Study of Alirocumab (REGN727/SAR236553) in Patients With heFH (Heterozygous Familial Hypercholesterolemia) Who Are Not Adequately Controlled With Their LMT (Lipid-Modifying Therapy): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of Alirocumab (REGN727/SAR236553) in Patients With heFH (Heterozygous Familial Hypercholesterolemia) Who Are Not Adequately Controlled With Their LMT (Lipid-Modifying Therapy) (NCT01709500), a randomized phase 3 study. The primary outcome is Percent Change From Baseline in Calculated LDL-C at Week 24 - Intent--to--Treat (ITT) Analysis.

2. Clinical Question

3. Trial Design

This was a randomized, double-blind, placebo-controlled, parallel-group Phase 3 study, with quadruple masking recorded in the registry. The study was completed and enrolled 249 participants. It evaluated alirocumab in people with heterozygous familial hypercholesterolemia whose lipid-modifying therapy was not adequately controlling their condition. The study was multinational.

Participants assigned to alirocumab received 75 mg every two weeks, added to a stable dose of statin, with or without other lipid-modifying therapy. The protocol description allowed the alirocumab dose to be increased to 150 mg every two weeks from Week 12 when LDL-C was at least 70 mg/dL at Week 8. The comparator group received placebo injections matched to alirocumab for the 78-week treatment duration. The registry lists atorvastatin, simvastatin, and rosuvastatin among the lipid-modifying therapies.

The posted primary analysis includes 166 participants in the alirocumab group and 81 in the placebo group. The analysis population was not simply everyone randomized: the registry defines it as randomized participants with a baseline and at least one post-baseline calculated LDL-C result, on or off treatment. The registry does not report the original sample-size justification or the specific assumptions used to plan enrollment. Its separate planning illustration is based on the observed result and should not be read as the trial’s original design calculation.

The primary endpoint is labeled as the Week 24 percent change in calculated LDL-C, while its timeframe field says from baseline to Week 52. The endpoint description says the model used available post-baseline data from Week 4 to Week 52 and estimated adjusted means at Week 24. This distinction matters: the Week 24 result is a modeled estimate informed by repeated measurements over the stated follow-up period, rather than a simple comparison of only Week 24 observations.

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: Randomization was stratified according to prior history of myocardial infarction or ischemic stroke, and intensity of statin treatment. Assignment to treatment arms was done centrally using an Interactive Voice/Web Response System in a 2:1 (alirocumab: placebo) ratio after confirmation of selection criteria.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: ITT population: all randomized participants with one baseline and at least one post-baseline calculated LDL-C value on- or off-treatment.

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 From Baseline in Calculated LDL-C at Week 24 - Intent--to--Treat (ITT) Analysis, measured over From Baseline to Week 52.

The primary endpoint measures how calculated LDL-C changed from baseline, expressed as a percentage, with a group-level adjusted mean reported for each treatment arm. LDL-C is one component of the lipid profile that the study set out to assess. The registry says calculated LDL-C values were derived using the Friedewald formula. The endpoint is labeled as a Week 24 result, and the registry describes the reported values as adjusted least-squares means with standard errors.

A percent change expresses the outcome relative to each participant’s baseline level, so the endpoint focuses on change rather than only on the follow-up LDL-C value. Comparing the adjusted group means provides an estimate of the average difference between randomized groups, while accounting for the repeated-measure structure described in the registry. The model used available post-baseline observations from Week 4 to Week 52, whether participants were on or off treatment, to estimate the Week 24 means.

These modeling choices are relevant because follow-up measurements can be missing and participants may have measurements at different visits. A repeated-measures model can use observed measurements across visits rather than restricting the analysis to participants with a complete set of measurements. The registry says the model was used to account for missing data, but does not report the assumptions made about why measurements were missing or a separate sensitivity analysis of those assumptions.

7. Results Posted in the Registry

• Alirocumab 75 mg/up to 150 mg: mean -48.70 versus 2.80 on control; difference -51.50 (95% CI -58.13 to -44.87), standardized effect d = -2.08; 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 From Baseline in Calculated LDL-C at Week 24 - On-Treatment Analysis

• 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 75 mg/up to 150 mg: mean -49.40 versus 2.70 on control; difference -52.10 (95% CI -58.57 to -45.63), standardized effect d = -2.13; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alirocumab 75 mg/up to 150 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percent Change From Baseline in Calculated LDL-C at Week 12 - ITT Analysis

