The Effect of Atorvastatin and Pioglitazone on Carotid Atherosclerosis With the Use of Positron Emission Tomography-computed Tomography (PET-CT): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effect of Atorvastatin and Pioglitazone on Carotid Atherosclerosis With the Use of Positron Emission Tomography-computed Tomography (PET-CT) (NCT01341730), a randomized phase 4 study. The primary outcome is Difference of Standardized Uptake Value (SUV) of Atherosclerotic Plaque in Carotid Artery by PET CT.

2. Clinical Question

The registry describes a prospective randomized clinical trial intended to compare the anti-inflammatory effect of atorvastatin alone with the combination of atorvastatin and pioglitazone in carotid arteries. The posted primary result is the difference in standardized uptake value (SUV) change at 3 months. The reported mean changes are -0.06 for atorvastatin alone and -0.1 for combination therapy. The posted between-group mean difference is -0.04, with a confidence interval that lies below zero and a reported unadjusted p-value of 0.042.

These figures answer a narrow imaging question. They do not, by themselves, describe changes in symptoms, cardiovascular events, or long-term outcomes. The registry lists clinical incidents among secondary outcomes, but does not post analyses for the outcomes. The record also does not report why the trial was terminated or provide a detailed account of participant flow. Accordingly, the posted imaging result should be read as a comparison of the reported group summaries rather than as a complete account of all planned outcomes or all participants.

3. Trial Design

This is a Phase 4, randomized, single-masked, parallel-group trial sponsored by The Catholic University of Korea. The registry lists enrollment of 41 and a status of terminated. The listed start was 2011-06 and primary completion was 2012-06. The record does not give a reason for termination, and the dates should not be taken as evidence about why the trial ended.

The two arms were atorvastatin 20 mg and atorvastatin 20 mg plus pioglitazone 30 mg. According to the arm descriptions, participants underwent PET-CT before randomization and were assigned to one of the two groups. Each description specifies follow-up PET-CT in 3 months. The randomization method, allocation concealment procedures, and the identity of the masked party are not reported in the registry record. “Single” masking is recorded, but the record does not explain who was masked or how masking was maintained.

The primary endpoint was the difference in carotid plaque SUV at 3 months, expressed as a mean change with standard deviation. The posted outcome groups contain 16 participants in the atorvastatin-alone arm and 17 in the combination arm. These outcome counts do not account for all 41 enrolled participants; the registry record does not provide the participant-flow information needed to explain the difference. It also does not state whether the primary analysis followed an intention-to-treat, per-protocol, or other population definition.

Three secondary outcomes are listed: change in PET-CT parameters, change in laboratory data, and clinical incidents. Results for those secondary outcomes are not posted as analyses. The registry record does not report the original sample-size justification, prespecified analysis plan, or any interim-analysis plan. The calculations shown in the sample-size section are planning illustrations based on the observed effect, 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

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: Four patients from each group withdrew the consent after enrollment.

6. Primary Endpoint

The registry lists the primary outcome as Difference of Standardized Uptake Value (SUV) of Atherosclerotic Plaque in Carotid Artery by PET CT, measured over 3 months.

The primary endpoint is the difference in standardized uptake value (SUV) of an atherosclerotic plaque in a carotid artery, assessed by PET-CT at 3 months. The posted result is expressed as a mean change from the initial evaluation, with standard deviations for the two treatment groups. SUV is a quantitative imaging measure of tracer uptake. In this trial, PET-CT was used to assess plaque-related uptake as an imaging marker relevant to the study’s stated anti-inflammatory question.

An imaging endpoint can provide a measurable outcome over the follow-up period specified in the study, while not being the same as a clinical event such as a cardiovascular incident. The registry also lists clinical incidents as a secondary outcome, but does not post an analysis for that outcome. The primary result therefore concerns an imaging measure and should be interpreted on that scale. It does not directly establish what happened to symptoms or clinical events.

