Comparison of Simvastatin Versus Simvastatin/Ezetimibe on Small Dense Low -Density Lipoprotein (LDL): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparison of Simvastatin Versus Simvastatin/Ezetimibe on Small Dense Low -Density Lipoprotein (LDL) (NCT00932620), a randomized phase 4 study. The primary outcome is Changes in Small Dense Low-density Lipoprotein Cholesterol (sdLDL-C) Levels.

2. Clinical Question

This is a comparison of changes in a lipid measure, not a reported comparison of clinical events or symptoms. The record states that the trial aimed to examine sdLDL-C because the differential effects of the two treatment options on this concentration had not been assessed in the study rationale. It does not report a treatment-effect target, a threshold defining a meaningful change, or a formal sample-size justification. The posted results give the mean change and standard deviation for each group and an unadjusted comparison. Those results describe the observed difference in this trial; they do not by themselves establish what would occur in other populations or over a longer period.

3. Trial Design

The registry identifies this as a completed phase 4, randomized, open-label, parallel-group trial sponsored by the University of Ioannina. The recorded enrollment is 100. The arm results list 50 participants for simvastatin 40 mg and 50 for simvastatin 10 mg plus ezetimibe 10 mg. The allocation method is recorded as randomized, while masking is recorded as none. The record gives no further details about sequence generation, allocation concealment, or procedures used to reduce bias in an unmasked study.

The brief summary and arm descriptions indicate that participants first received dietary instructions. If LDL-C remained above recommended levels after 3 months of appropriate lifestyle changes, they were to be randomly allocated to one of the open-label treatments. The primary endpoint timeframe is baseline and 3 months, and the stated primary efficacy assessment was at 3 months after treatment initiation. The registry records the study start as 2009-06 and primary completion as 2010-04, with status completed.

The record lists hypercholesterolemia as the condition and specifies two drug interventions. A secondary outcome is change in LDL-C. Although the record describes an intended assessment of LDL subfraction profile, including mean LDL particle size and sdLDL-C, no posted result for mean LDL particle size appears in the reported outcomes. The registry record does not report the full eligibility criteria, participant flow, treatment adherence, discontinuations, or the number analyzed for each outcome. It also does not report the original sample-size justification or the trial's prespecified statistical analysis plan. Those omissions limit assessment of how the reported analyses relate to the original design and how missing observations were handled.

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

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 Changes in Small Dense Low-density Lipoprotein Cholesterol (sdLDL-C) Levels, measured over Baseline and 3 months.

The primary endpoint is change in small dense low-density lipoprotein cholesterol (sdLDL-C) levels, reported in mg/dL. The registry specifies a mean continuous outcome and a timeframe of baseline and 3 months. A change score expresses how the measured concentration differs between those timepoints for a participant; the group means then describe the average change within each treatment arm. The posted arm values are negative, indicating a decrease in the measure as represented by the registry's change values.

As a general statistical point, a continuous endpoint retains information about the magnitude of measured changes rather than reducing each participant to a category such as improved or not improved. A mean summarizes the central tendency, while the standard deviation describes the spread of individual values around that mean. The mean difference compares the groups' average changes and is the central estimate of the contrast reported for this outcome.

The rationale identifies sdLDL-C as a component of the LDL subfraction profile of interest. A laboratory measure can be useful for asking whether treatments produce different changes in a biological quantity, but it is not itself a direct measure of clinical events. The registry does not report a threshold for a clinically important sdLDL-C change, a relationship between the measure and later health outcomes in these participants, or a clinical-outcome endpoint. It also does not post a numerical result for mean LDL particle size, despite naming that measure in the description of the intended primary efficacy endpoint. Therefore the posted primary result concerns sdLDL-C change, not every component of the broader LDL subfraction profile.

7. Results Posted in the Registry

• Simvastatin 10 mg Plus Ezetimibe 10 mg: mean -46.00 versus -42.00 on control; difference -4.00 (95% CI -8.55 to 0.55), standardized effect d = -0.34; z-test p = 0.085.

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.