• 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 75 mg/up to 150 mg: mean -43.80 versus 4.60 on control; difference -48.40 (95% CI -54.60 to -42.20), standardized effect d = -2.08; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alirocumab 75 mg/up to 150 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percent Change From Baseline in Calculated LDL-C at Week 12 - On- Treatment Analysis

• 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 75 mg/up to 150 mg: mean -44.20 versus 4.60 on control; difference -48.80 (95% CI -55.00 to -42.60), standardized effect d = -2.10; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alirocumab 75 mg/up to 150 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes include additional analyses of calculated LDL-C at Week 12 and Week 24, as well as measures involving Apo B, non-HDL-C, and total cholesterol. The registry lists 24 secondary outcomes as posted. Among the detailed LDL-C results, the adjusted comparisons at Week 12 and the on-treatment Week 24 analysis are directionally consistent with the primary Week 24 ITT estimate: each reports a negative difference between alirocumab and placebo. They provide context across visits and analysis populations, rather than a separate basis for replacing the primary result.

The Week 12 ITT and on-treatment estimates address different analysis definitions, and the Week 24 on-treatment result is not the same estimand as the primary ITT comparison. Such differences matter because restricting to on-treatment observations can change which measurements contribute, while an ITT analysis is intended to preserve the randomized comparison as defined in the registry. The registry’s ITT definition still requires baseline and post-baseline measurements, so it should be interpreted according to that stated population rather than assumed to include participants with no outcome measurements.

Secondary outcomes can help assess whether the primary pattern is seen in related measures and at other time points. However, testing many outcomes increases the chance of observing apparently notable results even when no corresponding underlying differences exist. The registry record does not report a multiplicity adjustment or a hierarchy for the secondary tests. Therefore, individual secondary p-values carry less weight than the primary analysis unless the analysis plan explains how the family of comparisons was controlled. The record does not report enough detail to assess that issue fully, and the listed outcome names alone do not establish the direction or size of every secondary result.

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

• Percent Change From Baseline in Calculated LDL-C at Week 24 - On-Treatment Analysis
• Percent Change From Baseline in Calculated LDL-C at Week 12 - ITT Analysis
• Percent Change From Baseline in Calculated LDL-C at Week 12 - On- Treatment Analysis
• Percent Change From Baseline in Apolipoprotein (Apo) B at Week 24 - ITT Analysis
• Percent Change From Baseline in Apo B at Week 24 - On-Treatment Analysis
• Percent Change From Baseline in Non-High -Density Lipoprotein Cholesterol (Non-HDL-C) at Week 24 - ITT Analysis
• Percent Change From Baseline in Non-HDL-C at Week 24 - On-Treatment Analysis
• Percent Change From Baseline in Total Cholesterol (Total-C) at Week 24 - ITT Analysis

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: it is a percent change in calculated LDL-C. For a continuous outcome, a mean summarizes the center of the observed or modeled group results. The reported values are least-squares means, which are model-adjusted group estimates rather than necessarily the arithmetic averages of the raw participant measurements. In this trial, the registry reports adjusted least-squares means and standard errors from a mixed model for repeated measures. The standard error describes the precision of an estimated mean; it is not the range of individual participant results.

Why use a repeated-measures model?

Repeated measurements mean that a participant can contribute LDL-C observations at more than one follow-up visit. Such measurements from the same participant are related, rather than independent. A mixed model for repeated measures accommodates this structure and can estimate group means over time while using observed measurements from different visits. The registry says the model used all available post-baseline data from Week 4 to Week 52, regardless of on- or off-treatment status, to obtain the Week 24 adjusted means and to account for missing data.

Using available observations can avoid limiting the analysis to people with a complete measurement at every visit. However, the model does not make missing outcomes known. Its interpretation relies on statistical assumptions about the observed data and missingness. The registry record does not report the detailed missing-data assumptions, model specification, covariance structure, or sensitivity analyses. Those details would help assess how robust the estimate is to different patterns of missing measurements.

What does the between-group estimate represent?

The sponsor’s primary analysis reports a least-squares mean difference of -51.4 for alirocumab compared with placebo. This is an adjusted estimate of the contrast between the two group means on the percent-change scale. A negative value indicates that the estimated percent change was lower in the alirocumab group than in the placebo group. The registry also posts an unadjusted recalculation based on summary statistics. That recalculation is a separate, simpler comparison; it does not reproduce the repeated-measures model or its adjustment for the pattern of measurements.

For a continuous outcome, a mean difference is naturally expressed in the same units as the outcome. Here, the outcome is percent change, so the contrast is measured on that scale. Its interpretation should remain tied to the endpoint definition and modeled population rather than being treated as a raw difference in LDL-C concentration.

