Evaluate Safety and Efficacy of ABT-335 in Combination With Simvastatin in Subjects With Multiple Abnormal Lipid Levels in the Blood: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluate Safety and Efficacy of ABT-335 in Combination With Simvastatin in Subjects With Multiple Abnormal Lipid Levels in the Blood (NCT00300456), a randomized phase 3 study. The primary outcome is Mean Percent Change in Triglycerides From Baseline to Final Visit.

2. Clinical Question

3. Trial Design

This was a phase 3, multicenter, randomized, double-blind, prospective, parallel-group study. The registry record identifies masking as triple. Its stated purpose was to compare the safety and efficacy of ABT-335 plus simvastatin combination therapy with ABT-335 and simvastatin monotherapy in subjects with multiple abnormal lipid levels in the blood. The trial is listed as completed, with enrollment of 657. The recorded start was 2006-03 and primary completion was 2007-03.

Six treatment groups are described: ABT-335 plus 20 mg simvastatin, ABT-335 plus 40 mg simvastatin, ABT-335 alone, and simvastatin alone at 20 mg, 40 mg, or 80 mg. The primary outcome results use group-specific analysis populations, so the number contributing to the triglyceride outcome differs by arm. These outcome counts should not be treated as the overall enrollment or as a complete description of how many participants received each treatment.

The primary outcome was measured from baseline to 12 Weeks (Final Visit). The primary population included randomized subjects with a baseline triglyceride value and at least 1 postbaseline triglyceride value, using last observation carried forward. Other posted outcomes include non-HDL-C, VLDL-C, total cholesterol, Apo B, and hsCRP. The registry record does not report the original sample-size justification, the detailed allocation procedure, or additional operational details beyond the design characteristics stated above.

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.

Before assignment: Seven subjects were randomized but never treated: 2 were taking a prohibited concomitant medication, 1 did not meet the entry criteria for lipid levels, 1 had an abnormal baseline electrocardiogram, 1 was unable to swallow pills, and 2 withdrew consent.

Overall Study

Analysis population for the primary outcome, as defined in the registry: All randomized subjects with a baseline triglyceride value and at least 1 postbaseline triglyceride value, last observation carried forward

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.

Only the first 6 of 7 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Mean Percent Change in Triglycerides From Baseline to Final Visit, measured over Baseline to 12 Weeks (Final Visit).

The primary endpoint is mean percent change in triglycerides from baseline to the 12-week final visit. For each included subject, the outcome is calculated as the week 12 triglyceride value minus the baseline value, divided by the baseline value, then multiplied by 100. A negative group mean therefore represents an average reduction relative to baseline; a more negative mean represents a larger average percentage reduction in this measure. This describes the outcome scale, not the clinical importance of any particular change.

Triglycerides are one of the lipid measures named in the study’s objective, and the endpoint provides a continuous summary of change across participants. Reporting a mean allows the group-level average to be compared across treatment arms. The standard error describes the estimated uncertainty in that mean, rather than the spread of individual participants’ changes.

The outcome population was not every randomized subject by definition. It included randomized subjects with a baseline triglyceride value and at least 1 postbaseline triglyceride value, with last observation carried forward used for missing follow-up information. The registry record does not report the detailed rules for applying this procedure beyond that description. The endpoint is a measure of change over the stated period; it does not by itself establish longer-term effects, patient-important benefit, or safety.

7. Results Posted in the Registry

• ABT-335 + 40 mg Simvastatin: mean -42.70 versus -37.40 on control; difference -5.30 (95% CI -12.95 to 2.35), standardized effect d = -0.18; z-test p = 0.175.
• ABT-335: mean -31.70 versus -37.40 on control; difference 5.70 (95% CI -1.91 to 13.31), standardized effect d = 0.20; z-test p = 0.142.
• 20 mg Simvastatin: mean -14.20 versus -37.40 on control; difference 23.20 (95% CI 15.63 to 30.77), standardized effect d = 0.79; z-test p = <0.001.
• 40 mg Simvastatin: mean -22.40 versus -37.40 on control; difference 15.00 (95% CI 7.36 to 22.64), standardized effect d = 0.51; z-test p = <0.001.

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.

