysis method, and significance threshold. The listed values should not be read as evidence about the chance that this completed trial detected an effect.

For the primary continuous outcome, the illustrations range from 1,713 participants per arm for planning around 100% of the observed effect to 6,852 participants per arm for 80% power when planning around 50% of the observed effect. The corresponding 90% figures are 2,294 and 9,173 participants per arm. Planning for 75% of the observed effect gives 3,046 participants per arm for 80% power and 4,077 for 90% power. The secondary binary outcome with a greater-than-50% change has its own illustration, based on its observed effect.

Smaller effects are harder to distinguish from random variation, so detecting them generally requires more participants under otherwise similar assumptions. The curve expresses that planning relationship across effect sizes. This is not observed power: it is a forward-looking illustration using the observed effect as an input, not a measure of what the completed trial achieved.

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 = -3.630; pooled standard deviation σ = 37.920.
2. n = 2 × (1.96 + 0.842)² × 37.920² / -3.630² = 1,713.0, rounded up to 1,713 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 <- -3.63                      # observed difference in means
sigma <- 37.9197957800408                     # 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(2982590)
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 = 1,713 (80% power), 2,294 (90% power)
 75% of observed effect: n per arm = 3,046 (80% power), 4,077 (90% power)
 50% of observed effect: n per arm = 6,852 (80% power), 9,173 (90% power)
power.t.test: 1714 
Simulated power at n = 1,713 per arm: 0.804 (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. Multiplicity, Missing Data and Analysis Populations

The registry record lists one primary endpoint and three secondary outcomes. It lists zero reported analyses. Although unadjusted p-values and summary comparisons are posted, a detailed statistical analysis plan, test hierarchy, or multiplicity adjustment is not reported in the registry record. It is therefore unclear whether the secondary outcomes were intended as confirmatory tests, exploratory measures, or part of a prespecified testing sequence.

Multiplicity matters because testing several outcomes creates multiple opportunities for a small p-value. Without an adjustment or a clearly defined hierarchy, an unadjusted secondary p-value should not be treated as having the same evidential role as a prespecified primary comparison. This does not make the secondary results unusable; it means their uncertainty and testing context need to be considered, and that context is not fully documented.

Missing-data handling is also not reported in the registry record. The posted primary outcome counts are 13 for warfarin and 14 for apixaban, but the record does not state whether these are all randomized participants, all participants with an available measurement, or a defined analysis population. It does not describe imputation, complete-case analysis, sensitivity analyses, withdrawals, or reasons for missing observations. No analysis population designation, such as intention-to-treat or per-protocol, is reported.

These omissions limit assessment of how robust the results are to missing outcomes or analysis choices. In a small randomized study, the influence of a missing observation can be consequential, but the record does not establish that any observations were missing. The appropriate conclusion is that the handling of missing data and the population used for analysis are not reported in the registry record, rather than assuming either that data were complete or that a particular method was used.

15. 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: death (15.4%), gastrointestinal bleeding and death (7.7%), sudden death at home (7.7%), ischemic stroke with hemorrhagic transformation and death (7.1%).

The adverse-event record lists serious adverse events affecting 4 participants in the warfarin group and 2 in the apixaban group. Other adverse events affected 1 participant in the warfarin group and 0 in the apixaban group. Deaths are listed for 4 participants receiving warfarin and 2 receiving apixaban. These are descriptive counts from a small trial; they do not by themselves establish a comparative safety effect.

The registry lists serious-event terms including Death at 15.4%, Gastrointestinal bleeding and Death at 7.7%, Sudden Death at home at 7.7%, and Ischemic Stroke with hemorrhagic transformation and death at 7.1%. The basis for the term percentages and whether event categories overlap are not reported in the registry record. They should not be added or treated as mutually exclusive categories.

The record does not provide detailed event timing, severity criteria, attribution, exposure duration, or an analysis adjusted for time at risk. Sparse counts and limited follow-up constrain interpretation. These figures describe what the registry lists; they do not establish that either treatment caused or prevented an event, nor do they support a definitive comparison of safety.

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

The posted primary result estimates the difference in mean percentage change in left ventricular thrombus size between the two randomized groups over 3 months. Both group means are negative, and the estimated contrast is -3.63. The confidence interval, from -32.62 to 25.36, is broad and includes zero. Thus, the record describes average reductions in both groups but leaves substantial uncertainty about the difference between them.