How should the p-value be understood?

The sponsor reports p < 0.001 for the primary comparison. In general, a p-value measures how incompatible the observed data are with a specified null model, assuming that model and the analysis assumptions are correct. It is not the probability that the result occurred by chance, nor is it a direct measure of effect size or clinical importance. The confidence interval adds information about the range of effect estimates that are reasonably compatible with the data and model.

The registry separately posts p < 0.001 for the unadjusted recalculation. These values arise from different analyses, so they should not be treated as interchangeable. The sponsor’s mixed-model analysis takes precedence as the reported trial analysis; the recalculation is useful as an independent descriptive check, but it does not replace the sponsor’s model.

What does the ITT label mean in this record?

The registry defines the ITT population as all randomized participants with one baseline and at least one post-baseline calculated LDL-C value, whether on or off treatment. This is the registry’s operational definition for this endpoint. It is not literally every randomized participant, because a participant without the specified measurements would not meet the posted definition. The distinction is important when interpreting the sample sizes and when assessing how missing outcome data could affect the result.

The primary endpoint title specifies Week 24, while the timeframe field refers to baseline through Week 52. The description says the estimates at Week 24 were obtained from a repeated-measures model using available observations through Week 52. These statements can be read together as a Week 24 modeled estimate informed by repeated data over the longer stated period, but the registry does not provide further detail about the timing or full specification of the analysis.

11. Confidence Intervals and Precision

The sponsor-reported primary contrast is -51.4, with a 95% confidence interval from -58.1 to -44.8. A confidence interval describes a range of estimates compatible with the observed data and the statistical model at the stated confidence level. It communicates both the direction and the precision of the estimated between-group difference. Here the full interval is negative, indicating that the modeled difference is on the side of a greater decrease in calculated LDL-C in the alirocumab group relative to placebo.

The interval is relatively concentrated around its reported estimate, but precision is not the same as certainty about every feature of the result. It reflects sampling uncertainty under the model and does not account for every possible source of bias, missing-data assumption, or limitation in how the registry reports the analysis. The confidence interval also does not describe the spread of outcomes among individual participants. Individual results can vary even when an estimate of the group-average contrast is precise.

The arm-level estimates are -48.7 for alirocumab and 2.8 for placebo, with standard errors of 1.9 and 2.8, respectively. Those standard errors concern the precision of each adjusted mean, not the difference itself. The sponsor’s confidence interval for the contrast is more directly relevant to the uncertainty in the comparative estimate. The registry also reports a 95% interval for the recalculated comparison, from -58.13 to -44.87. That interval belongs to the unadjusted recalculation and should not be confused with the sponsor’s model-based interval.

Neither interval establishes clinical importance on its own. The registry record does not report a threshold for a clinically important difference. Precision describes statistical uncertainty around the estimated effect; deciding what that effect means in clinical context requires information beyond the interval and p-value.

12. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total event counts. They are illustrations based on the observed effect rather than the trial’s original design calculation. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The target effect is set at a stated fraction of the observed effect.

For planning at 100% of the observed effect, the illustration gives 4 participants per arm for 80% power and 5 participants per arm for 90% power. At 75% of the observed effect, it gives 7 participants per arm for 80% power and 9 participants per arm for 90% power. At 50% of the observed effect, it gives 15 participants per arm for 80% power and 20 participants per arm for 90% power. These values are model-based planning illustrations and do not describe the enrolled sample or the trial’s actual power.

In general, the 80% power column represents the number of participants per arm estimated to give an 80% chance of detecting the specified effect under the planning assumptions, if that effect is real. The 90% column expresses the same idea for a higher target probability of detection. For the same effect and assumptions, aiming for higher power generally requires more participants. Smaller effects are harder to distinguish from random variation, so the illustration requires more participants per arm as the target effect becomes a smaller fraction of the observed effect.

The original sample-size justification and design assumptions are not reported in the registry record. The planning illustration is not observed power: it cannot establish the probability that this completed trial detected an effect after the results were known. Its values depend on assumptions drawn from the observed effect and a simplified normal approximation, and they should not be treated as recommended enrollment targets for another study.

