Olpasiran Trials of Cardiovascular Events And LipoproteiN(a) Reduction - DOSE Finding Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Olpasiran Trials of Cardiovascular Events And LipoproteiN(a) Reduction - DOSE Finding Study (NCT04270760), a randomized phase 2 study. The primary outcome is Percentage Change From Baseline in Lipoprotein(a) (Lp[a]) at Week 36.

2. Clinical Question

This is a biomarker question, not a direct test of whether treatment changes the risk of cardiovascular events. Cardiovascular disease is listed as the condition, but the primary endpoint is Lp(a), a continuous laboratory measure. The study title refers to cardiovascular events and Lp(a) reduction; the primary outcome posted for this analysis is the Week 36 percentage change in Lp(a).

The registry identifies the study as phase 2 and completed. Its listed study dates are 2020-07-28 for start and 2021-12-27 for primary completion. The results address the biomarker response over the stated follow-up time; they do not by themselves establish longer-term clinical effects or answer questions beyond the outcomes reported in the registry record.

3. Trial Design

The registry describes a randomized, double-blind, parallel-group, placebo-controlled phase 2 study sponsored by Amgen. It enrolled 281 participants and is marked completed. The official title describes a study of olpasiran efficacy, safety and tolerability in subjects with elevated Lp(a). The brief study description focuses on the effect of subcutaneous olpasiran compared with placebo on percentage change from baseline in Lp(a).

Five groups are listed. Four received olpasiran: 10 mg Q12W, 75 mg Q12W, 225 mg Q12W, and 225 mg Q24W. The fifth received placebo Q12W. The registry labels masking as double and allocation as randomized. The arm descriptions do not give additional details about delivery, adherence, or treatment procedures, so those details are not reported in the registry record.

The primary endpoint was percentage change from baseline in Lp(a) at Week 36, with the stated timeframe of baseline and Week 36. The analysis population was the FAS: randomized participants who received at least one dose of investigational product, with data available at each time point. The registry says the reported least squares means come from a repeated measures linear effects model including treatment group, stratification factors, scheduled visit, and the interaction between treatment group and scheduled visit.

The registry lists secondary outcomes for Week 48 Lp(a), LDL-C and ApoB at Week 36 and Week 48, and mean serum olpasiran concentrations at Day 1, Week 24 and Week 48. It also records secondary outcomes and analyses, but the numerical results for several listed outcomes are not reported in the registry record. Details such as the identities of stratification factors, original sample-size justification, and planned interim analyses are not reported in the registry record.

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: The Treatment Period was 48 weeks with investigational product (IP) administered subcutaneously (SC) every 12 weeks (Q12W) or 24 weeks (Q24W). After Week 48 there was an Extended Safety Follow-up Period without further dosing with IP for a minimum of 24 weeks. Participants remained on standard of care per their local guidelines during the Treatment Period and Extended Safety Follow-up Period.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Participants in the FAS with data available at each time point. FAS: includes all randomized participants who received at least one dose of IP.

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: Full Analysis Set (FAS): includes all randomized participants who received at least one dose of IP.

6. Primary Endpoint

The registry lists the primary outcome as Percentage Change From Baseline in Lipoprotein(a) (Lp[a]) at Week 36, measured over Baseline and Week 36.

The primary endpoint is the percentage change from baseline in lipoprotein(a), or Lp(a), at Week 36. It expresses how the measured Lp(a) value at follow-up compares with that participant’s baseline value, on a percentage scale. A negative percentage change indicates a reduction relative to baseline; a positive value indicates an increase. The outcome is continuous, rather than a count of clinical events or a yes-or-no outcome.

The registry reports least squares means from a repeated measures linear effects model. These are model-based estimates, not simple averages of the observed values in each group. The stated model includes treatment group, stratification factors, scheduled visit, and the interaction between treatment group and scheduled visit. The identities of the stratification factors are not reported in the registry record.

Lp(a) is used as a biomarker endpoint: it allows the study to assess change in a specified laboratory measure over the trial’s follow-up. The registry’s primary question is whether the estimated percentage change differs between each olpasiran regimen and placebo. This endpoint does not directly measure cardiovascular events, symptoms, or quality of life. A difference in a biomarker result should therefore be interpreted as evidence about that measured outcome, not as a direct estimate of a clinical benefit or harm.

