Evaluate the Effect of Obicetrapib in Patients With HeFH on Top of Maximum Tolerated Lipid-Modifying Therapies.: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluate the Effect of Obicetrapib in Patients With HeFH on Top of Maximum Tolerated Lipid-Modifying Therapies. (NCT05425745), a randomized phase 3 study. The primary outcome is Percent Change in Low-Density Lipoprotein Cholesterol (LDL-C) From Baseline to Day 84 [PUC].

2. Clinical Question

3. Trial Design

NCT05425745 is a completed phase 3 randomized study sponsored by NewAmsterdam Pharma. The registry lists the start date as 2022-07-25 and primary completion date as 2024-05-28. Enrollment was 354. The study used a parallel-group design and compared obicetrapib with placebo. The official title describes a placebo-controlled, double-blind study of 10 mg obicetrapib in participants with a history of HeFH whose lipid-modifying therapies did not adequately control their condition. The registry lists quadruple masking as the masking design.

Participants in the active-treatment arm were assigned one 10 mg obicetrapib tablet once daily; participants in the comparator arm were assigned one placebo tablet once daily. The study summary describes efficacy, safety, and tolerability as its aims. The available record does not detail the sequence-generation method, allocation concealment, stratification factors, or how masking was maintained. Those design details are not reported in the registry record.

The primary outcome was percent change from baseline to Day 84 in LDL-C measured by PUC. The registry identifies the primary-outcome baseline population as all participants randomized, with baseline defined as the last measurement before the first dose of study drug. The outcome display lists 118 participants for placebo and 232 for obicetrapib. The registry also notes that two participants randomized to obicetrapib did not receive study drug. Safety group counts use 118 participants for placebo and 234 for obicetrapib. The record does not explain every difference between the outcome and safety counts.

There are 20 outcome measures and 14 analyses listed, with 19 secondary outcomes posted. The full protocol, trial-specific sample-size justification, prespecified statistical analysis plan, and details of interim analyses are not reported in the registry record. These omissions limit what can be established about the original design decisions and the complete planned analysis.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Baseline Population is defined as all participants who were randomized in the study. Baseline values were defined as last measurement prior to the first dose of study drug. 2 participants in the obi arm were randomized but did not receive study drug, therefore the "n" for the obi arm baseline values did not exceed n=234. In addition, participants needed available labs at both baseline and Day 84.

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: Baseline Population is defined as all randomized participants.

6. Primary Endpoint

The registry lists the primary outcome as Percent Change in Low-Density Lipoprotein Cholesterol (LDL-C) From Baseline to Day 84 [PUC], measured over 84 Days.

The primary endpoint measures the percent change in LDL-C from baseline to Day 84, with LDL-C measured by preparative ultracentrifugation (PUC). Baseline is defined in the registry as the last measurement before the first dose of study drug. The outcome is continuous: it represents change on a numerical scale, rather than a count of participants who did or did not meet a threshold. The registry reports least-squares means for the treatment groups and a between-group estimate from an analysis of covariance (ANCOVA).

LDL-C is the outcome selected for the main comparison in this trial of obicetrapib added to participants’ existing lipid-modifying therapies. The percent-change scale expresses change relative to each participant’s baseline value, while the between-group contrast describes the estimated difference in average change. A negative group estimate indicates a decrease from baseline on this scale; the between-group estimate compares that change with the placebo group’s change. These statistical descriptions do not establish the clinical importance of a particular estimate.

In general, selecting a primary endpoint sets out the central outcome the trial is intended to evaluate and helps distinguish that main question from the additional outcomes. The trial-specific rationale for selecting Day 84, PUC measurement, and this endpoint is not reported in the registry record. Nor does the record give a clinical threshold for interpreting the size of change. Thus the posted result addresses a specific laboratory measure and follow-up time, not every aspect of efficacy, safety, or longer-term outcomes.