Mean Percent Change in Non-high-density Lipoprotein Cholesterol (Non-HDL-C) From Baseline to Final Visit

• 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 errors.
• Result:
  • ABT-335 + 40 mg Simvastatin: mean -35.00 versus -30.70 on control; difference -4.30 (95% CI -8.40 to -0.20), standardized effect d = -0.28; z-test p = 0.040.
  • ABT-335: mean -17.30 versus -30.70 on control; difference 13.40 (95% CI 9.33 to 17.47), standardized effect d = 0.89; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for ABT-335 + 40 mg Simvastatin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for ABT-335 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Mean Percent Change in Very Low-density Lipoprotein Cholesterol (VLDL-C)From Baseline to Final Visit

• 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 errors.
• Result:
  • ABT-335 + 40 mg Simvastatin: mean -51.10 versus -38.90 on control; difference -12.20 (95% CI -23.41 to -0.99), standardized effect d = -0.29; z-test p = 0.033.
  • ABT-335: mean -36.90 versus -38.90 on control; difference 2.00 (95% CI -9.23 to 13.23), standardized effect d = 0.05; z-test p = 0.727.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for ABT-335 + 40 mg Simvastatin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between ABT-335 and the control. The interval gives the range of effects that remain compatible with the data.

Mean Percent Change in Total Cholesterol From Baseline to Final Visit

• 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 errors.
• Result:
  • ABT-335 + 40 mg Simvastatin: mean -27.10 versus -23.90 on control; difference -3.20 (95% CI -6.54 to 0.14), standardized effect d = -0.25; z-test p = 0.060.
  • ABT-335: mean -12.40 versus -23.90 on control; difference 11.50 (95% CI 8.17 to 14.83), standardized effect d = 0.90; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between ABT-335 + 40 mg Simvastatin and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for ABT-335 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes cover several additional lipid measures and hsCRP. Across the lipid outcomes, the group means generally show negative percent changes, but the relative ordering of the combination and monotherapy groups is not uniform across measures. This means the secondary results should be read as outcome-specific patterns rather than as one consistent ranking of every treatment group. The secondary endpoint comparisons also have their own analysis populations, which vary across measures.

These outcomes add context to the primary triglyceride result by describing changes in other lipid measures over the same stated period. They do not change the definition of the primary endpoint, and they cannot be treated as independent confirmation of it: outcomes may be related, and several measures and group comparisons were examined. The registry record lists five secondary outcomes, but sponsor-reported analyses are not listed for the secondary comparisons included in the posted summary statistics.

Unadjusted secondary results carry less weight because multiple outcomes and comparisons create more opportunities for apparently notable findings by chance. The registry record does not report a multiplicity adjustment or a prespecified hierarchy for interpreting the secondary endpoints. In addition, the recalculated confidence intervals and p-values are based on posted summaries rather than the sponsor's full analysis models. These results are useful for describing patterns and generating questions, but should not be treated as equivalent to a single confirmatory primary analysis.

For the same reasons, a secondary result that appears statistically distinct in an unadjusted comparison does not establish clinical importance or a reliable effect across all endpoints. Interpretation depends on the outcome, the comparison, its uncertainty, the analysis population, and the broader multiplicity context.

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

• Mean Percent Change in Non-high-density Lipoprotein Cholesterol (Non-HDL-C) From Baseline to Final Visit
• Mean Percent Change in Very Low-density Lipoprotein Cholesterol (VLDL-C)From Baseline to Final Visit
• Mean Percent Change in Total Cholesterol From Baseline to Final Visit
• Mean Percent Change in Lipoprotein Apo B (Apo B) From Baseline to Final Visit
• Median Percent Change in High-sensitivity C-reactive Protein (hsCRP) From Baseline to Final Visit

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: each participant contributes a percentage change, and the reported arm result is the mean of those values. A mean is a measure of central tendency, while its standard error describes uncertainty in the estimated mean. A standard error is not the same as a standard deviation: the latter describes variation among individual values, whereas the former describes how precisely the group mean is estimated.

What does a mean difference express?

A mean difference compares the average outcome in one arm with the average in a reference arm. In these recalculations, the estimate is the comparison-arm mean minus the reference-arm mean. The sign therefore depends on both the order of the comparison and the outcome scale. For a percent-change outcome where negative values represent reductions, a negative difference indicates a more negative average in the comparison arm; a positive difference indicates a less negative average. The sign alone does not indicate clinical importance.

The recalculated estimates are unadjusted calculations from posted group means and standard errors. They do not account for participant-level covariates or reproduce the sponsor's ANCOVA model. Their confidence intervals and p-values should therefore be read as separate, summary-statistic comparisons. The registry's sponsor-reported ANCOVA results are available for two comparisons and take precedence for those comparisons, particularly because the registry record flags a discrepancy between reported analyses and recalculations.