The registry gives standard errors alongside the group least squares means. A standard error describes the uncertainty in an estimated mean; it is not the spread of individual participant measurements. The group estimates and model-based treatment comparisons answer related but different questions: the former describe estimated change within each group, while the latter quantify the estimated difference between an olpasiran group and placebo.

7. Results Posted in the Registry

• Group 1: Olpasiran 10 mg Q12W: mean -66.91 versus 3.60 on control; difference -70.51 (95% CI -75.60 to -65.42), standardized effect d = -5.24; z-test p = <0.001.
• Group 2: Olpasiran 75 mg Q12W: mean -93.78 versus 3.60 on control; difference -97.38 (95% CI -102.47 to -92.29), standardized effect d = -7.23; z-test p = <0.001.
• Group 3: Olpasiran 225 mg Q12W: mean -97.53 versus 3.60 on control; difference -101.13 (95% CI -106.27 to -95.99), standardized effect d = -7.56; z-test p = <0.001.
• Group 4: Olpasiran 225 mg Q24W: mean -96.89 versus 3.60 on control; difference -100.49 (95% CI -105.67 to -95.31), standardized effect d = -7.45; 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.

Percentage Change From Baseline in Lp(a) at Week 48

• 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:
  • Group 1: Olpasiran 10 mg Q12W: mean -64.89 versus 3.59 on control; difference -68.48 (95% CI -74.68 to -62.28), standardized effect d = -4.17; z-test p = <0.001.
  • Group 2: Olpasiran 75 mg Q12W: mean -92.54 versus 3.59 on control; difference -96.13 (95% CI -102.33 to -89.93), standardized effect d = -5.86; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Group 1: Olpasiran 10 mg Q12W than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Group 2: Olpasiran 75 mg Q12W than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The named secondary outcomes broaden the assessment beyond the primary Week 36 Lp(a) endpoint. They include Lp(a) percentage change at Week 48, LDL-C percentage change at Week 36 and Week 48, ApoB percentage change at Week 36 and Week 48, and mean serum olpasiran concentrations at Day 1, Week 24 and Week 48. The registry therefore lists both additional biomarker outcomes and drug concentration measurements.

The posted numerical results for Week 48 Lp(a) generally follow the direction of the Week 36 primary result among the displayed groups: the olpasiran group estimates are negative and the placebo estimate is positive. The registry also reports model-based comparisons for two olpasiran regimens at Week 48, with negative treatment differences and p-values of < 0.001. This pattern is consistent with the primary endpoint’s direction, but it remains evidence about Lp(a), not a direct clinical-event outcome.

Numerical results for LDL-C, ApoB, and serum olpasiran concentrations are not reported in the registry record in the results detail available for interpretation. The record lists these outcomes, but without numerical estimates it is not possible to assess their direction, magnitude, or precision. They should not be inferred from the Lp(a) results.

Secondary outcomes usually carry less confirmatory weight than a prespecified primary outcome, particularly when many outcomes, time points, or comparisons are considered. Testing multiple hypotheses increases the chance of at least one apparently notable result unless the analysis plan accounts for that multiplicity. The registry does not report a multiplicity adjustment or testing hierarchy for these outcomes. Accordingly, secondary findings can add context and help describe the observed pattern, but the unadjusted secondary results should be interpreted cautiously and should not replace the primary analysis.

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

• Percentage Change From Baseline in Lp(a) at Week 48
• Percentage Change From Baseline in Low Density Lipoprotein Cholesterol (LDL-C) at Week 36 and Week 48
• Percentage Change From Baseline in Apolipoprotein (B) (ApoB) at Week 36 and Week 48
• Mean Serum Olpasiran Concentrations at Day 1, Week 24 and Week 48

9. Statistical Interpretation

10. Statistical Methods Explained

What does the repeated measures model contribute?

The registry reports a repeated measures linear effects model for the primary outcome. In general, repeated measures methods analyze observations collected at multiple scheduled visits while accounting for the fact that measurements from the same participant are related. A model can use the pattern of available measurements across visits rather than treating each visit as a wholly separate experiment. The registry says the model includes treatment group, stratification factors, scheduled visit, and the interaction of treatment group with scheduled visit.

The treatment-by-visit interaction allows the estimated treatment contrast to depend on the scheduled visit. That is relevant when the outcome is followed over time and the question concerns a particular visit, such as Week 36. The listed primary estimate is for the stated Week 36 endpoint. The registry does not identify the stratification factors or report further details about the model’s covariance structure, estimation procedure, or model diagnostics; those details are not reported in the registry record.

