A Study of Navenibart (STAR-0215) in Participants With Hereditary Angioedema: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of Navenibart (STAR-0215) in Participants With Hereditary Angioedema (NCT05695248), a non-randomized phase 1, phase 2 study. The primary outcome is Number of Participants Experiencing Treatment-emergent Adverse Events.

2. Clinical Question

3. Trial Design

ALPHA-STAR is described as a Phase 1b/2 single- and multiple-dose study of navenibart in participants with hereditary angioedema. It was non-randomized, unmasked and sequential. Enrollment was 29, and the registry status is completed. The study description says that one group received one dose and two other groups received two doses. The stated purpose was to study the drug in participants with HAE when it was first given to this population.

The three cohorts had distinct regimens. Cohort 1 received one 450 milligram dose. Cohort 2 received 600 mg followed by 300 mg, with the doses 3 months apart. Cohort 3 received two 600 mg doses 1 month apart. This sequence of differing regimens is important when interpreting cohort results: the groups were not randomly assigned to comparable treatment conditions, and there was no randomized control arm. Differences between cohorts could not be attributed to dosing alone using the information in the registry record.

The primary outcome concerns treatment-emergent adverse events, with follow-up extending from Day 1 through Day 448 for Cohort 1, Day 531 for Cohort 2 and Day 475 for Cohort 3. The registry record describes secondary measures including monthly HAE attack rate change, attack-free participants and days, attack severity and duration, attacks requiring on-demand therapy, time to first attack, and maximum drug concentration. Numerical results for those secondary outcomes are not reported in the registry record. Detailed eligibility criteria, cohort-entry procedures and a statistical analysis plan 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.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Safety Analysis Set: all participants who received any amount of navenibart.

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: Safety Analysis Set: all participants who received any amount of navenibart.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Experiencing Treatment-emergent Adverse Events, measured over Day 1 through Day 448 (Cohort 1), Day 531 (Cohort 2), Day 475 (Cohort 3).

The primary endpoint is the number of participants experiencing treatment-emergent adverse events. The registry defines an adverse event as an untoward medical occurrence in a participant who received a pharmaceutical product; a causal relationship to treatment is not required. An event is treatment-emergent if it begins at or after treatment starts, or if a pre-existing medical condition increases in severity or relationship to treatment at or after that point.

This kind of endpoint is used to describe the occurrence of safety events during treatment and follow-up. Counting participants focuses on whether an event affected a participant, rather than on the total number of event episodes. The endpoint is therefore a safety summary, not a direct measure of treatment benefit or of whether navenibart caused an event. The registry identifies the Safety Analysis Set as all participants who received any amount of navenibart.

Follow-up windows differ by cohort: Day 1 through Day 448 for Cohort 1, Day 531 for Cohort 2 and Day 475 for Cohort 3. The registry record also points to serious and other, nonserious, adverse events regardless of causality. The endpoint description does not itself establish that an event was caused by treatment. Detailed primary-endpoint analysis results are not reported in the registry record details.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry record identifies the study as non-randomized, unmasked and sequential. It does not report a detailed statistical analysis plan, so the methods below distinguish what the record states from general statistical principles. No analysis-level results are reported in the registry record.

What does a participant count describe?

The primary outcome is a count of participants with treatment-emergent adverse events. A participant count answers how many people in a cohort had at least one event meeting the stated definition. It is different from a count of event episodes: one participant could experience more than one event, but a participant-based endpoint counts that person as affected. The registry record describes the primary measure in participant-count terms. It does not provide an event-level statistical model in the registry record.

For the safety figures, the reported count is paired with the number at risk in each cohort. Those figures can be read as cohort-specific descriptive counts. They should not be confused with a causal effect, a risk difference or an adjusted event rate. No additional comparisons or derived quantities are calculated in this interpretation.

Why does non-randomized allocation matter?