7. Results Posted in the Registry

• Obicetrapib 10 mg: mean -36.05 versus 0.25 on control; difference -36.30 (95% CI -42.27 to -30.33), standardized effect d = -1.35; 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.

Percent Change in Low Density Lipoprotein-Cholesterol (LDL-C) From Baseline to Day 180 [Martin/Hopkins]

• 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:
  • Obicetrapib 10 mg: mean -31.80 versus 5.98 on control; difference -37.78 (95% CI -44.79 to -30.77), standardized effect d = -1.20; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Obicetrapib 10 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percent Change in Low Density Lipoprotein-Cholesterol (LDL-C) From Baseline to Day 365 [PUC]

• 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:
  • Obicetrapib 10 mg: mean -31.14 versus 10.30 on control; difference -41.44 (95% CI -51.10 to -31.78), standardized effect d = -1.00; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Obicetrapib 10 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percent Change in Apolipoprotein B (ApoB) From Baseline to Day 84

• 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:
  • Obicetrapib 10 mg: mean -21.45 versus 2.93 on control; difference -24.38 (95% CI -28.57 to -20.19), standardized effect d = -1.30; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Obicetrapib 10 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes extend the assessment beyond the primary Day 84 LDL-C measure. They include LDL-C at later time points and measures of apolipoprotein B and non-HDL-C. The posted secondary results with estimates show a broad pattern consistent in direction with the primary finding: the obicetrapib group’s estimated changes are more negative than the placebo group’s for the reported comparisons. This provides context across related lipid measures and follow-up times, rather than a separate substitute for the primary endpoint.

The secondary outcomes differ in measure and timing, so they do not all answer the same question. Later assessments describe outcomes at later follow-up, while apolipoprotein B and non-HDL-C are distinct measures. Their results can help describe whether the primary pattern appears alongside other registered outcomes, but they cannot by themselves establish what a particular change means clinically or how durable it is beyond the periods assessed.

There are 20 outcome measures, 14 analyses, and 19 secondary outcomes posted. When a trial examines multiple outcomes, the chance of obtaining at least one small p-value can increase if each result is interpreted as an independent confirmatory test. Statistical methods can address multiplicity, but the registry does not report whether or how the secondary analyses were adjusted for it. The trial’s prespecified hierarchy of secondary outcomes is also not reported in the registry record.

For that reason, unadjusted secondary p-values carry less weight as confirmatory evidence than a result supported by a prespecified analysis that accounts for the testing plan. They remain useful descriptive evidence, especially when estimates and intervals are considered alongside the primary result, but their interpretation should be cautious. The full outcome-level analysis plan and details about missing secondary measurements are not reported in the registry record.

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

• Percent Change in Low Density Lipoprotein-Cholesterol (LDL-C) From Baseline to Day 180 [Martin/Hopkins]
• Percent Change in Low Density Lipoprotein-Cholesterol (LDL-C) From Baseline to Day 365 [PUC]
• Percent Change in Apolipoprotein B (ApoB) From Baseline to Day 84
• Percent Change in Apolipoprotein B (ApoB) From Baseline to Day 180
• Percent Change in Apolipoprotein B (ApoB) From Baseline to Day 365
• Percent Change in Non-HDL-C From Baseline to Day 84
• Percent Change in Non-HDL-C From Baseline to Day 180
• Percent Change in Non-HDL-C From Baseline to Day 365

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous, and the registry reports least-squares means and an ANCOVA comparison. These methods serve related but distinct purposes. The group means describe estimated average percent changes, while the between-group estimate describes the contrast between the groups. The registry reports a 95% confidence interval for that contrast and a p-value. The unadjusted recalculation uses posted summary statistics and should be understood as a separate, simpler comparison rather than as a reproduction of every feature of the sponsor’s analysis.

What does ANCOVA contribute?