What is a least squares mean?

General explanation: a least squares mean is a model-based group estimate, often described as an adjusted mean. It is derived from the fitted model rather than calculated as a plain arithmetic average. Here, the registry explicitly says that least squares means come from the repeated measures model and identifies the terms included in that model. Since those terms account for features in the analysis, the estimated group values and between-group treatment differences need not match simple unadjusted calculations from summary statistics.

The primary outcome is a continuous measure. The reported group values are least squares means and their dispersion field is a standard error. A standard error describes uncertainty in an estimate of the mean. It does not describe the full spread of individual measurements. The registry’s treatment difference compares the model-estimated change in an olpasiran group with the model-estimated change in placebo. A negative treatment difference indicates a more negative estimated percentage change for olpasiran on this scale.

How should p-values be read?

General explanation: a p-value describes how unusual data at least as incompatible with a specified null hypothesis would be if that null hypothesis and the analysis assumptions were true. It is not the probability that the null hypothesis is true, and it does not measure the probability that a result occurred by chance in an everyday sense. The sponsor-reported primary comparisons have p-values of < 0.001. The registry labels these comparisons as superiority analyses. A small p-value is not a measure of clinical importance and does not establish a clinical effect beyond the endpoint analyzed.

The registry’s reported p-values arise from its repeated measures analysis. The separate recalculations use posted summary statistics to make simple, unadjusted comparisons; their p-values are not a replacement for the sponsor’s model-based results. The methods and assumptions are not identical, so the two approaches should not be treated as interchangeable analyses.

Why do confidence intervals matter?

General explanation: a confidence interval describes a range of estimates compatible with the data and the method used, at a stated confidence level. It conveys precision as well as direction. A narrower interval indicates greater precision under that method; a wider interval leaves more uncertainty about the magnitude. The sponsor reports 95% confidence intervals for the primary treatment differences. Intervals that do not include zero are consistent with a nonzero difference under the model and its assumptions, but they do not establish that the difference is clinically important.

The recalculated confidence intervals are derived from the posted group summaries and are unadjusted. The calculation uses an approximate pooled standard deviation inferred from the standard errors, as indicated in the posted recalculation details. This is a simplifying approach and does not reproduce the repeated measures model, its covariate adjustment, or any unreported analysis decisions. These recalculations are therefore best understood as a check based on summary statistics, not as a second sponsor analysis.

What do the analysis populations and missing measurements mean?

The registry defines the FAS as randomized participants who received at least one dose of investigational product. The primary result is described as using FAS participants with data available at each time point. This definition clarifies who contributes to the stated analysis, but does not explain how missing observations were handled by the model, whether any sensitivity analyses were performed, or whether other analysis populations were used for the primary endpoint. Those details are not reported in the registry record.

General explanation: missing outcome data can affect precision and may affect interpretation if the probability of missingness is related to participants’ outcomes or treatment experience. Repeated measures models can use observed data under assumptions about the missing-data process, but the registry description alone does not establish which assumptions are appropriate or whether they hold. The record does not report enough information to evaluate this issue fully.

Why can over-dispersion matter in other outcome types?

General explanation: for count outcomes, over-dispersion means the observed variability exceeds what a basic count model would expect. If it is ignored, standard errors and confidence intervals may be too small, making estimates appear more precise than they are. This primary endpoint is continuous, so over-dispersion is not the central issue for its reported model. The general concept matters when interpreting statistical methods for count outcomes, but no count-outcome analysis is described for this primary endpoint.

Overall, the reported model provides adjusted, visit-specific estimates for the continuous biomarker outcome, while the recalculated comparisons provide unadjusted illustrations from posted summary statistics. The registry does not report all analysis details needed to independently reproduce the sponsor’s model. The reported sponsor analysis is therefore the primary basis for interpreting the posted Week 36 comparison.

11. Confidence Intervals and Precision

The sponsor-reported 95% confidence intervals for the primary treatment differences are entirely below zero. For 10 mg Q12W, the estimate is -70.51 with a 95% confidence interval from -75.12 to -65.90. For 75 mg Q12W, the estimate is -97.38 with a 95% confidence interval from -101.98 to -92.77. For 225 mg Q12W, the estimate is -101.13 with a 95% confidence interval from -105.79 to -96.47. For 225 mg Q24W, the estimate is -100.49 with a 95% confidence interval from -105.16 to -95.82.