Randomization is a design method that aims to make treatment groups comparable, on average, with respect to measured and unmeasured factors. This study was non-randomized, and the cohorts followed different dosing schedules. In general, without random allocation, a difference between cohorts may reflect differences in who entered each cohort, the sequence of enrollment, follow-up or other factors as well as the regimen. The registry record does not report a control group or a statistical adjustment that would resolve those concerns. Cohort-by-cohort observations are therefore best treated as descriptive, not as a randomized comparative estimate.

Unmasked means that the study was not blinded according to the registry record. In general, knowledge of treatment assignment can influence reporting, assessment or care, depending on the outcome and study procedures. The record does not describe how outcomes were assessed or whether any safeguards were used. It would be inappropriate to assume either that such influence occurred or that it was prevented.

How should follow-up be considered?

The listed safety observation periods differ by cohort: Day 1 through Day 448, Day 531 and Day 475, respectively. A raw count does not account for how long participants were observed. In general, event rates that incorporate time at risk can be useful when exposure or follow-up varies, but no such rates are reported in the registry record. Differences in follow-up also mean that the cohort counts are not directly comparable as if each group had been observed for the same duration.

For clinical outcomes, time-to-event methods can use the timing of an event and account for incomplete follow-up under specified assumptions. The registry lists time to first HAE attack as a secondary outcome, but the registry entries do not report its estimate, analysis method or censoring rules. Those details are not reported in the registry record.

What do the planning illustrations mean?

The planning illustrations use the observed effect as a basis, with the effect to detect defined as a stated fraction of that observed effect. Their stated assumptions are a two-sided significance level of 0.05, equal allocation between two arms and a normal approximation. These are planning illustrations, not observed power and not evidence that the trial was designed with those assumptions. The registry record does not report that these assumptions were the study's own design choices or that a sample-size justification used them.

In general, power is the probability that a specified analysis will detect an effect of a chosen size under its assumptions. A planning calculation is conditional on the assumed effect, allocation, test and model; it does not show the probability that an observed result is true. The record's illustrations are not a substitute for the trial's own design rationale, which is not reported in the registry record. The assumptions state that time-to-event illustrations use the total number of events, while other illustrations use participants per arm.

Why can a confidence interval be informative?

In general, a confidence interval communicates uncertainty around an estimated quantity. A narrow interval indicates greater precision under the model used, while a wide interval indicates less precision. It does not by itself remove bias from a non-randomized comparison, and interpretation depends on the target estimate and method. No confidence intervals or inferential results for the outcomes are reported in the registry record.

Over-dispersion is a general statistical issue that arises when the observed variability exceeds what a model assumes. For count outcomes, ignoring extra variability can make standard errors too small and intervals too narrow. The registry entries do not report a count model, an over-dispersion assessment or an adjustment for it. There is therefore no basis for describing such a method as having been used in this trial.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Cohort 1: Single Dose Navenibart", "Cohort 2: Multiple Dose Navenibart", "Cohort 3: Multiple Dose Navenibart")
n      <- c(4, 13, 12)
events <- c(4, 9, 12)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Cohort 1: Single Dose Navenibart  4  4  100.0  39.8  100.0  51.0  100.0  47.8  99.5
ARM  Cohort 2: Multiple Dose Navenibart  13  9  69.2  38.6  90.9  42.4  87.3  41.9  87.2
ARM  Cohort 3: Multiple Dose Navenibart  12  12  100.0  73.5  100.0  75.8  100.0  75.3  99.8

11. Multiplicity, Missing Data and Analysis Populations

The registry lists multiple secondary outcomes, including HAE attack rate change, attack-free status, attack severity and duration, on-demand therapy use, time to first attack, attack-free days and maximum drug concentration. Multiple outcomes create a general multiplicity issue: when many hypotheses are tested, the chance of at least one apparently notable result can increase if each is assessed separately. The registry record details do not report a multiplicity adjustment, a hierarchy of outcomes or a prespecified testing sequence. It is not possible to infer whether any such strategy was used.