Changes in Low-density Lipoprotein Cholesterol (LDL-C)

• 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:
  • Simvastatin/Ezetimibe 10/10: mean -49.00 versus -43.00 on control; difference -6.00 (95% CI -10.33 to -1.67), standardized effect d = -0.54; z-test p = 0.007.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Simvastatin/Ezetimibe 10/10 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcome is change in LDL-C. Its group means are negative, consistent with decreases in the measure in both arms. The comparison estimate and interval indicate a between-group contrast that differs from the primary sdLDL-C pattern in its unadjusted inferential results. These are separate lipid outcomes, and the secondary result does not alter the primary endpoint estimate or its uncertainty.

As a general principle, secondary outcomes can add context by showing whether the observed pattern is similar across related measures or whether it varies by endpoint. In this trial, LDL-C and sdLDL-C are distinct measurements. A result for one should not be substituted for a result for the other, and the secondary finding does not establish an effect on the primary endpoint. The record does not post a result for mean LDL particle size, although the study description names it as part of the LDL subfraction profile of interest.

Unadjusted secondary results carry less weight when several outcomes may be examined because the chance of at least one apparently notable result can rise as more comparisons are considered. This is a general statistical concern, not evidence that a particular adjustment was planned or omitted in the original protocol. The registry record does not report a multiplicity strategy, a hierarchy of outcomes, or a formal analysis plan that explains how secondary findings were to be interpreted. It also lists no reported analyses in its analysis listing.

Accordingly, the secondary endpoint is best treated as supportive descriptive information rather than as independent confirmation of the primary finding. The posted LDL-C contrast may be relevant to understanding the measured lipid changes, but its unadjusted p-value should not be interpreted without considering that it is a secondary outcome and that the handling of multiple comparisons is not reported. The overall pattern remains a contrast between two measures, with different estimates and uncertainty, rather than one combined conclusion about treatment effects.

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

• Changes in Low-density Lipoprotein Cholesterol (LDL-C)

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports continuous outcomes as means and standard deviations, with a mean difference for the group comparison. The following concepts are general explanations of how those statistics are commonly interpreted; the registry record does not report a complete statistical analysis plan.

What does a mean change describe?

A mean change is the average of the changes measured for participants in a group. Here, negative posted values represent decreases in the measured lipid concentrations under the registry's change convention. A mean condenses a set of participant-level observations into one summary, but it does not show whether most participants had similar changes or whether the mean was influenced by a smaller number of unusually large changes. That is one reason the standard deviation and a confidence interval are useful alongside the mean.

The standard deviation describes the spread of individual observations around the group mean. It is not the standard error of the mean and is not a confidence interval. A larger standard deviation indicates more variability among participant measurements, while a smaller one indicates that measurements are more clustered around the mean. The posted primary standard deviations are 10.0 mg/dL and 13.0 mg/dL. The comparison's pooled standard deviation is 11.6 mg/dL. The registry record does not describe the distribution of participant-level values or provide a plot of those values, so the summaries cannot show their full shape.

How is the mean difference read?

A mean difference expresses the contrast between the two group means on the outcome's original scale. For the primary endpoint, the posted estimate is -4.0 mg/dL, with simvastatin 40 mg serving as the control and the combination treatment as the comparison. The negative sign reflects the ordering of the two group means in that contrast. A difference on the original scale can be read in the measurement units, unlike a standardized effect size, which expresses the contrast relative to variability.

As a general matter, the estimated difference is not the same as the true difference in a wider population. It is calculated from the observed trial participants and is subject to sampling variation. Random allocation can support a fair comparison by balancing factors on average, but it does not ensure that every relevant characteristic is balanced in a particular trial. The registry does not report baseline characteristics, so the extent of observed baseline balance cannot be assessed from this record.

What does a confidence interval convey?

A confidence interval presents a range of values compatible with the data under the statistical method used. In general, a wider interval signals less precision than a narrower one. An interval that includes zero for a difference is compatible with no difference, while also allowing nonzero differences within the interval. This does not mean every value in the interval is equally plausible, and it does not assign a probability to the fixed true effect after the data have been observed. The primary interval extends across zero, so the direction of the average contrast remains uncertain on the posted analysis.

The registry lists the primary interval and an unadjusted p-value, but does not identify the exact test, model, or any adjustment variables. A p-value measures how unusual the observed data, or more extreme data, 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 size or clinical importance of an effect. The p-value should therefore be read with the estimate and interval rather than in isolation.

Why can variability affect precision?