The record identifies the endpoint, unit, summary measure, dispersion measure, and timeframe. It does not add a detailed description of how plaque regions were selected, how images were read, or how SUV values were processed. Those measurement and quality-control details are not reported in the registry record. The numerical comparison is consequently interpretable as a reported difference in mean SUV change, but the public record does not allow a full assessment of the imaging measurement procedures.

7. Results Posted in the Registry

• Atorvastatin 20 mg + Pioglitazone 30 mg: mean -0.10 versus -0.06 on control; difference -0.04 (95% CI -0.08 to -0.00), standardized effect d = -0.70; z-test p = 0.042.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: each participant’s plaque SUV change is summarized as a numerical quantity, and the group results are reported as means and standard deviations. A mean describes the average observed change in a group. A standard deviation describes the spread of individual observations around that group mean. The standard deviation is not the same as the uncertainty in the mean, and neither summary reveals the full distribution of measurements.

The comparison of interest is the difference between the two group means. The posted means are -0.06 for atorvastatin alone and -0.1 for combination therapy, and the posted difference is -0.04. A negative value for this contrast corresponds to a more negative average change in the combination group, based on the reported group ordering. The means describe average change; they do not say that every participant’s measurement changed in the same direction or by the same amount.

What does a mean difference summarize?

A mean difference places the two group averages on the same measurement scale. It is useful because it describes the estimated contrast directly in SUV units, rather than only saying that the groups differed. The estimate is still uncertain because it is calculated from a limited set of observations. A confidence interval represents a range of values compatible with the estimate and its sampling uncertainty under the analysis assumptions. It does not show the range of individual participant outcomes.

The posted comparison gives a standard error for each group mean and a pooled standard deviation used in the comparison. These are summary-statistic quantities: they describe uncertainty in the group means and the variability used in the unadjusted comparison. The registry record does not report a model specification, covariate adjustment, or detailed assumptions for the primary endpoint analysis. The comparison should therefore be read as an unadjusted comparison of the posted group summaries, rather than as a documented adjusted model.

What does the p-value tell us?

The unadjusted p-value is 0.042. In general, a p-value measures how unusual the observed data, or data more extreme, would be if a specified null model and its assumptions held. It is not a measure of effect size: the mean difference conveys the estimated scale of the contrast, while the p-value reflects the estimate relative to its statistical uncertainty under the model. A p-value does not establish causality on its own, describe the likelihood that the result is true, or indicate whether a change matters clinically.

The registry does not state a prespecified significance threshold for the trial’s primary analysis. A significance level of 0.05 appears in the separate planning illustration assumptions, but those assumptions are not a report of the trial’s original analysis plan. The record does not say whether the trial adjusted for multiple outcomes or repeated comparisons. This matters because interpreting a single p-value in the context of several measured outcomes depends on the analysis plan and multiplicity handling.

Why do assumptions and outcome counts matter?

Statistical comparisons rely on assumptions about the data and the analysis. For continuous outcomes, distributional shape and the suitability of the chosen summary and comparison can affect uncertainty estimates. The registry provides means and standard deviations but does not report the participant-level data, distribution plots, diagnostic checks, or a detailed analysis method. It is therefore not possible from the posted summary alone to assess the outcome distribution or verify each analysis assumption.

The posted primary groups contain 16 and 17 participants, whereas enrollment is listed as 41. The record does not explain the difference. It does not say whether all enrolled participants were randomized, whether some lacked follow-up imaging, or whether exclusions were made for analysis. Those are possibilities that cannot be resolved from this record and should not be presumed. The analysis population and missing-data handling are not reported in the registry record.

Randomization can support a fair group comparison by reducing systematic differences at assignment, but its interpretation also depends on implementation, follow-up, outcome measurement, and analysis. The record identifies the trial as randomized, but gives no method for sequence generation or concealment. Single masking is recorded without specifying who was masked. These missing details limit evaluation of potential selection or measurement influences, even though the treatment assignment is described as randomized.

