Study in Participants With Homozygous Familial Hypercholesterolemia (HoFH): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study in Participants With Homozygous Familial Hypercholesterolemia (HoFH) (NCT03156621), a randomized phase 3 study. The primary outcome is Percent Change in Low-density Lipoprotein Cholesterol (LDL-C) From Baseline to Week 12 (Intent-to-Treat [ITT] Estimand).

2. Clinical Question

3. Trial Design

This was a phase 3, randomized, double-blind, placebo-controlled, parallel-group study of alirocumab in participants with HoFH. The registry records triple masking. Which specific roles were masked is not reported in the registry record. The study is marked completed, with enrollment of 69 participants.

The double-blind treatment period compared alirocumab 150 mg subcutaneously every 2 weeks with matching placebo. The assigned double-blind treatment began at baseline and continued through week 10. At week 12, both groups were scheduled to begin open-label alirocumab every 2 weeks, continuing through week 22. The primary endpoint was assessed from baseline to week 12, so it addresses the comparison before the open-label period began.

The endpoint summaries include 24 participants in the placebo group and 45 in the alirocumab group. These are the group counts recorded for the primary endpoint. The registry’s exact original randomization procedure, allocation ratio rationale, and reasons for the observed group sizes are not reported in the registry record. The protocol’s original sample-size justification and planned analysis details beyond the information recorded for the endpoint are also not reported in the registry record.

The registry describes secondary objectives involving other lipid measures, safety and tolerability, pharmacokinetics, and potential anti-drug antibodies. The posted results include primary and secondary lipid analyses and adverse-event counts. Pharmacokinetic and anti-drug antibody results are not detailed in the record summarized by these results.

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: Sixty-nine of the 85 participants were eligible and randomized in a 2:1 ratio to receive either alirocumab 150 mg SC Q2W or matching placebo. Randomization was stratified by LDL apheresis treatment status (on vs off treatment).

Double-Blind Treatment Period (DBTP)

Open-Label Treatment Period (OLTP)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: ITT estimand (All randomized participants who had at least 1 measurement value for LDL-C before the first dose of double blind investigational study drug)

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Percent Change in Low-density Lipoprotein Cholesterol (LDL-C) From Baseline to Week 12 (Intent-to-Treat [ITT] Estimand), measured over Baseline to Week 12.

The primary endpoint is percent change in LDL-C from baseline to week 12. It is defined as 100 times the week 12 LDL-C value minus the baseline LDL-C value, divided by the baseline value. A negative percent change therefore represents a lower LDL-C value at week 12 than at baseline; a positive value represents a higher value.

The registry reports least-squares means for each group and a least-squares mean difference between alirocumab and placebo. This is a continuous endpoint: it describes the magnitude and direction of change rather than classifying participants only as having met or not met a threshold. As a general statistical point, retaining the measured change can preserve information about how large changes are across participants. The clinical rationale for choosing this endpoint and the full endpoint specification beyond the registry description are not reported in the registry record.

The primary analysis population is described as the ITT estimand: all randomized participants who had at least one LDL-C measurement before the first dose of double-blind investigational study drug. This wording defines the population for the reported endpoint; it does not establish how participants without later measurements were handled. That missing-data approach is not reported in the registry record.

7. Results Posted in the Registry

• Alirocumab 150 mg SC Q2W: mean -26.90 versus 8.60 on control; difference -35.50 (95% CI -50.79 to -20.21), standardized effect d = -1.15; 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 Apolipoprotein (Apo) B From Baseline to Week 12 (ITT Estimand)

• 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:
  • Alirocumab 150 mg SC Q2W: mean -22.50 versus 7.20 on control; difference -29.70 (95% CI -41.89 to -17.51), 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 Alirocumab 150 mg SC Q2W than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percent Change in Non-high-density Lipoprotein Cholesterol (Non-HDL-C) From Baseline to Week 12

• 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:
  • Alirocumab 150 mg SC Q2W: mean -24.80 versus 8.00 on control; difference -32.80 (95% CI -47.11 to -18.49), standardized effect d = -1.14; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alirocumab 150 mg SC Q2W than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percent Change in Total Cholesterol (TC) From Baseline to Week 12