This result does not show that the treatments are equivalent. A failure to identify a clear difference is not the same as demonstrating that any difference is small enough to be unimportant. Equivalence requires a prespecified margin and an analysis designed to test it; neither is reported in the registry record. The result also does not establish superiority in either direction. The unadjusted p-value of 0.806 should not be interpreted as the probability that the treatments are the same.

The secondary outcomes do not settle the question. They involve sparse event counts, and the registry record does not report analyses or a multiplicity plan for them. Their estimates should be read as descriptive, with limited precision. The serious adverse-event figures are likewise counts from this study and cannot establish comparative safety on their own.

More broadly, the registry record does not report participant characteristics beyond the condition, detailed outcome measurement procedures, missing-data methods, analysis populations, or the original sample-size justification. Those gaps limit interpretation of the result’s generalizability and robustness. The findings describe the posted outcomes for this randomized study; they do not determine how an individual should be treated and are not medical advice.

17. Why This Trial Matters Statistically

Statistically, this study illustrates the distinction between a point estimate and the precision of that estimate. The primary comparison has a numerical direction, but its confidence interval spans values on both sides of zero and is wide. Reporting the estimate together with its interval gives a more informative account than treating the p-value alone as the result.

The study also demonstrates why a randomized design does not guarantee a precise answer when outcome groups are small. Randomization supports a structured comparison, but uncertainty remains when participant outcomes vary and the number of observations is limited. The primary standard deviations are substantial relative to the group means, and the secondary outcomes include sparse counts. These features matter when considering what the data can support.

Another statistical lesson is that outcome types require different interpretations. A continuous change measure uses the magnitude of change, while a threshold outcome classifies participants according to whether they cross a cutoff. Rare clinical events provide a different kind of evidence and can be especially uncertain when only a few events are recorded. These outcomes are complementary, not interchangeable.

Finally, the record leaves key analysis details undocumented, including the statistical plan, analysis populations, missing-data handling, and multiplicity approach. Such information helps readers assess whether the reported comparisons were prespecified and how sensitive they might be to analytic choices. The results are therefore useful as posted estimates, but their interpretation should remain calibrated to the wide primary interval and the limited detail in the registry record.

18. 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 limitations specific to this record constrain interpretation. Enrollment is listed as 27, and the posted primary outcome groups contain 13 participants for warfarin and 14 for apixaban. This is a small evidence base for estimating a mean difference and for comparing infrequent clinical events. The primary confidence interval is correspondingly broad, and the secondary outcomes have sparse counts.

The registry record does not report eligibility criteria beyond the condition, participant characteristics, thrombus measurement procedures, or the operational definition of resolution. Without those details, it is difficult to assess how the outcome was measured or to whom the results may apply. The record also does not identify who was masked, how masking was maintained, or how allocation was generated and concealed.

Although the record describes the study as randomized and outcome blinded, it does not report a statistical analysis plan, original sample-size justification, analysis population, missing-data methods, or sensitivity analyses. It lists zero reported analyses. This limits assessment of whether the posted comparisons match prespecified methods and whether the results are robust to missing observations or alternative analytic choices.

Follow-up for the stated outcomes is 3 months, so the record describes a limited timeframe. It does not report longer-term outcome data. The serious-event summaries also lack detail about timing, attribution, and the basis for the listed term percentages. Finally, the registry does not report a clinically meaningful difference threshold for the primary endpoint, making it difficult to connect the observed estimate and its interval to a predefined threshold of importance.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Apixaban Versus Warfarin in Patients With Left Ventricular Thrombus — NCT02982590.
• Registry record last updated 2021-07-08; status last verified 2021-06.
• Results first posted 2021-07-08.
• 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.

22. Record Summary

The registry record describes a completed, randomized, parallel-group phase 3 study comparing apixaban with warfarin in participants with left ventricular thrombus. It lists enrollment of 27, a single-masked, outcome-blinded design, and a 3-month primary outcome timeframe. The primary endpoint is mean percentage change in thrombus size after 12 weeks of treatment.

The primary mean difference for apixaban compared with warfarin is -3.63, with a 95% confidence interval from -32.62 to 25.36 and an unadjusted p-value of 0.806. The interval spans zero and is broad, leaving substantial uncertainty about the between-group difference. Three secondary outcomes and adverse-event summaries are also posted, but their small counts and unadjusted analyses warrant cautious interpretation.

The registry record does not report the original sample-size justification, detailed statistical plan, analysis populations, missing-data methods, or multiplicity approach. The posted results describe the recorded outcomes but do not establish superiority, equivalence, or a definitive safety comparison.