How should the confidence intervals and p-values be read?

A confidence interval gives a range of values compatible with the estimate under the calculation's assumptions. A narrower interval indicates greater precision than a wider one, but precision alone does not establish clinical relevance. If a mean-difference interval includes zero, the posted data are compatible with no difference as well as with differences in either direction within the interval. If the interval excludes zero, that is evidence against a zero difference under the unadjusted calculation; it does not account for the number of comparisons or prove that the difference matters to patients.

A p-value measures how incompatible the observed statistic is with a specified null hypothesis under the model used. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. The unadjusted p-values in the recalculations do not include a correction for multiple comparisons. Sponsor-reported p-values come from ANCOVA and should not be interpreted as if they were generated by the recalculated method.

What does ANCOVA contribute?

Analysis of covariance, or ANCOVA, compares outcomes between groups while incorporating covariate information into the model. It can estimate an adjusted group contrast and may account for baseline measurements or other prespecified variables if those variables are included. The registry record identifies ANCOVA for two comparisons but does not report the model covariates, detailed model specification, or effect estimates and confidence intervals for those analyses. It is therefore not possible to reconstruct the sponsor's adjusted results from the reported p-values alone.

Why distinguish analysis populations and missing-data methods?

The primary population required a baseline triglyceride value and at least 1 postbaseline value. Last observation carried forward uses an earlier observed measurement to represent a later missing measurement. This approach makes an analysis possible when follow-up measurements are missing, but it relies on assumptions about how the outcome would have changed after the last measurement. The registry record does not report the extent or pattern of missing data, or sensitivity analyses evaluating alternative missing-data assumptions.

Group-specific outcome counts can differ because not all participants contribute usable data for every measure. The counts associated with the primary endpoint therefore describe its analysis population, not necessarily all randomized participants. The registry record does not report further details on exclusions from the endpoint analysis.

Why can variability affect comparisons?

General statistical explanation: greater variability among individual outcomes makes it harder to estimate a group mean precisely, all else being equal. Unequal group sizes can also affect precision, particularly when the smaller group carries less information. The reported standard errors provide information about uncertainty in the arm means, but the posted aggregate results do not reveal the full distribution of individual triglyceride changes or whether model assumptions were checked.

Because several arms and outcomes were evaluated, interpreting any one unadjusted result in isolation can overstate the strength of evidence. The registry record does not report a multiplicity adjustment or a complete statistical analysis plan. The stated methods and reported results therefore support a descriptive reading of the endpoints and cautious interpretation of unadjusted comparisons, rather than a claim that all possible comparisons were confirmatory.

11. Confidence Intervals and Precision

The arm means are accompanied by standard errors, which indicate the precision of each estimated average. For the primary outcome, the standard errors range from 2.71 to 3.82 across the six groups. The larger standard error in the 80 mg simvastatin group accompanies a smaller endpoint analysis count than in the other arms. Standard errors are uncertainty measures for means, not ranges containing most individual participants' results.

Recalculated mean-difference confidence intervals provide a direct view of uncertainty in selected between-arm contrasts. For ABT-335 plus 40 mg simvastatin versus the reference combination, the interval runs from -12.95 to 2.35. For ABT-335 alone versus the reference combination, it runs from -1.909 to 13.31. Both include zero and allow for differences in either direction. The comparisons with simvastatin monotherapy have intervals that exclude zero, but they remain unadjusted recalculations and do not account for multiple testing.

Confidence intervals are more informative than a significance label alone because they show the range of effect estimates compatible with the data under the calculation's assumptions. Their width reflects precision, not whether an effect is clinically meaningful. The sponsor's reported ANCOVA analyses are stated to have 95% confidence intervals, but their limits and effect estimates are not reported in the registry record. Consequently, the ANCOVA p-values cannot show the size or precision of those adjusted contrasts.

Precision also depends on the analysis population, variability, and model. The reported results do not provide participant-level distributions, missing-data patterns, or enough detail to assess all model assumptions. The available intervals should be read as uncertainty around the stated comparisons, not as guarantees about the true effect.

12. Planning a Similar Trial: Sample Size

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

The sample-size illustrations are planning calculations based on the observed effect, not the trial's original design. The registry record does not report the trial's own sample-size justification or original design assumptions. The listed assumptions for these illustrations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is expressed as a stated fraction of the observed effect. For these continuous outcomes, the figures are participants per arm, not total events.