• 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:
  • Alirocumab 150 mg SC Q2W: mean -19.80 versus 6.60 on control; difference -26.40 (95% CI -38.59 to -14.21), standardized effect d = -1.07; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alirocumab 150 mg SC Q2W than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes extend the assessment beyond LDL-C to other lipid measures, including ApoB, non-HDL-C, total cholesterol, lipoprotein(a), HDL-C, and proportions meeting specified LDL-C reduction thresholds. The registry also describes safety, pharmacokinetic, and anti-drug antibody objectives. These outcomes address related but distinct questions and do not replace the primary endpoint.

For the posted continuous comparisons of ApoB, non-HDL-C, and total cholesterol, the sponsor-reported MMRM estimates are lower in the alirocumab group than in the placebo group, and each reported comparison has p < 0.001. This direction is consistent with the primary LDL-C contrast. The results support a coherent pattern across these reported lipid measures, while remaining estimates of separate endpoints rather than independent confirmation of a clinical outcome.

The registry lists 23 outcome measures and records 22 secondary results as posted. A complete assessment of all secondary results requires attention to their estimates, uncertainty, analysis populations, and definitions. The registry record does not report a multiplicity adjustment or a hierarchy governing interpretation of the secondary endpoints. Without such a procedure, unadjusted secondary p-values carry less weight: testing many outcomes increases the chance that some results appear statistically notable by chance, even if each test is considered separately.

Secondary findings are best treated as supportive and exploratory unless a prespecified testing strategy establishes otherwise. The registry record does not report whether the secondary tests were adjusted, ordered in a formal sequence, or intended to support confirmatory claims. Their consistency with the primary direction is informative, but it does not remove uncertainty from multiple testing or establish effects on outcomes that were not measured.

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

• Percent Change in Apolipoprotein (Apo) B From Baseline to Week 12 (ITT Estimand)
• Percent Change in Non-high-density Lipoprotein Cholesterol (Non-HDL-C) From Baseline to Week 12
• Percent Change in Total Cholesterol (TC) From Baseline to Week 12
• Percentage of Participants With ≥15% Reduction in LDL-C at Week 12
• Percentage of Participants With ≥30% Reduction in LDL-C at Week 12
• Percent Change in Lipoprotein(a) [Lp(a)] From Baseline to Week 12
• Percentage of Participants With ≥50% Reduction in LDL-C at Week 12
• Percent Change in HDL-C From Baseline to Week 12 - ITT Analysis

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous, expressed as percent change in LDL-C from baseline to week 12. The registry reports group least-squares means and their standard errors, followed by a between-group least-squares mean difference from an MMRM analysis. This distinction matters: the descriptive group summaries and the model-based comparison are related, but they are not identical summaries.

What does a least-squares mean represent?

In general, a least-squares mean is a model-based estimate of a group mean. It is often used when an analysis accounts for repeated observations or other terms in a statistical model. The registry reports least-squares means for the endpoint and identifies MMRM as the sponsor’s method. The model’s full specification, including any covariates, covariance structure, and estimation details, is not reported in the registry record.

The reported primary group estimates are -26.9% for alirocumab and 8.6% for placebo. Their sponsor-reported least-squares mean difference is -35.6 percentage points. The comparison is expressed in the same units as the percent-change outcome: it is a difference between group percent changes, not a percent reduction in the difference itself.

Why use a repeated-measures model?

In general, a mixed model for repeated measures can use measurements collected at multiple visits and account for the fact that observations from the same participant are related. It can estimate group differences while using the repeated outcome information specified in the model. The registry names MMRM for the reported analysis, but the visit-level data, model terms, and handling of incomplete follow-up are not reported in the registry record. Those details are needed to assess the exact model assumptions and how they were implemented.

The primary endpoint timeframe is baseline to week 12. The blinded comparison treatment is described as continuing through week 10, with open-label alirocumab beginning at week 12 for both groups. This makes the primary assessment a comparison tied to the double-blind period. No claim about a blinded placebo comparison after that point follows from the primary analysis.

How should the p-value be understood?