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 = -51.500; pooled standard deviation σ = 24.717.
2. n = 2 × (1.96 + 0.842)² × 24.717² / -51.500² = 3.6, rounded up to 4 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 <- -51.5                      # observed difference in means
sigma <- 24.7172665419565                     # 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(1709500)
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 = 4 (80% power), 5 (90% power)
 75% of observed effect: n per arm = 7 (80% power), 9 (90% power)
 50% of observed effect: n per arm = 15 (80% power), 20 (90% power)
power.t.test: 4.8 
Simulated power at n = 4 per arm: 0.696 (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-reported primary analysis used a mixed model and estimated a least-squares mean difference of -51.4, with a 95% confidence interval from -58.1 to -44.8 and p < 0.001. The recalculated comparison is a simpler, unadjusted analysis of posted summary statistics. It estimates a difference of -51.5, with a 95% confidence interval from -58.13 to -44.87 and p < 0.001. The two estimates are close, and both indicate a negative between-group difference on the percent-change scale.

The agreement is a useful consistency check, but the analyses are not identical. The sponsor’s result comes from the stated repeated-measures model, which uses observations over time and reports adjusted estimates. The recalculation uses summary statistics and does not reproduce that model. It should therefore be described as an unadjusted recalculation, not as a replacement for the trial’s own analysis. Because the registry does not flag a discrepancy, the posted comparison does not indicate a conflict that would require resolving in favor of a different estimate.

For the trial’s primary conclusion about its modeled endpoint, the sponsor’s own analysis is the principal result to interpret. The recalculation offers a supplementary check of whether the aggregate summaries point in a similar direction and have similar magnitude; it does not validate the model assumptions or independently confirm the underlying participant-level analysis.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several statistical hypotheses are tested. With more tests, the chance of at least one apparently strong result can increase, even if each test is interpreted using the same nominal significance threshold. The registry lists numerous secondary outcomes, including several LDL-C analyses and outcomes involving Apo B, non-HDL-C, and total cholesterol. It does not report whether the trial used a multiplicity adjustment, a prespecified testing hierarchy, or another approach to control the interpretation of multiple comparisons. The original statistical analysis plan is not reported in the registry record.

This omission is most relevant when interpreting secondary p-values. The primary endpoint is the principal planned comparison in the registry results, while secondary analyses are supportive or exploratory unless a prespecified strategy establishes otherwise. Without the multiplicity plan, the individual secondary results should not be treated as having the same confirmatory status as the primary result.

Missing data are addressed in the primary endpoint description through a mixed model for repeated measures, which used available post-baseline data from Week 4 to Week 52 and was stated to account for missing data. This describes the model’s role but does not reveal the assumptions about the reason measurements were missing. The record does not report the missingness pattern, a detailed imputation method, or sensitivity analyses that test alternative assumptions. A model can use incomplete follow-up data, but it cannot remove uncertainty about outcomes that were not observed.

The analysis population is also specifically defined. The registry calls it ITT, but requires a baseline and at least one post-baseline calculated LDL-C value, on or off treatment. This may exclude randomized participants who did not meet those measurement criteria. The record does not provide enough detail to assess how many participants were excluded from the primary analysis or how their missing measurements might affect the comparison. These reporting gaps limit independent evaluation of the analysis, even though the model-based estimate and its interval are posted.

16. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: acute coronary syndrome (1.2%), angina unstable (1.2%), cardiogenic shock (1.2%), myocardial infarction (1.2%), gastrointestinal haemorrhage (1.2%).

For serious adverse events, the registry reports 10 affected participants among 167 at risk in the alirocumab group and 7 among 81 at risk in the placebo group. For other adverse events, it reports 65 affected participants among 167 at risk in the alirocumab group and 35 among 81 at risk in the placebo group. These are participant counts, not measures of event severity beyond the registry’s serious-versus-other classification, and the counts alone do not establish that an event was caused by treatment.

The listed serious adverse event terms each have a reported frequency of 1.2%: acute coronary syndrome, unstable angina, cardiogenic shock, myocardial infarction, gastrointestinal haemorrhage, and non-cardiac chest pain. The registry record does not state in this summary whether the categories are mutually exclusive, so the terms should not be summed or interpreted as a count of distinct participants. Death counts are not reported in the registry record.

These figures provide a descriptive comparison of the recorded adverse-event experience over the trial, not a full assessment of causation or comparative risk. The registry summary does not supply further information about event timing, adjudication, or attribution. Safety interpretation should therefore remain limited to the posted counts and terms.

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

The primary result describes a substantial negative difference in adjusted percent change in calculated LDL-C between the randomized groups, with a 95% confidence interval that remains below zero. It supports the interpretation that the modeled group-average LDL-C change differed between alirocumab and placebo in this trial population. The result is specific to the study’s endpoint, analysis population, measurement schedule, and model.