The 80% power column gives the estimated participants per arm for a future two-arm study to have an 80% chance of detecting the specified effect under the planning assumptions, if that effect and assumptions are correct. The 90% power column gives the corresponding per-arm planning figure for a higher chance of detection. These are design illustrations, not findings about what happened in the completed study.

Rows planning for 75% or 50% of the observed effect ask what sample size would be needed to detect a smaller effect than the observed one. Smaller effects are harder to distinguish from random variation, so they generally require more participants. The displayed curve provides a visual account of how the planning estimate changes with the assumed effect size; it is another way to read the same planning relationship, not a separate trial result.

These calculations use observed effects as inputs, so they are sensitive to how large or small the observed estimates happen to be. A planning estimate based on an observed effect should not be interpreted as a guarantee that a future trial will achieve the stated power. These figures are not observed power.

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 = -5.300; pooled standard deviation σ = 29.209.
2. n = 2 × (1.96 + 0.842)² × 29.209² / -5.300² = 476.8, rounded up to 477 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 <- -5.3                      # observed difference in means
sigma <- 29.2085626252069                     # 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(300456)
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 = 477 (80% power), 639 (90% power)
 75% of observed effect: n per arm = 848 (80% power), 1,135 (90% power)
 50% of observed effect: n per arm = 1,908 (80% power), 2,554 (90% power)
power.t.test: 477.7 
Simulated power at n = 477 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.

14. Analyses Reported by the Sponsor

The registry record reports sponsor analyses using ANCOVA for two comparisons: ABT-335 plus 20 mg simvastatin versus 20 mg simvastatin, and ABT-335 plus 40 mg simvastatin versus 40 mg simvastatin. Each reported p-value is <0.001. The record identifies those analyses as having 95% confidence intervals, but does not give their effect estimates or interval limits.

The recalculated comparisons use posted arm means and standard errors and are unadjusted. They compare the combination arms with the ABT-335 plus 20 mg simvastatin reference group, rather than duplicating the sponsor's two matched-dose ANCOVA contrasts. For this record, a discrepancy is flagged. The sponsor's own analysis takes precedence for the comparisons it reports; the recalculations are supplementary descriptions of the posted summary statistics and should not be used to replace the sponsor's model-based results.

The reported p-values alone do not show the magnitude of the ANCOVA contrasts or their precision. The registry record does not report the covariates or full model details needed to independently reproduce those analyses. Accordingly, the sponsor findings can be described as statistically significant according to the reported ANCOVA p-values, while the actual adjusted differences and their uncertainty remain unavailable in the registry record.

15. Multiplicity, Missing Data and Analysis Populations

Several treatment groups and multiple outcomes create a multiplicity concern: the more comparisons examined, the greater the chance that some results appear notable by chance even when there is no underlying difference. This is especially relevant for the secondary outcomes and the recalculated comparisons, whose p-values are unadjusted. The registry record does not report a multiplicity adjustment, a testing hierarchy, or which comparisons were designated as confirmatory beyond identifying the primary outcome.

The primary analysis population required a baseline triglyceride value and at least 1 postbaseline triglyceride value. Last observation carried forward was used for missing follow-up measurements. This method carries an earlier observed value forward to fill a later missing value. It can preserve participants in an analysis, but depends on assumptions about the unobserved outcome after the last measurement. The registry record does not report the amount of missing data, the reasons for missingness, or sensitivity analyses using alternative approaches.

Outcome counts vary by arm and endpoint. These differences mean that the group summaries do not all represent precisely the same set of participants. The registry record does not provide enough detail to determine why each outcome count differs, how missing observations were distributed, or whether exclusions differed systematically between groups.

The available descriptions name the primary analysis population and the imputation approach, but do not report the full statistical analysis plan, detailed model specifications, or whether interim analyses were conducted. Those items are not reported in the registry record. Without them, the degree to which all analysis choices were specified before outcome data were examined cannot be assessed from the record alone.

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

The results describe average percentage changes in triglycerides and other lipid measures from baseline to the 12-week final visit among the participants included in each outcome analysis. They show that the posted primary endpoint means were negative in all six groups. The recalculated differences quantify how the posted group means compare under an unadjusted summary-statistic approach, while the registry also reports ANCOVA p-values for two specified comparisons.

A statistically significant result is not the same as a clinically important result. The record does not establish a threshold for a meaningful change in triglycerides, and the available information does not connect these short-term laboratory outcomes to longer-term health outcomes. Nor do the results alone establish that a treatment works or does not work. They describe the measurements and comparisons recorded for this trial.