In general, a p-value measures how incompatible the observed data are with a specified null hypothesis under the analysis assumptions. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. The sponsor reports p < 0.001 for the primary contrast. This is evidence against a zero-difference null within the reported model; it should be interpreted together with the estimated difference and confidence interval.

The recalculation uses the posted group means and standard errors to make a simple, unadjusted comparison. Its estimated mean difference is -35.5, with an interval from -50.79 to -20.21 and p < 0.001. The calculation uses an approximate pooled standard deviation derived from the group standard errors and sample sizes. It does not reproduce the sponsor’s MMRM, its repeated-measures structure, or any model adjustment. The estimate and interval are therefore a check based on summary statistics, not a replacement for the reported analysis.

Why can estimates from different methods differ?

General statistical methods can differ because they use different assumptions and different information. A simple calculation from group summaries treats the comparison differently from an MMRM that models repeated measurements. Standard errors and intervals can also differ because of those methods. Here, the recalculated and sponsor estimates are close, but the registry identifies MMRM as the reported analysis. The record does not provide enough modeling detail to reproduce that analysis independently.

The reported analysis is marked as a superiority analysis. That label describes the statistical comparison being tested; it does not by itself establish clinical importance or imply an effect on outcomes that were not measured. The interpretation remains tied to the week-12 LDL-C percent-change endpoint and the population described in the registry.

11. Confidence Intervals and Precision

The sponsor reports a 95% confidence interval from -51.2 to -19.9 percentage points for the primary least-squares mean difference of -35.6. A confidence interval gives a range of estimates compatible with the data and the model under its assumptions. It communicates uncertainty about the estimated difference; it is not a range containing 95% of individual participants’ outcomes.

Both limits are below zero, so the interval supports a negative group contrast under the reported analysis. The interval also spans a substantial range of possible magnitudes. The estimate should not be read as if the true difference were known to be exactly -35.6. The interval’s width reflects the precision available in this trial and the sponsor’s model, but the registry record does not provide enough details to attribute that width to particular sources.

The unadjusted recalculation has a 95% interval from -50.79 to -20.21. It is based on posted summary statistics and an approximate standard deviation, rather than the sponsor’s MMRM. Its limits are therefore not interchangeable with the sponsor’s interval. For the trial’s reported inference, the sponsor’s model-based interval is the relevant one to cite.

In general, greater precision is indicated by a narrower confidence interval, while a wider interval leaves more uncertainty about the size of the effect. Neither interval answers whether the measured difference is clinically important. The registry does not report a threshold for clinical importance, a minimally important difference, or a decision rule based on the confidence interval.

12. Planning a Similar Trial: Sample Size

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

The planning values are participants per arm, not total participants or total events. This is a two-group continuous-outcome comparison, and the planning assumptions specify equal allocation. The illustrations use a two-sided significance level of 0.05 and a normal approximation. Each scenario sets the effect to detect at the stated fraction of the observed effect. The trial’s original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the number of participants per arm that a planning calculation estimates would give an 80% chance of detecting the specified effect under those assumptions, if that effect and the assumptions were correct. The 90% column makes the same kind of projection for a 90% chance. These are design-planning quantities, not probabilities that the observed result is correct and not measurements of the trial’s achieved power.

The rows based on a smaller fraction of the observed effect require more participants per arm. In general, smaller effects are harder to distinguish from random variation, so a study needs more information to detect them at a given power and significance level. The illustrations use the observed effect as a reference, but future studies may have different effects, variability, or analysis plans.

These figures are planning illustrations, not observed power. They should not be treated as the enrollment target used for this completed trial. The curve represents the relationship between the assumed effect and planning requirements; its values depend on the same stated assumptions. The registry record does not report whether the original design used these assumptions or a different calculation.

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 = -35.500; pooled standard deviation σ = 30.860.
2. n = 2 × (1.96 + 0.842)² × 30.860² / -35.500² = 11.9, rounded up to 12 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 <- -35.5                      # observed difference in means
sigma <- 30.859740473464                     # 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(3156621)
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 = 12 (80% power), 16 (90% power)
 75% of observed effect: n per arm = 22 (80% power), 29 (90% power)
 50% of observed effect: n per arm = 48 (80% power), 64 (90% power)
power.t.test: 12.9 
Simulated power at n = 12 per arm: 0.773 (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 sponsor’s primary analysis is an MMRM comparison of least-squares means. It reports a difference of -35.6, a 95% confidence interval from -51.2 to -19.9, and p < 0.001. This is the appropriate result to cite as the trial’s reported inferential analysis.