These intervals describe uncertainty around the model-based treatment differences on the percentage-change scale. Their position below zero is consistent with the negative direction of the estimated contrasts. They do not show the range of individual participant responses, and they do not represent a prediction interval for a future participant or study.

General explanation: a confidence interval is a repeated-sampling procedure with a stated confidence level. It summarizes precision under the analysis model and its assumptions; it is not a guarantee that the true value lies within a particular calculated interval. Precision should be considered alongside the endpoint and study design. In this trial, the endpoint is a biomarker at Week 36, so precision of the biomarker contrast does not answer how precisely any clinical-event effect has been estimated.

The recalculated intervals use an unadjusted method based on posted summary statistics, while the sponsor intervals come from the repeated measures linear effects model. Small differences between their estimates or interval limits can arise because the methods use different information and assumptions. The sponsor-reported intervals are the appropriate reference for the sponsor’s model-based result; the recalculated intervals are supplementary checks, not substitutes for the registry analysis.

The registry does not report all information needed to judge precision beyond these intervals, including a full account of missing-data handling and model diagnostics. As a result, the intervals provide a useful description of statistical uncertainty under the reported model, but they do not eliminate uncertainty about unreported assumptions or generalizability.

12. Planning a Similar Trial: Sample Size

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

The sample-size illustrations are expressed as participants per arm, not as total participants or total events. The calculations are planning illustrations based on the observed effect, not the original design assumptions for this trial. Their stated assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect. The original sample-size justification and planning assumptions for the trial are not reported in the registry record.

The 80% power column gives the illustrated number of participants per arm for a hypothetical future comparison to have an 80% chance of meeting the chosen statistical criterion if the assumed effect and other planning assumptions hold. The 90% power column gives the corresponding illustration for a 90% chance. These are planning concepts; they do not describe the probability that the completed trial’s result is correct. The posted illustrations are not observed power.

The effect fractions represent scenarios that use the full observed effect, 75% of the observed effect, or 50% of the observed effect. Smaller assumed effects require more participants to detect under otherwise unchanged assumptions. For example, the primary comparison illustrations include 1 participant per arm for both power targets at the full observed effect in the listed comparisons, while the 50% effect scenarios require more participants per arm. Such values can look unusually small because the calculations are anchored to the large effects observed in this trial and use a normal approximation.

These calculations are not a reconstruction of the trial’s enrollment decision. They do not account for unreported design considerations such as anticipated attrition, multiplicity, practical recruitment limits, or the original protocol’s chosen target effect. For time-to-event outcomes the stated convention would be total events, but the primary endpoint is continuous, and these planning figures are participants per arm.

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 = -70.510; pooled standard deviation σ = 13.466.
2. n = 2 × (1.96 + 0.842)² × 13.466² / -70.510² = 0.6, rounded up to 1 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 <- -70.51                      # observed difference in means
sigma <- 13.4663759464852                     # 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(4270760)
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 = 1 (80% power), 1 (90% power)
 75% of observed effect: n per arm = 2 (80% power), 2 (90% power)
 50% of observed effect: n per arm = 3 (80% power), 4 (90% power)
power.t.test: 2.1 
Simulated power at n = 1 per arm: NA (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 results use a repeated measures linear effects model and report treatment differences, 95% confidence intervals, and p-values. The recalculated comparisons are simple unadjusted re-calculations from posted group summary statistics. They are useful as a separate numerical check but do not reproduce the sponsor’s adjustment for treatment group, stratification factors, scheduled visit, and the treatment-by-visit interaction.

The recalculated primary treatment-difference estimates are -70.51, -97.38, -101.1, and -100.5 for the four listed olpasiran regimens, respectively. The corresponding sponsor estimates are -70.51, -97.38, -101.13, and -100.49. The registry does not flag a discrepancy. Differences in the last reported digits for some estimates, and differences between recalculated and sponsor confidence intervals, reflect that the recalculation is not the same analysis as the sponsor’s model-based comparison.

For the sponsor’s analysis, the posted 95% confidence intervals and p-values should be used when describing the primary model-based findings. The recalculations should not be interpreted as an independent replication, nor as a correction to the sponsor analysis. They are based on summary statistics and rely on simplifying assumptions; the sponsor’s model uses the repeated measures approach described in the registry record.