In general, analysis of covariance (ANCOVA) compares group outcomes while accounting for one or more covariates. In a trial with a baseline measurement, an analysis may use baseline outcome values as a covariate, but the precise covariates and model specification used for this trial are not reported in the registry record. The registry identifies the reported method as ANCOVA and describes its parameter as least-squares means. A least-squares mean is a model-based estimate of a group mean, calculated under the fitted model’s adjustment structure. It can therefore differ from a raw arithmetic average.

The reported estimate of -36.31 is the ANCOVA between-group result, with a 95% confidence interval from -42.22 to -30.39 and p <.0001. The record labels the analysis as a superiority analysis. The trial-specific hypothesis-testing details, including any model diagnostics and covariates beyond what is explicitly described, are not reported in the registry record. Statistical interpretation should not assume a particular model specification beyond the method and output that the registry names.

What does the unadjusted recalculation represent?

The recalculated comparison is a simple unadjusted calculation from the posted group summary statistics. It yields a mean difference of -36.3 with a 95% interval from -42.27 to -30.33 and p <0.001. It does not apply the ANCOVA adjustment used in the sponsor’s reported analysis. Its role is to provide a transparent check of the broad contrast using the posted summaries, not to replace the sponsor’s analysis or establish what the prespecified analysis was.

The recalculation uses an approximate pooled standard deviation, as indicated in the posted calculation details. This approximation is based on the available group summaries rather than participant-level data. A summary-statistic calculation cannot reproduce individual-level modeling, account for covariates that are not represented in those summaries, or resolve questions about missing observations. The fact that the recalculated and sponsor-reported estimates are close is useful context, but the methods remain distinct.

How should the p-value be read?

In general, a p-value describes how unusual results at least as discrepant from a specified null hypothesis would be under the assumptions of the statistical test, if that null hypothesis were true. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. The sponsor reports p <.0001 for the primary ANCOVA analysis; the simple unadjusted recalculation reports p <0.001. These are the p-values attached to different analyses. The p-value alone does not describe the range of plausible effect sizes, which is why the confidence interval also matters.

The reported p-value is a test of the between-group comparison under the analysis used. It does not establish that every participant’s outcome changed in the same way. Nor does it answer questions about adverse events, longer-term effects, or the clinical meaning of the endpoint. Those require other data and interpretation beyond the p-value.

Why can over-dispersion matter?

In general, over-dispersion occurs when observed variation is greater than a statistical model expects. If a model understates variability, its standard errors may be too small and its confidence intervals too narrow, making statistical evidence appear more precise than it is. The posted primary endpoint is continuous and reports standard errors, but the registry record does not report an over-dispersion assessment or a need for an over-dispersion correction. This is a general consideration, not a claim that over-dispersion occurred in this trial.

For continuous outcomes, distributional shape, outliers, unequal variability, and model fit can also affect how well a model represents the data. The participant-level distributions, diagnostics, and sensitivity analyses are not reported in the registry record. Consequently, the registry output permits interpretation of the reported estimates and uncertainty, but not a full independent assessment of modeling assumptions.

11. Confidence Intervals and Precision

The sponsor’s primary ANCOVA estimate is -36.31, with a 95% confidence interval from -42.22 to -30.39. The interval describes a range of values compatible with the data and the analysis under the method’s assumptions. It conveys uncertainty around the estimated group contrast; it is not a range containing a stated proportion of individual participants’ responses. Because the interval lies below zero, the reported result indicates a negative between-group contrast on the percent-change scale.

The interval also helps assess precision. A confidence interval that spans a broad range leaves more uncertainty about the magnitude than a narrower interval, even when both exclude zero. Here, the endpoints represent different plausible sizes of the estimated contrast. The registry’s result therefore supports a direction for the average contrast under the reported analysis, while the precise magnitude remains subject to sampling uncertainty and the assumptions of the model.