The unadjusted recalculation from group summaries estimates a difference of -35.5, a 95% interval from -50.79 to -20.21, and p < 0.001. It is a simple comparison derived from the posted means, standard errors, and group sizes. It does not reproduce the MMRM or its assumptions. The closeness of the point estimates is reassuring as a basic numerical check, but the recalculated interval and p-value should not be substituted for the sponsor’s reported analysis.

The registry’s discrepancy flag is false. The sponsor’s model-based analysis and the recalculation are not identical procedures, so small differences in estimates and uncertainty are expected. The available record does not include enough model detail or participant-level data to reproduce the sponsor’s result independently.

15. Multiplicity, Missing Data and Analysis Populations

The registry reports one primary LDL-C endpoint and numerous secondary outcomes. It does not report a multiplicity-control procedure, a testing hierarchy, or whether the secondary tests were intended to be confirmatory. When many hypotheses are tested, the chance of at least one apparently significant result can increase. As a general statistical principle, adjustment or a prespecified testing sequence can help control that issue. Without a reported procedure, secondary p-values should be interpreted more cautiously than the primary result.

The primary population is described as all randomized participants who had at least one LDL-C measurement before the first dose of double-blind study drug. This is the registry’s definition of the ITT estimand population for the endpoint. The registry does not report the number of randomized participants excluded from this population, if any, or a detailed accounting of participants with missing endpoint measurements.

The missing-data method is not reported in the registry record. In general, handling missing repeated measurements can affect estimates when the probability of a missing observation is related to observed or unobserved outcomes. MMRM is identified as the sponsor’s method, but the assumptions about missingness and any sensitivity analyses are not reported. The record also does not report whether imputation or another missing-data procedure was used.

Details of interim analyses, stopping rules, and the complete statistical analysis plan are not reported in the registry record. These absences limit assessment of the analysis decisions beyond the endpoint methods and results described. They do not change the numerical result reported by the sponsor, but they constrain how fully readers can evaluate prespecification, multiplicity, and robustness.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: arthralgia (2.2%).

For serious adverse events during the double-blind treatment period, the registry records 0 affected participants among 24 in the placebo group and 0 among 45 in the alirocumab group. During the open-label treatment period, the group labelled DB Placebo has 0 among 24, while the group labelled DB Alirocumab has 1 among 45. The top serious-event term listed is arthralgia at 2.2%.

These are registry counts for the recorded groups and periods. The double-blind and open-label entries should be read separately; they do not represent a single uninterrupted placebo-controlled comparison, because both groups were scheduled to receive open-label alirocumab beginning at week 12. The record reports 0 deaths in each listed group.

Event counts alone do not establish that a treatment caused an event or that two groups have equivalent safety. The groups are small, and the registry record does not provide event narratives or enough information to assess timing, duration, severity beyond the serious classification, or individual attribution. These figures describe reported serious adverse events, not the full safety profile or a clinical recommendation.

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

The primary result describes a difference between treatment groups in percent change in LDL-C from baseline to week 12. The sponsor’s model-based estimate is -35.6 percentage points, with a 95% confidence interval from -51.2 to -19.9 and p < 0.001. The negative estimate means that the estimated percent change was lower in the alirocumab group than in the placebo group over the primary assessment period.

This is a result for a laboratory measure in participants with HoFH, under the trial’s recorded treatment schedule and analysis population. It does not establish what happened to clinical events, longer-term health outcomes, or outcomes beyond the period assessed by the primary endpoint. Those outcomes are not reported in the registry record.

A statistically significant result is not itself a measure of clinical importance. The registry does not report a threshold for a clinically meaningful LDL-C difference, nor does it provide evidence that links this endpoint estimate to a particular patient-level benefit. The confidence interval gives information about uncertainty in the estimated group contrast, but it does not resolve those broader questions.