15. Multiplicity, Missing Data and Analysis Populations

The registry record gives results for the primary Week 36 Lp(a) endpoint and lists several secondary outcomes and analyses. It does not report a multiplicity adjustment, a hierarchy or gatekeeping procedure for hypotheses, or whether the reported p-values were adjusted for multiple comparisons. These items are not reported in the registry record. The reported p-values should therefore be read as the values attached to the listed analyses, without assuming that the family of comparisons was controlled in a particular way.

Multiplicity matters because the probability of observing at least one apparently strong result can increase when many endpoints, time points, or treatment comparisons are tested. This does not mean that any particular result is false; it means that the evidential meaning of an individual p-value depends partly on the wider testing plan. The registry’s four primary treatment comparisons and its multiple secondary outcomes make the missing multiplicity details relevant to interpretation. The record does not establish whether an adjustment was planned or used outside the posted results.

The registry defines the FAS as randomized participants who received at least one dose of investigational product. For the primary analysis, it further describes participants as having data available at each time point. It does not report how many participants contributed to each model estimate beyond the arm-level counts presented with the results, or describe the handling of missing values, withdrawals, or incomplete follow-up in detail. Imputation methods, missing-data sensitivity analyses, and reasons for missing observations are not reported in the registry record.

General explanation: a repeated measures model can use observed data across visits, but its interpretation depends on assumptions about the relationship between missingness and unobserved outcomes. The brief model description does not provide enough information to assess those assumptions. The registry also does not report interim analyses or the original sample-size justification. These omissions limit assessment of the full analysis plan, but they do not alter the numerical results as posted.

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: osteoarthritis (3.7%), cholangitis (1.9%), cervical spinal stenosis (1.9%), gastrointestinal cancer metastatic (1.9%), metastases to pancreas (1.9%).

The registry reports serious adverse event counts separately for the treatment period and the extended safety follow-up period, with an at-risk count for each group and period. During the treatment period, the serious-event counts are 3 for olpasiran 10 mg Q12W, 3 for olpasiran 75 mg Q12W, 6 for olpasiran 225 mg Q12W, 4 for olpasiran 225 mg Q24W, and 8 for placebo Q12W. The listed at-risk counts are 58, 58, 56, 55, and 54, respectively.

During extended safety follow-up, the serious-event counts are 4, 2, 6, 5, and 4 across those same groups. The listed at-risk counts are 57, 57, 54, 55, and 53. These are counts of participants reported with serious adverse events, not rates adjusted for duration of exposure. The registry also records no deaths in the olpasiran groups during the treatment period and 1 death in the placebo group; during extended safety follow-up, it records no deaths in the listed groups.

The record lists serious-event terms including osteoarthritis, cholangitis, cervical spinal stenosis, gastrointestinal cancer metastatic, metastases to pancreas, and ischaemic stroke, with the percentages attached to those terms as posted. These figures should be read as descriptive safety reporting. The record does not establish that an event was caused by a study treatment, and these counts alone do not support a comparative safety conclusion. Full event definitions, exposure-adjusted analyses, and further context are not reported in the registry record.

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

The Week 36 results show model-estimated differences in percentage change in Lp(a) between each olpasiran regimen and placebo. The sponsor-reported estimates are negative, their 95% confidence intervals lie below zero, and the registry reports p-values of < 0.001 for each primary comparison. In the context of this endpoint, that pattern indicates that the estimated Lp(a) change was more negative in each olpasiran group than in placebo at the specified visit.

The result does not directly show that cardiovascular events were reduced. The primary endpoint is a biomarker, not a clinical event. Although cardiovascular disease appears among the trial conditions and the study title refers to cardiovascular events, the primary results described in the registry are about Lp(a) change. The record does not provide a primary cardiovascular-event result that could answer whether clinical event risk differed.

The results also do not establish the effect of treatment outside the studied population, regimens, and follow-up described in the record. They do not resolve questions about longer-term outcomes, unreported secondary results, or the clinical meaning of a particular change in Lp(a). Statistical significance and a confidence interval that excludes zero do not by themselves establish clinical importance.