What is over-dispersion, and is it relevant?

As a general statistical concept, over-dispersion occurs when observed variability is greater than a model expects. It is especially relevant for outcomes modeled as counts or rates, where an overly restrictive variance assumption can make uncertainty seem too small. The posted primary endpoint is a continuous SUV measure summarized by means and standard deviations, not a count outcome. The registry does not report a model-based dispersion assessment, so there is no basis to claim that over-dispersion was present or tested in this trial.

Similarly, general methods such as covariate adjustment, robust standard errors, or alternative distributional models can sometimes be considered for continuous outcomes, but the registry does not report using them. It is important not to infer an analysis technique from the fact that a numerical result is posted. The stated result can be described, while the unreported model details remain unknown.

How should the recalculations be understood?

The displayed planning calculations are simple unadjusted illustrations derived from the observed summary effect. They use stated planning assumptions and are separate from the trial’s original design. They do not show that the study had a particular probability of detecting its result, and they do not replace the trial’s observed estimates or uncertainty. The record does not report the original sample-size justification or the statistical plan used during conduct.

Overall, the statistical evidence is a mean difference in the designated imaging endpoint, accompanied by a confidence interval and an unadjusted p-value. A complete assessment would require information that the registry does not report, including the analysis population, missing-data methods, image measurement procedures, and the prespecified handling of multiple outcomes. These omissions do not change the arithmetic of the posted summaries; they limit how much can be learned about their robustness and broader interpretation.

10. Confidence Intervals and Precision

The posted confidence interval communicates uncertainty around the mean difference of -0.04. Its endpoints are both below zero, and the endpoint nearest zero is close to zero. Thus the interval is consistent with a negative between-group difference, but it also shows that the estimated contrast is not sharply determined. The interval’s confidence level is not reported in the registry record, so it should not be labeled with a confidence percentage that the record does not state.

A confidence interval is not a range containing a fixed proportion of individual participants’ outcomes. It describes uncertainty about the group-level contrast under the calculation’s assumptions. The standard deviations describe variability among observations, while the interval reflects uncertainty in the estimated difference. Those are related but distinct aspects of precision.

The unadjusted p-value of 0.042 is another summary of statistical uncertainty, but it does not replace the interval. The estimate and interval give a more direct view of the magnitude and range of plausible values, while the p-value condenses the comparison relative to a null model. Neither communicates clinical importance on its own. The record does not provide a threshold for a meaningful SUV change or a link between this imaging difference and clinical outcomes.

Precision also depends on the analysis population and completeness of outcome data. The posted groups include 16 and 17 participants, but participant flow and missing-data handling are not reported. As a result, the interval can be read as the uncertainty attached to the posted comparison, while the registry does not permit a fuller evaluation of how missing measurements or analysis choices might affect that uncertainty.

11. Planning a Similar Trial: Sample Size

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

The sample-size display is a planning illustration based on the observed effect, not a record of the original trial’s design calculation. Its rows consider planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For these continuous-outcome comparisons, the entries are participants per arm, not total events. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect.

For planning for 100% of the observed effect, the display gives 33 participants per arm for 80% power and 44 participants per arm for 90% power. For planning for 75% of the observed effect, it gives 58 participants per arm for 80% power and 78 participants per arm for 90% power. For planning for 50% of the observed effect, it gives 130 participants per arm for 80% power and 174 participants per arm for 90% power.

In plain terms, the 80% power column shows the illustrated number of participants per arm for a design intended to have an 80% chance of detecting the specified effect under the stated assumptions. The 90% power column uses the same interpretation at a higher target probability. Smaller effects are harder to distinguish from random variation, so the illustration requires more participants per arm when the effect to detect is reduced. These figures are not observed power and do not describe the trial’s actual operating characteristics. The registry record does not report the original sample-size justification or its design assumptions.