The comparison also has a defined time boundary. Placebo was used during the double-blind period through week 10, and the primary assessment was at week 12; both groups were scheduled to receive open-label alirocumab from week 12 through week 22. The primary result should not be interpreted as a placebo-controlled comparison after the open-label treatment began.

Accordingly, the registry result supports a description of the measured LDL-C contrast at week 12. It does not establish that the same result would occur in other populations, with different treatment schedules, or over other timeframes. It also does not answer questions about comparative long-term safety, since the posted counts alone do not provide a complete or causal assessment.

18. Why This Trial Matters Statistically

This trial offers a clear example of how to distinguish a measured endpoint from its statistical interpretation. The outcome is percent change in LDL-C, while the primary inferential result is a model-based difference between groups. Keeping those quantities separate helps avoid confusing an individual group’s change with the contrast that answers the randomized comparison.

The trial also illustrates why the analysis method matters. The sponsor reports an MMRM estimate, whereas a simple recalculation from group summaries yields a related but not identical estimate and interval. The recalculation is useful as a check on the direction and approximate size of the contrast, but it cannot reconstruct the sponsor’s repeated-measures analysis. Readers need to identify which result is model-based and which is a summary-statistic calculation.

Precision is another central part of interpretation. The confidence interval gives a range of plausible values under the reported analysis, rather than a guarantee that the point estimate is exact. The p-value addresses compatibility with a null hypothesis, not clinical importance. Reading the estimate, interval, and analysis method together gives a more complete account than relying on a significance label alone.

Finally, multiple secondary outcomes and a later open-label period place boundaries around what can be inferred. Secondary findings can provide context for the primary lipid result, but their evidential weight depends on multiplicity handling and prespecification. The registry record does not report those details. Clear reporting of both available results and absent methods is therefore part of responsible statistical interpretation.

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.

The primary analysis population is described in terms of randomization and a baseline LDL-C measurement, but the record does not report a participant flow accounting or the number of randomized participants with missing week-12 measurements. Missing-data handling and sensitivity analyses are not reported. These details matter when judging how incomplete follow-up could affect a continuous endpoint.

The registry identifies MMRM but does not report its full specification, including model terms, covariance structure, or assumptions. The sponsor’s analysis cannot therefore be independently reconstructed from this record. The unadjusted recalculation is based on summary statistics and is not an alternative adjusted analysis.

The trial enrolled 69 participants, with primary endpoint group counts of 24 and 45. The record does not report the original sample-size justification, the assumptions used to plan enrollment, or whether any interim analyses were performed. The planning illustrations based on the observed effect are not evidence of the trial’s original design process.

The record does not report a multiplicity strategy for the secondary endpoints. Nor does it provide a stated threshold for clinical importance of the primary endpoint. These omissions limit confirmatory interpretation of secondary findings and the ability to translate a statistically precise laboratory contrast into claims about clinical importance.

The blinded comparison was followed by open-label alirocumab in both groups from week 12 through week 22. The primary endpoint is therefore tied to the baseline-to-week-12 comparison, and the record does not provide a later placebo-controlled comparison. The posted serious-event counts are descriptive and do not by themselves establish causation or comparative safety. The registry also does not report enough information to evaluate generalizability beyond the studied population.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study in Participants With Homozygous Familial Hypercholesterolemia (HoFH) — NCT03156621.
• Registry record last updated 2021-06-29; status last verified 2021-06.
• Results first posted 2021-06-29.
• 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

The registry describes a completed randomized, double-blind, placebo-controlled, parallel-group phase 3 study of alirocumab in participants with HoFH. The primary endpoint was percent change in LDL-C from baseline to week 12, during the blinded comparison period.

The sponsor reports an MMRM least-squares mean difference of -35.6 percentage points for alirocumab versus placebo, with a 95% confidence interval from -51.2 to -19.9 and p < 0.001. Related reported secondary lipid comparisons show a similar direction, while multiplicity handling is not reported in the registry record.

Serious adverse-event counts are reported by double-blind and open-label groups. Missing-data methods, the original sample-size justification, and further details needed to reproduce the model are not reported in the registry record.