It does not show that every participant experienced the group-average change, or that individual responses were uniform. It does not by itself establish the effect on outcomes beyond calculated LDL-C, including outcomes not reported as the primary endpoint. Nor does a low p-value prove the result is clinically important. The registry does not report a clinical-importance threshold for interpreting the size of the difference.

The findings also do not resolve every uncertainty about missing data, the assumptions of the repeated-measures model, or the interpretation of multiple secondary outcomes. The registry identifies the model and the period of data used but does not report all modeling details or sensitivity analyses. The ITT population definition requires at least one post-baseline measurement, and the original analysis plan is not reported in the registry record.

The adverse-event counts are descriptive and cannot establish causation. They should not be converted into a conclusion about an individual’s likely experience. The trial results characterize measured outcomes in the enrolled study population under the recorded treatment and analysis conditions; they are not a guarantee of results in other populations or circumstances.

18. Why This Trial Matters Statistically

Statistically, this trial illustrates why the analysis method and the endpoint label matter alongside the reported estimate. The primary result is not simply a comparison of raw endpoint averages: it is a least-squares mean contrast from a repeated-measures model using available follow-up observations. The registry’s description makes clear that the Week 24 estimate was informed by measurements from Week 4 through Week 52, including observations collected on or off treatment. Understanding that structure helps readers interpret what the estimate summarizes.

The result also shows how different summaries answer related but distinct questions. The sponsor’s model-based analysis is the main trial result, while the unadjusted recalculation provides a simpler aggregate comparison. Their close estimates are reassuring as a descriptive consistency check, but the recalculation cannot verify the repeated-measures assumptions or replace participant-level modeling.

The trial is also a reminder to separate statistical evidence from clinical interpretation. The confidence interval quantifies uncertainty around the group contrast under the analysis model, and the p-value describes compatibility with a null model. Neither alone defines clinical importance or captures all risks of bias. Secondary outcomes and missing-data decisions add further layers of interpretation, especially when the registry does not describe multiplicity control or sensitivity analyses.

Finally, planning illustrations based on an observed effect are not equivalent to the original design rationale. Here the registry record does not report the original sample-size justification. Keeping planning calculations distinct from the completed trial’s observed sample and results avoids conflating assumptions about future studies with evidence from this one.

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 registry’s endpoint labeling requires care: the primary outcome title specifies Week 24, while the timeframe field says baseline to Week 52. Its description states that the model estimated Week 24 means using available post-baseline data through Week 52, but the registry does not provide further detail that would fully resolve how the fields were intended to align.

The record does not report the original sample-size justification, full statistical analysis plan, detailed model specification, or missing-data sensitivity analyses. It says the repeated-measures model accounted for missing data, but does not describe the assumptions about why measurements were missing. The ITT definition also requires a baseline and at least one post-baseline LDL-C measurement, so it is narrower than all randomized participants if anyone lacked those measurements; the number meeting or failing the criterion is not reported in the registry record.

The registry does not report whether multiplicity was controlled across the many secondary outcomes. This limits how strongly individual secondary findings can be interpreted as confirmatory. The detail available for secondary outcomes is also uneven: a list of outcome names does not provide the numerical results or precision for each listed outcome.

Safety reporting in the posted summary is limited to participant counts and selected serious adverse event terms. Death counts are not reported in the registry record, and the summary does not provide the additional information needed to establish event attribution or understand overlap among listed terms. These are limitations of the available registry reporting and should not be treated as evidence that the unreported details had any particular value.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study of Alirocumab (REGN727/SAR236553) in Patients With heFH (Heterozygous Familial Hypercholesterolemia) Who Are Not Adequately Controlled With Their LMT (Lipid-Modifying Therapy) — NCT01709500.
• Registry record last updated 2015-10-28; status last verified 2015-09.
• Results first posted 2015-10-28.
• 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

This completed Phase 3 randomized, double-blind, placebo-controlled, parallel-group study enrolled 249 participants with heterozygous familial hypercholesterolemia whose lipid-modifying therapy was not adequately controlling their condition. Participants received alirocumab, starting at 75 mg every two weeks with possible up-titration to 150 mg, or matched placebo alongside background therapy.

The primary endpoint was percent change from baseline in calculated LDL-C, labeled at Week 24 and analyzed using a repeated-measures model with available data through Week 52. The sponsor-reported adjusted difference was -51.4, with a 95% confidence interval from -58.1 to -44.8 and p < 0.001. The registry also lists secondary lipid outcomes and descriptive adverse-event counts. Details of the original sample-size rationale, multiplicity strategy, and several modeling and missing-data assumptions are not reported in the registry record.