The unadjusted recalculation gives -36.3 with an interval from -42.27 to -30.33. This is similar to, but not identical to, the sponsor’s ANCOVA interval of -42.22 to -30.39. The difference is expected to be possible because the methods are not the same: one is a model-based sponsor analysis, and the other is a simple unadjusted recalculation from summary statistics. The registry does not report a discrepancy between them.

In general, a confidence interval reflects statistical uncertainty, not all sources of uncertainty. It does not account for questions about endpoint selection, missing-data handling, multiplicity, or unreported analytic choices. The confidence interval also does not establish clinical importance. The registry does not state a threshold for a clinically meaningful difference, so the interval’s statistical interpretation should remain separate from judgments about the practical meaning of the estimate.

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 figures are planning illustrations based on the observed effect, not the original trial’s design assumptions. For these continuous-outcome comparisons, the figures are participants per arm, not total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The original trial’s sample-size justification is not reported in the registry record.

The 80% power column gives the illustrated number of participants per arm for a design with an 80% chance of detecting the assumed effect under those planning assumptions, if that effect and the assumptions were correct. The 90% power column gives the corresponding per-arm planning figure for a design with a 90% chance. These are prospective design concepts, not measures of how likely the observed result was to be true. The figures are not observed power.

Rows that use 100% of the observed effect plan around the full observed estimate; rows using 75% or 50% plan around smaller effects. Smaller effects need more participants to detect with the same planned power and significance level. That relationship explains why the per-arm planning figures rise as the assumed fraction of the observed effect becomes smaller. The illustrations are not a reconstruction of the trial’s enrollment target: they use the observed effect and stated simplifying assumptions, while the trial’s original design rationale and assumptions are not reported in the registry record.

These planning values should be read as conditional illustrations. They do not account for details that may have been used in the trial’s actual design, such as the full analysis model or any other planning considerations, because those details are not reported. They also do not imply that the trial was designed around the effect ultimately observed.

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 = -36.300; pooled standard deviation σ = 26.943.
2. n = 2 × (1.96 + 0.842)² × 26.943² / -36.300² = 8.6, rounded up to 9 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 <- -36.3                      # observed difference in means
sigma <- 26.9429546967868                     # 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(5425745)
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 = 9 (80% power), 12 (90% power)
 75% of observed effect: n per arm = 16 (80% power), 21 (90% power)
 50% of observed effect: n per arm = 35 (80% power), 47 (90% power)
power.t.test: 9.7 
Simulated power at n = 9 per arm: 0.764 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry’s sponsor-reported primary result is an ANCOVA estimate of -36.31, with a 95% confidence interval from -42.22 to -30.39 and p <.0001. The simple unadjusted recalculation from the posted summaries gives -36.3, a 95% interval from -42.27 to -30.33, and p <0.001. The estimates and intervals are close, but the values are not identical because the recalculation and ANCOVA are different analyses.

The recalculation uses group-level summary statistics and an approximate pooled standard deviation. It does not reproduce the covariate adjustment or other features of the sponsor’s model. It is therefore best read as a secondary statistical check of the broad contrast, not as a replacement for the analysis reported by the trial sponsor. The registry does not flag a discrepancy between the analyses.

The sponsor’s analysis is the trial’s reported analysis for the primary endpoint. The registry does not provide the full statistical analysis plan, the detailed ANCOVA specification, or participant-level data with which to reproduce that model. As a result, the posted outputs support a comparison of the headline estimates and their uncertainty, but not a complete independent replication of the sponsor’s analysis.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several hypotheses are tested. If each test is considered on its own, making many comparisons can increase the chance that at least one result appears statistically compelling by chance. The registry lists 20 outcome measures and 14 analyses, with 19 secondary outcomes posted. This makes the analysis context important: a primary endpoint can be distinguished from additional outcomes only when the planned outcome hierarchy and any multiplicity procedures are clear.