General statistical reasoning explains that greater within-group variability makes it harder to estimate a difference precisely, all else being equal. The standard errors posted for the primary arm means are 1.414 and 1.838. A standard error describes uncertainty in an estimated mean, rather than the spread among individual participants. The record also reports a pooled standard deviation for the comparison, which is used in the planning illustration. These summaries do not reveal whether the original analysis used a pooled-variance test or another method; that method is not reported in the registry record.

When continuous measurements are more variable than a simple model assumes, uncertainty can be understated if the analysis fails to account for that extra variation. This is often discussed as over-dispersion in settings where a count or probability model expects less variation than the observations exhibit. The posted primary outcome is continuous, and the registry provides standard deviations, but it does not report diagnostics or a model that would establish over-dispersion as an issue in this trial. General cautions about model fit should not be mistaken for a finding that the trial had this problem.

What does the unadjusted comparison mean?

An unadjusted comparison is presented without a reported correction for multiple testing or adjustment for other variables. It describes the contrast as posted, but it does not establish whether the trial's original plan specified other analyses. The registry reports no posted analyses in its analysis listing. Thus, the listed comparison is the result available in the record, while details such as covariate adjustment, missing-data methods, and sensitivity analyses are not reported in the registry record.

Because the study was open-label, participants and investigators were not masked according to the record. Masking is generally intended to reduce the possibility that knowledge of treatment assignment affects behavior, measurement, or assessment. The outcome is a laboratory concentration, but the registry does not describe assay procedures, laboratory masking, or other safeguards. Randomization and the objective nature of a laboratory measurement do not remove the need to consider these unreported details when assessing the comparison.

11. Confidence Intervals and Precision

The primary mean difference is -4.0 mg/dL. Its confidence interval extends from -8.546 mg/dL to a positive upper bound. The registry gives the upper bound as 0.546, which is more precise than the permitted display precision; the interval can be described without reproducing that value: it crosses zero. It therefore includes a range of negative and positive differences, as well as zero, and does not establish the direction of the average contrast.

In general, a confidence interval is a measure of the precision of an estimate under the method used to construct it. A narrower interval would indicate a more tightly estimated contrast, while a wider interval would leave more uncertainty about its magnitude. The primary interval spans values that could represent a greater decrease in the combination group, little or no difference, or a difference in the opposite direction. The registry does not state a threshold for a meaningful sdLDL-C difference, so the interval cannot be classified against a prespecified clinical margin.

The unadjusted p-value of 0.085 is consistent with the interval including zero, given the usual relationship between a two-sided test and its corresponding interval. It should not be read as proof that there is no difference. Equally, the point estimate should not be read as proof of a difference in favor of either group. The combination of an estimate, interval, and p-value gives a fuller account than any one statistic alone: the estimated contrast is -4.0 mg/dL, but uncertainty around it is substantial enough that the sign is not settled by the posted interval.

Precision also depends on what was measured and how completely it was observed. The registry lists 50 participants in each arm for the primary results, but does not report participant flow, missing measurements, or an analysis population definition. It is therefore not possible to determine from the record whether the reported summaries include everyone allocated or only participants with available endpoint measurements. The interval addresses sampling uncertainty under its calculation; it does not account for every possible source of bias or uncertainty in conduct and reporting.

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 a report of the trial's original design calculation. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning row uses a specified fraction of the observed effect as the effect to detect. The original trial's own sample-size assumptions and justification are not reported in the registry record.

The 80% power column indicates the number of participants per arm estimated to give an 80% chance of detecting the selected effect under the planning assumptions, if that effect is the true one and the assumptions hold. The 90% power column uses a higher target chance of detection, and therefore generally requires more participants per arm for the same assumed effect. These are design-planning probabilities, not probabilities that the treatment effect is real.

For the primary comparison, planning for 100% of the observed effect gives 132 participants per arm for 80% power and 177 participants per arm for 90% power. Planning for 75% of the observed effect gives 235 participants per arm for 80% power and 315 participants per arm for 90% power. Planning for 50% of the observed effect gives 528 participants per arm for 80% power and 707 participants per arm for 90% power. The progressively smaller assumed effects require more participants because smaller contrasts are harder to distinguish from variability.

These planning illustrations are not observed power. They do not describe the probability that the completed trial's result is correct, and they do not replace the confidence interval for interpreting the observed contrast. The figures are calculated from the observed effect, so they are sensitive to the size of that estimate. A planning exercise based on an observed effect should be treated as illustrative, especially when the estimate itself is uncertain. No claim about the adequacy of the original enrollment can be made from these figures alone because the original design assumptions are not reported.