Uncertainty matters. Some recalculated intervals include zero, while other unadjusted intervals exclude zero. The latter still do not account for multiplicity or substitute for the sponsor's adjusted analyses. The sponsor's reported p-values do not include effect estimates or confidence interval limits in the posted analysis details, so their magnitude and precision cannot be assessed from those p-values alone.

The primary population used last observation carried forward for missing follow-up values, and the registry record does not report the amount or pattern of missingness. Safety interpretation also has limits: the listed adverse-event counts do not include at-risk denominators, and deaths are not reported in the record's adverse-event details. The results therefore do not support calculation of event rates or a complete benefit-harm assessment.

These findings apply to the studied population, regimens, outcome definitions, and follow-up period. The registry record does not report enough detail to assess generalizability beyond those conditions or to draw conclusions about outcomes not measured in the trial.

17. Why This Trial Matters Statistically

This trial illustrates why the treatment contrast and outcome scale must be considered together. Because the endpoint is percent change, negative means represent reductions, and a positive mean difference can indicate a less negative average in the comparison arm when the reference arm's mean is subtracted. Reading signs without the endpoint definition could reverse the apparent direction of a comparison.

It also shows the distinction between descriptive summaries and model-based inference. Group means and standard errors support straightforward recalculations, but those calculations do not reproduce ANCOVA. The registry reports sponsor analyses for two specific comparisons, and a discrepancy is flagged; the sponsor's analyses take precedence for those comparisons. Effect estimates and interval limits for the ANCOVA results would be needed to understand their magnitude and precision fully.

The record further demonstrates that analysis populations can be outcome-specific. The primary endpoint required baseline and postbaseline data and used last observation carried forward, while counts differ across outcomes. Those details matter for interpreting both the size of the groups and the uncertainty of estimates.

Finally, multiple endpoints and comparisons complicate interpretation. Unadjusted secondary findings may help describe patterns, but they are not equivalent to a single prespecified primary test. Reporting design assumptions, missing-data patterns, adjustment procedures, and model details would make the evidence easier to evaluate. Those details are not reported 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.

The information available for interpretation has several trial-specific limits. The registry record does not report the original sample-size justification, detailed allocation procedure, full statistical analysis plan, or ANCOVA model covariates. It also does not provide the sponsor's adjusted effect estimates and confidence interval limits, despite reporting p-values for two analyses. The discrepancy flag further reinforces that recalculated unadjusted contrasts should not be treated as replacements for the sponsor's own analyses.

The primary outcome used last observation carried forward, but the record does not report the amount or pattern of missing follow-up data or sensitivity analyses. The outcome population was defined by availability of baseline and postbaseline triglyceride measurements, and participant counts vary across outcomes. Without further detail, the influence of missingness and differences in analysis populations cannot be evaluated fully.

Several secondary outcomes and treatment comparisons were assessed, but multiplicity handling is not reported. Unadjusted secondary comparisons therefore warrant particular caution. The registry record also does not report detailed eligibility criteria beyond the broad description of mixed dyslipidemia and multiple abnormal lipid levels, limiting assessment of how well the results apply to other populations.

Safety information is incomplete for rate comparisons. The record lists affected counts for serious and other adverse events, but at-risk denominators are not reported; deaths are also not reported in these details. The listed counts should not be converted into rates or interpreted as a complete safety profile. Follow-up for the primary endpoint is 12 Weeks (Final Visit), so these results do not address longer-term outcomes.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Evaluate Safety and Efficacy of ABT-335 in Combination With Simvastatin in Subjects With Multiple Abnormal Lipid Levels in the Blood — NCT00300456.
• Registry record last updated 2009-06-03; status last verified 2009-05.
• Results first posted 2009-03-25.
• 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

NCT00300456 is a completed phase 3, multicenter, randomized, double-blind, prospective, parallel-group study sponsored by Abbott. It enrolled 657 and compared ABT-335 plus simvastatin regimens with ABT-335 or simvastatin monotherapy in subjects with mixed dyslipidemia and multiple abnormal lipid levels. The primary endpoint was mean percent change in triglycerides from baseline to the 12-week final visit.

Primary endpoint means were negative in all six arms. The registry reports ANCOVA p-values of <0.001 for two combination-versus-simvastatin comparisons, but does not provide their adjusted effect estimates or confidence interval limits. Recalculated unadjusted comparisons are supplementary and do not replace the sponsor's reported analyses. Secondary outcomes describe additional lipid and hsCRP measures, with multiplicity and missing-data details not reported in the registry record.