12. How the Sample Size Is Derived

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

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.040; pooled standard deviation σ = 0.057.
2. n = 2 × (1.96 + 0.842)² × 0.057² / -0.040² = 32.4, rounded up to 33 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 <- -0.04                      # observed difference in means
sigma <- 0.057473696648568                     # 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(1341730)
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 = 33 (80% power), 44 (90% power)
 75% of observed effect: n per arm = 58 (80% power), 78 (90% power)
 50% of observed effect: n per arm = 130 (80% power), 174 (90% power)
power.t.test: 33.4 
Simulated power at n = 33 per arm: 0.797 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome and three secondary outcomes. The secondary outcomes concern PET-CT parameters, laboratory data, and clinical incidents. It reports four outcome measures overall and zero posted analyses. The primary comparison is shown, but analyses for the listed secondary outcomes are not posted. The record does not describe whether additional outcomes or analyses were planned.

When several outcomes or comparisons are examined, the chance of obtaining at least one apparently unusual result can change. Statistical methods for handling multiplicity can account for that context, but the registry record does not report a multiplicity adjustment, a testing hierarchy, or another prespecified approach. The posted p-value of 0.042 is explicitly unadjusted, and should be read as such. The registry’s sample-size illustration uses a stated two-sided significance level of 0.05, but this does not establish the trial’s original significance threshold or multiplicity plan.

The participant counts for the primary outcome are 16 and 17, while enrollment is listed as 41. The registry does not give a flow diagram or explanation of this difference. Missing-data methods, reasons for missing measurements, and any imputation procedure are not reported in the registry record. It also does not identify the analysis population, such as whether the analysis included all randomized participants or a defined subset. These omissions prevent assessment of how the posted comparison relates to the full enrolled group.

The record identifies randomization and single masking, but does not state the random-sequence method, allocation concealment process, or who was masked. It also does not report interim analyses, stopping rules, or a detailed statistical analysis plan. These items should be treated as unknown rather than inferred from the trial’s status or numerical results. The posted primary result can be described, but the registry does not supply enough detail to reconstruct all decisions that shaped the analysis.

14. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The serious adverse event summary lists zero affected participants among 16 at risk in the atorvastatin 20 mg group and zero affected among 17 at risk in the atorvastatin 20 mg plus pioglitazone 30 mg group. No serious adverse event terms are listed. For the other adverse event category, the record also lists zero affected participants in each group, with 16 and 17 at risk respectively.

These entries describe what is posted in the registry’s adverse-event summary. They do not establish that no adverse events occurred outside the definitions or reporting scope used for the record. Death counts are not reported. The registry does not provide event-level descriptions, follow-up time for safety, ascertainment procedures, or an explanation of whether the trial’s terminated status affected safety reporting. The small posted group counts and absent detail limit what can be inferred from zero reported affected participants.

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

The posted result shows that the mean SUV change was more negative in the atorvastatin-plus-pioglitazone group than in the atorvastatin-alone group over the stated 3-month timeframe. The reported mean difference is -0.04, and the unadjusted p-value is 0.042. The confidence interval lies below zero but approaches zero, so the estimate is compatible with a range of negative differences rather than one precisely known value.

This is an imaging endpoint. The result does not directly report symptoms, clinical incidents, or longer-term outcomes. Although clinical incidents are listed as a secondary outcome, the registry does not post an analysis for them. The record also does not provide a threshold defining a clinically meaningful SUV change. A statistical difference in a measurement cannot, by itself, answer whether a difference is meaningful to patients or predicts a change in clinical outcomes.

The findings should also be viewed in light of the limited posted analysis information. The outcome groups contain 16 and 17 participants, while enrollment is 41. The registry does not explain participant flow, define the analysis population, or describe missing-data handling. It does not provide details on imaging measurement procedures or the full statistical analysis plan. Those gaps make it difficult to assess the robustness of the numerical comparison.