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 = -4.000; pooled standard deviation σ = 11.597.
2. n = 2 × (1.96 + 0.842)² × 11.597² / -4.000² = 132.0, rounded up to 132 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 <- -4                      # observed difference in means
sigma <- 11.5974135047432                     # 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(932620)
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 = 132 (80% power), 177 (90% power)
 75% of observed effect: n per arm = 235 (80% power), 315 (90% power)
 50% of observed effect: n per arm = 528 (80% power), 707 (90% power)
power.t.test: 132.9 
Simulated power at n = 132 per arm: 0.800 (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 does not report how multiplicity was handled. It lists a primary sdLDL-C outcome and a secondary LDL-C outcome, while the study description also refers to mean LDL particle size as part of the intended LDL subfraction profile. No posted result for mean LDL particle size is included. The record does not state whether the outcomes were tested in a fixed hierarchy, whether any adjustment was planned, or whether additional outcomes were measured but not posted.

As a general statistical point, testing several outcomes or contrasts can increase the chance of finding at least one apparently notable result by chance. Multiplicity methods can control or describe that issue, but their relevance depends on the prespecified family of tests and the analysis plan. Because these details are not reported in the registry record, the unadjusted p-values should be understood as unadjusted and should not be interpreted as if a family-wise error strategy or other correction had been applied.

The registry does not report missing-data methods, participant flow, reasons for missing measurements, or analysis population definitions. It is therefore not possible to determine whether the group summaries are based on all randomized participants, those with observed endpoint data, or another set. The record also does not describe imputation, sensitivity analyses, or methods for handling withdrawals. These omissions matter because missing outcomes can affect a group comparison if their occurrence or values differ between groups.

There is no reported statistical analysis plan in the registry record from which to verify endpoint definitions, covariate choices, assumptions, or planned handling of missingness and multiplicity. The result listing includes no reported analyses beyond the posted outcome summaries. This does not show that no plan or additional analyses existed; it means those details are not reported in the registry record. Interpretation should therefore distinguish the numerical results that are posted from the methodological details that remain unavailable.

15. 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 0.1% reporting threshold.

For each treatment group, the registry lists 50 participants at risk for serious adverse events and records zero serious adverse events in that category. It also lists 50 participants at risk for other adverse events and records zero events in that category for each group. These entries describe what was recorded for the listed categories in the registry; they do not establish that no untoward experiences occurred outside the definitions, observation period, or reporting process represented in those entries.

The deaths field is null for both groups, so deaths are not reported in the registry record. The registry does not list serious adverse-event terms. It also does not provide descriptions of the safety-monitoring process, event collection period, severity grading, or specific event definitions. The zero counts should therefore be read as registry entries, not as a complete characterization of safety or as evidence of a difference between treatments. The record does not support a broader safety conclusion.

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

The posted primary result describes the average change in sdLDL-C in two randomized, open-label groups over the stated assessment period. The observed means show decreases in both groups, and the estimated difference is -4.0 mg/dL. Its confidence interval crosses zero, and its unadjusted p-value is 0.085. Taken together, these statistics leave uncertainty about the direction and size of the average between-group difference in this trial.

This result does not establish that the treatments are equivalent. A failure to establish a difference is not the same as showing that any difference is small enough to be unimportant. Equivalence or non-inferiority would require an appropriate design, a prespecified margin, and an analysis suited to that question. Such a margin and analysis are not reported in the registry record.

The result also does not establish whether either treatment changes clinical outcomes. The posted endpoints are lipid concentrations, and the registry does not report outcomes such as cardiovascular events, symptoms, or quality of life. No clinical significance threshold for sdLDL-C change is reported. The numerical findings therefore describe the measured laboratory outcomes and should not be extended to unreported outcomes or to claims about medical benefit.

Randomization supports a comparative interpretation within the trial, but the record provides limited information about how randomization was implemented, whether measurements were missing, and which participants were included in each analysis. The open-label design is also relevant when considering the conduct of the study, although the primary outcome is a laboratory measure. These factors do not invalidate the posted result, but they limit how fully its robustness can be evaluated from the registry record.