Whether the trial controlled the overall error rate across secondary analyses, used a prespecified testing sequence, or treated secondary results as exploratory is not reported in the registry record. The statistical analysis plan and the protocol’s full outcome hierarchy are also not reported. Consequently, the posted secondary p-values should not be assumed to have the same confirmatory status as the designated primary analysis.

Missing-data methods are another important part of interpreting an outcome analysis. The registry record does not report how missing Day 84 measurements or missing secondary measurements were handled, whether values were imputed, or what sensitivity analyses were conducted. The outcome counts therefore describe the analysis displays but do not fully explain why participants may be absent from a particular analysis. Missing-data handling can affect both estimates and their uncertainty, depending on the amount and pattern of missingness and the assumptions used.

The registry defines the primary baseline population as all randomized participants and baseline as the last measurement before the first dose. It notes that two participants randomized to obicetrapib did not receive study drug. The primary outcome lists 232 participants in that arm, while the safety group lists 234. The record does not provide enough detail to reconcile every count or establish the exact population used for every analysis. A complete interpretation would require the analysis populations, participant flow, missing-data procedures, and prespecified plan; these details are not reported in the registry record.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 2% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: angina pectoris (1.7%), angina unstable (0.9%), chronic obstructive pulmonary disease (0.9%), death (0.8%), enteritis (0.8%).

The safety record lists serious adverse events among 8 of 118 participants in the placebo group and 13 of 234 participants in the obicetrapib 10 mg group. The safety group counts also list other adverse events for 52 of 118 placebo participants and 95 of 234 obicetrapib participants. Deaths are listed for 2 participants in the placebo group and 3 in the obicetrapib group. These are counts within the reported safety groups and should be read with their group denominators; they are not, by themselves, an adjusted comparison or an explanation of event causality.

The registry lists serious-event terms including angina pectoris at 1.7%, angina unstable at 0.9%, chronic obstructive pulmonary disease at 0.9%, death at 0.8%, enteritis at 0.8%, and gastrointestinal fistula at 0.8%. The record does not establish from these entries alone how the listed terms relate to treatment assignment or provide enough detail to assess each event’s timing, severity, or attribution.

Safety counts are descriptive. Differences in counts should not be interpreted as evidence of causation or as a definitive comparison of risk without the trial’s full safety definitions, exposure information, and analysis methods. Those details are not reported in the registry record. The listed results also do not capture the full clinical context needed to interpret an individual event.

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

The posted primary result describes a difference between the obicetrapib and placebo groups in average percent change in LDL-C from baseline to Day 84, measured by PUC. The sponsor’s ANCOVA estimate is -36.31, with a 95% confidence interval from -42.22 to -30.39. The estimate is below zero, and the interval excludes zero. The result therefore indicates a statistically distinguishable group contrast under the reported analysis and its assumptions.

That conclusion is specific to the measure, timing, population, and analysis described in the registry. It does not mean that every participant had the same outcome, and the group-level estimate does not reveal the distribution of individual responses. It also does not establish the clinical importance of the estimated difference: the registry does not report a threshold for clinical importance. Nor does a laboratory outcome alone address every outcome relevant to participants.

The result does not, by itself, resolve questions about longer-term effects, outcomes beyond those posted, or the balance of benefits and harms. Secondary outcomes provide additional measures and time points, while the safety record lists adverse-event counts and deaths. These different kinds of data need to be interpreted on their own terms. The registry output does not provide all the information needed to assess event causality or to make a full benefit-risk judgment.

Statistical uncertainty is also only one part of uncertainty. The confidence interval describes sampling uncertainty under the reported analysis, but the registry does not report the full statistical analysis plan, detailed missing-data methods, or whether multiplicity was addressed for secondary analyses. The primary estimate can be described accurately without filling in those gaps. Its meaning should remain bounded by the posted Day 84 endpoint and the analyses documented in the registry record.