The registry identifies a randomized, single-masked, parallel-group Phase 4 trial, but does not state who was masked or how the randomization was implemented. Its terminated status is recorded without a reason. These registry entries should not be used to speculate about conduct or outcomes not described in the record. The defensible conclusion is limited to the posted group summaries and their stated uncertainty: a difference was reported in mean change in the imaging measure, with important questions about design detail, completeness, and clinical interpretation left unanswered by the public record.

16. Why This Trial Matters Statistically

This trial illustrates why the choice of endpoint matters. The primary outcome is a continuous imaging measure, reported as mean change and a between-group mean difference. That format allows readers to examine the direction and magnitude of the observed contrast, rather than relying only on a p-value. It also requires distinguishing the imaging result from a clinical event outcome. The posted endpoint answers a question about PET-CT SUV change, while the listed clinical incidents are not analyzed in the posted results.

The example also shows why precision and analysis context belong alongside an estimate. The posted mean difference is -0.04 and the unadjusted p-value is 0.042, but the interval comes close to zero and the record does not report its confidence level. The number of outcome participants differs from total enrollment, without a participant-flow explanation. Readers can describe the displayed result while recognizing that the public record does not document the analysis population or missing-data approach.

Finally, the sample-size illustrations make a useful distinction between observing a result and planning a future study. They use fractions of the observed effect and stated design assumptions, but are not the original trial’s justification or observed power. The registry does not report the trial’s own design assumptions. This distinction is important when interpreting planning figures: they help show how the required sample size changes with the effect being targeted, but they do not retrospectively establish the adequacy of the completed trial.

For biostatistical reading, the central lesson is to keep the outcome scale, estimate, uncertainty, and reporting gaps together. A numerical result can be informative without supporting conclusions beyond the endpoint and analysis actually posted.

17. Limitations

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

Several limitations specific to this record affect interpretation. First, the registry lists enrollment of 41, whereas the primary outcome summaries include 16 participants in the atorvastatin-alone group and 17 in the combination group. Participant flow, reasons for the smaller outcome counts, and missing-data handling are not reported. The difference cannot be attributed to any particular cause from the information available.

Second, the record does not report the analysis population, a detailed statistical analysis plan, or methods for handling multiple outcomes. The comparison is presented with an unadjusted p-value, but the registry does not document whether covariate adjustment or other analysis choices were prespecified. The confidence interval level is also not reported.

Third, information about implementation is limited. Randomization and single masking are recorded, but sequence generation, allocation concealment, and the identity of the masked party are not specified. The record does not describe PET-CT image-reading procedures, plaque selection, or quality control. These omissions make it difficult to evaluate potential influences on assignment, measurement, and analysis.

Fourth, the trial is listed as terminated, with no reason given. The record lists secondary outcomes but does not post their analyses. It does not report death counts. These absences constrain interpretation and should not be filled by speculation. The posted result is therefore best treated as a short-term comparison of the reported primary imaging summaries, with design and reporting details unavailable in the registry record.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: The Effect of Atorvastatin and Pioglitazone on Carotid Atherosclerosis With the Use of Positron Emission Tomography-computed Tomography (PET-CT) — NCT01341730.
• Registry record last updated 2020-08-06; status last verified 2020-07.
• Results first posted 2020-08-06.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

NCT01341730 is a randomized, single-masked, parallel-group Phase 4 trial sponsored by The Catholic University of Korea. It compared atorvastatin 20 mg alone with atorvastatin 20 mg plus pioglitazone 30 mg in a study of carotid atherosclerosis. The registry lists enrollment of 41, a terminated status, and a primary completion date of 2012-06.

The primary endpoint was change in carotid plaque SUV on PET-CT at 3 months. The posted group means were -0.06 and -0.1, and the mean difference was -0.04, with an unadjusted p-value of 0.042. The outcome summaries include 16 and 17 participants. Three secondary outcomes are listed, but their analyses are not posted. The registry does not report the reason for termination, participant flow, analysis population, missing-data methods, or the original sample-size justification.