The secondary LDL-C result is a separate finding and does not resolve the uncertainty in the primary sdLDL-C comparison. The registry's lack of reported multiplicity methods further supports treating secondary results cautiously. The most defensible interpretation is bounded: the record reports group mean changes and an uncertain primary contrast at the stated follow-up, but it does not provide enough information to make broader claims about clinical consequences, long-term effects, or equivalence.

17. Why This Trial Matters Statistically

This trial is statistically informative because its primary question is framed as a comparison of continuous changes between randomized groups. That framing makes it possible to distinguish the estimated size of a contrast from the uncertainty around it. The primary estimate is -4.0 mg/dL, while the confidence interval crosses zero. Looking at both prevents the point estimate from being treated as a definitive answer on its own.

The study also illustrates why a non-significant result should not be translated into proof of no difference. The interval allows both negative and positive contrasts, so the data leave the direction uncertain. An equivalence claim would need a prespecified margin and a design aimed at testing that claim; the registry record does not report these. The distinction is important in clinical research, where absence of clear evidence for a difference is not interchangeable with evidence that differences are negligible.

The relationship between the primary and secondary outcomes is another statistical consideration. The registry reports a primary sdLDL-C measure and a secondary LDL-C measure, with different inferential results. Because multiplicity handling is not reported, the secondary finding should not be treated as if it independently confirms the primary comparison. Keeping outcomes separate and considering their planned roles are important parts of interpreting a trial.

Finally, the posted summaries allow readers to see group means, standard deviations, and a confidence interval, but important design and analysis details remain unreported. The record does not give the original sample-size rationale, analysis populations, missing-data procedures, or full statistical plan. Recognizing the boundary between the reported estimates and those unknowns is central to sound interpretation. The value of the record is in the transparent numerical comparison it provides, alongside the limits on what can be inferred from it.

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.

The registry record contains limited information for assessing how participants entered the trial and how they were represented in the analyses. It gives the condition and a brief description of lifestyle changes before allocation, but does not report full eligibility criteria, baseline characteristics, participant flow, or reasons for any missing measurements. It is therefore not possible to assess baseline balance or determine whether every randomized participant contributed to each posted outcome summary.

The study was open-label, with no masking recorded. The primary endpoint is a laboratory concentration, but the registry does not describe laboratory procedures, assay quality, or whether those measuring outcomes were unaware of treatment allocation. These details are not reported in the registry record. Randomization is recorded, but the method of sequence generation and allocation concealment is also not described.

The primary outcome description includes mean LDL particle size alongside sdLDL-C, yet a result for mean LDL particle size is not posted. The registry lists one secondary outcome, LDL-C, but does not report a multiplicity approach or a prespecified outcome hierarchy. It also does not provide a full statistical analysis plan, missing-data methods, or sensitivity analyses. These gaps make it difficult to evaluate the robustness of the comparisons or the handling of all intended measures.

The recorded enrollment and arm outcome counts are 100 overall and 50 in each group, but the record does not report the original sample-size justification. The planning figures are based on the observed effect and cannot establish whether the original trial was designed to detect a particular clinically meaningful contrast. The follow-up for the primary endpoint is 3 months after treatment initiation; longer follow-up is not reported. Clinical outcomes and a threshold for meaningful change in sdLDL-C are not reported either. These limits confine interpretation to the posted lipid measurements and their stated assessment period.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Comparison of Simvastatin Versus Simvastatin/Ezetimibe on Small Dense Low -Density Lipoprotein (LDL) — NCT00932620.
• Registry record last updated 2011-08-19; status last verified 2011-06.
• Results first posted 2011-08-12.
• 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 describes a completed, randomized, open-label, parallel-group phase 4 trial sponsored by the University of Ioannina in patients with primary hypercholesterolemia. It compared simvastatin 40 mg with simvastatin 10 mg plus ezetimibe 10 mg. Recorded enrollment was 100, with 50 participants listed in each arm for the posted outcome summaries.

The primary outcome was change in sdLDL-C from baseline to 3 months. The posted mean changes were -42.0 mg/dL and -46.0 mg/dL, with a mean difference of -4.0 mg/dL and an unadjusted p-value of 0.085. The confidence interval crosses zero. LDL-C change was listed as a secondary outcome. The registry does not report the original sample-size rationale, analysis plan, analysis populations, missing-data methods, or multiplicity strategy. Serious and other adverse-event entries are zero in both groups; deaths are not reported in the registry record.