18. Why This Trial Matters Statistically

This trial is statistically informative because it reports a prespecified primary comparison of a continuous LDL-C outcome in a randomized, placebo-controlled phase 3 design. The primary estimate, interval, and p-value allow readers to assess both the direction of the group contrast and its statistical uncertainty. The ANCOVA result gives a model-based comparison, while the simple unadjusted recalculation offers a separate check using the posted summaries. Keeping those analyses distinct helps avoid treating a recalculation as if it were the sponsor’s model.

The record also illustrates why estimates should be read alongside study design and analysis details. The primary outcome has a clearly stated measure and time point, but the full model specification, missing-data procedures, multiplicity plan, and original sample-size justification are not reported. These details matter because they clarify what population was analyzed, how uncertainty was estimated, and how much evidential weight to give additional outcomes.

Secondary measures add breadth by reporting related outcomes over different time points and across different lipid measures. At the same time, many outcomes and analyses create a multiplicity issue if all are interpreted as confirmatory tests. The distinction between the primary result and secondary findings is therefore important, especially where the prespecified hierarchy and adjustment methods are unavailable.

Finally, the safety counts and outcome counts should not be collapsed into one denominator or treated as interchangeable. The registry reports different counts across outcome displays and notes that two randomized participants in the obicetrapib group did not receive study drug. Recognizing such distinctions is a basic part of statistical reading: a result applies to the analysis and population that produced it. The record supports a focused interpretation of the posted primary contrast, while leaving several design and analysis questions unresolved.

19. Limitations

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

Several trial-specific limitations follow from details not reported in the registry record. The complete protocol and statistical analysis plan are unavailable in the record, so the prespecified model specification, covariates, testing hierarchy, and handling of secondary analyses cannot be confirmed. The record also does not report how missing outcome data were handled or whether sensitivity analyses were performed. These omissions limit independent assessment of robustness.

The outcome displays use different counts from the overall enrollment and safety entries. The primary outcome lists 118 participants for placebo and 232 for obicetrapib; safety groups list 118 and 234, respectively. The registry notes that two participants randomized to obicetrapib did not receive study drug, but the available description does not fully reconcile counts across analyses. The number and reasons for missing endpoint measurements are not reported in the registry record.

The reported primary result is a model-based ANCOVA estimate, but detailed model assumptions and diagnostics are not reported. The unadjusted recalculation is based on summary statistics and an approximate pooled standard deviation, so it cannot reproduce participant-level modeling or evaluate the underlying distributions. Its closeness to the sponsor result is reassuring as a numerical check but does not substitute for access to participant-level data or the analysis plan.

The record reports a primary endpoint at Day 84 and several secondary outcomes, but it does not state a clinical-importance threshold for interpreting the magnitude. Multiplicity handling for the secondary outcomes is not reported. Safety entries are counts and listed terms; fuller information about event timing, exposure, attribution, and definitions is not reported. These limitations do not negate the posted results, but they constrain the scope and certainty of conclusions that can be drawn from the registry record alone.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Evaluate the Effect of Obicetrapib in Patients With HeFH on Top of Maximum Tolerated Lipid-Modifying Therapies. — NCT05425745.
• Registry record last updated 2025-06-11; status last verified 2025-06.
• Results first posted 2025-06-11.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT05425745 is a completed randomized, parallel-group phase 3 study of obicetrapib 10 mg once daily versus placebo in participants with a history of HeFH whose lipid-modifying therapies did not adequately control their condition. Enrollment was 354. The primary outcome was percent change in LDL-C from baseline to Day 84 measured by PUC.

The sponsor-reported ANCOVA estimate was -36.31, with a 95% confidence interval from -42.22 to -30.39 and p <.0001. The simple unadjusted recalculation was similar but used a different method. Secondary LDL-C, apolipoprotein B, and non-HDL-C outcomes provide additional context; multiplicity procedures are not reported in the registry record. Safety entries include serious adverse events, other adverse events, and deaths in both groups. The full statistical plan, missing-data methods, and original sample-size justification are not reported in the registry record.