Safety counts are descriptive and should be considered separately from the biomarker efficacy analysis. They record serious adverse events and deaths by treatment and follow-up period, but do not alone establish causation or provide a complete comparative safety assessment. The registry record does not report all details needed to assess the context of each event or the analysis of exposure over time.

A balanced reading is therefore narrow: the posted primary analysis supports a model-based difference in the Week 36 Lp(a) endpoint between each olpasiran group and placebo, with the reported direction and precision. It should not be expanded into a claim about cardiovascular outcomes or an overall treatment benefit, neither of which is established by this biomarker result alone.

18. Why This Trial Matters Statistically

This trial is statistically informative because it reports a continuous biomarker outcome across several randomized regimens and a placebo group, with model-based estimates at a specified follow-up visit. The repeated measures model incorporates scheduled visit and a treatment-by-visit interaction, so the analysis is designed to represent change over time rather than treating the Week 36 contrast as an unadjusted comparison of two raw averages.

The registry also provides enough information to distinguish group estimates from treatment differences. A group least squares mean describes estimated change within that group; a treatment difference compares that estimate with placebo. Standard errors accompany the group estimates, while the sponsor reports 95% confidence intervals for the between-group results. Keeping these quantities distinct helps prevent standard errors from being mistaken for participant-level variability or confidence intervals.

The record further illustrates why model-based results and simple recalculations from summary data are not identical kinds of evidence. Recalculations can be useful for checking the broad numerical pattern, but they do not reproduce the sponsor’s repeated measures model. The registry does not flag a discrepancy, and the model-based results remain the relevant reported analysis.

At the same time, statistical interpretation depends on more than the size of a p-value. The endpoint is a biomarker, the registry does not report the multiplicity strategy, and important details about missing-data handling and the original design assumptions are absent. Those limitations frame what can reasonably be inferred from the numerical results and why a statistically precise biomarker comparison does not answer every clinical question.

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 record leaves several design and analysis details unspecified. It does not report the original sample-size justification or the trial’s own planning assumptions, so the enrollment cannot be evaluated against a stated target effect or precision goal. The planning illustrations based on observed effects are not a substitute for those original design details.

The primary analysis description identifies the model terms but does not identify the stratification factors or provide details about model diagnostics, covariance structure, or estimation procedures. It defines the FAS and says data must be available at each time point, but does not describe the missing-data method, reasons for missingness, or sensitivity analyses. Those omissions restrict independent assessment of robustness.

The record does not report whether multiplicity was controlled across treatment comparisons, time points, or secondary outcomes. It also does not report an analysis hierarchy or interim analyses. The secondary outcome list is broader than the results detail available for interpretation; numerical results for several named outcomes are not reported in the registry record.

The primary endpoint is Lp(a) percentage change at Week 36, which is a biomarker outcome rather than a clinical event. Consequently, the primary results do not answer whether cardiovascular events differed. The registry’s safety counts are descriptive; they do not by themselves indicate causality or account for duration of exposure. Event-level detail and further comparative safety analyses are not reported in the registry record.

Finally, the recalculations rely on summary statistics and simplifying assumptions rather than the sponsor’s repeated measures model. They are not a replacement for the sponsor analysis. These limitations do not negate the posted estimates, but they define the scope and strength of conclusions that can be drawn from the registry record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Olpasiran Trials of Cardiovascular Events And LipoproteiN(a) Reduction - DOSE Finding Study — NCT04270760.
• Registry record last updated 2026-03-31; status last verified 2026-03.
• Results first posted 2023-08-23.
• 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 NCT04270760 as a completed, randomized, double-blind, parallel-group phase 2 study of subcutaneous olpasiran compared with placebo in participants with elevated Lp(a). Enrollment was 281. Four olpasiran regimens and a placebo regimen are listed.

The primary endpoint was percentage change from baseline in Lp(a) at Week 36, analyzed using a repeated measures linear effects model in the FAS. The sponsor reported negative treatment differences for all four olpasiran comparisons, with 95% confidence intervals below zero and p-values of < 0.001. The outcome is a biomarker and does not directly establish an effect on cardiovascular events.

The registry lists further Lp(a), LDL-C, ApoB, and serum concentration outcomes. Numerical results for several listed secondary outcomes, multiplicity procedures, detailed missing-data methods, and the original sample-size justification are not reported in the registry record. Serious adverse event and death counts are posted for the treatment and extended safety follow-up periods and should be interpreted descriptively.