Missing-data methods are also not reported in the registry record. The registry entries do not describe whether participants discontinued, how incomplete outcome observations were handled, whether analyses used imputation, or how missing follow-up was reflected in the estimates. These omissions matter because different handling choices can affect an estimate and its uncertainty. No particular method should be assumed.

The primary endpoint identifies a Safety Analysis Set consisting of participants who received any amount of navenibart. The registry entries do not describe an intention-to-treat population, a per-protocol population or outcome-specific analysis populations for the secondary measures. Nor do they provide the analysis methods, covariate adjustments or confidence intervals for those outcomes. Thus, the stated safety population can be described, but it cannot be extended by assumption to all analyses.

The registry reports 0 analyses in the registry record. This is not a statement that no data were collected; it indicates that analysis-level results are not available in the registry record. Without reported methods for multiplicity and missing data, and without outcome estimates, the secondary outcome list should be understood as a list of planned or registered measures rather than as evidence of particular results.

12. 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 0% reporting threshold.

Most frequent non-serious adverse event terms

The serious adverse event figures report zero affected participants in each cohort: 0 of 4 at risk in Cohort 1, 0 of 13 at risk in Cohort 2, and 0 of 12 at risk in Cohort 3. The reported death count is also zero in each cohort. These are registry-recorded counts for the specified study groups and follow-up; they do not show that the possibility of serious events is absent, particularly beyond the observation available in the study.

Other adverse events were reported for 4 of 4 participants at risk in Cohort 1, 9 of 13 in Cohort 2, and 12 of 12 in Cohort 3. These are counts of affected participants, not a count of every event episode. The registry definition states that an adverse event does not necessarily have a causal relationship with treatment. The registry entries do not identify the most common serious event terms, and the registry record points readers to its reported adverse events for detailed event summaries.

Follow-up differs across cohorts, and the study has no randomized control group. The counts should not be used to claim that navenibart caused or prevented an event, or to rank the cohorts by safety. They describe recorded events within this study.

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

The registry record establishes that ALPHA-STAR was a completed, non-randomized, sequential Phase 1b/2 study of navenibart in participants with hereditary angioedema. It reports three dosing cohorts, a primary safety endpoint based on participants experiencing treatment-emergent adverse events, and cohort-specific safety counts. The record's serious adverse event counts and death counts are zero across the cohorts, while other adverse events are reported for participants in each cohort.

These observations do not establish that navenibart caused any particular adverse event. The adverse-event definition explicitly does not require a causal relationship to treatment. Nor do the counts establish a comparative safety effect: there was no randomized control group, dosing schedules differed, and follow-up periods were not identical. The cohort counts describe the study record rather than a controlled comparison.

The outcome list indicates that the trial registered measures of HAE attacks and pharmacokinetics, among other outcomes. But the numerical results for those measures are not reported in the registry record. It is therefore not possible to describe the size, direction or precision of a clinical-activity estimate from this information. The absence of an estimate in the registry record should not be interpreted as a finding of no effect or as evidence that no outcome data were collected.

More broadly, a completed early-phase study can contribute descriptive information about a regimen and the kinds of outcomes assessed, but conclusions depend on the reported estimates, their uncertainty, the study design and the analysis methods. The registry entries do not report a detailed statistical plan, missing-data methods or multiplicity strategy. The most defensible reading is limited to the recorded design and safety counts; causal, comparative and efficacy conclusions are not supported by those details alone.

14. Why This Trial Matters Statistically

This trial is statistically notable for the way its design limits comparisons. It used a sequential, non-randomized structure and assigned different dosing schedules across three cohorts. That design can provide cohort-specific observations, but it does not create the balance that random allocation is intended to achieve. A numerical difference between cohorts, even if one were reported, would not by itself isolate the effect of dose or dosing interval.

The endpoint also illustrates the difference between a safety count and an efficacy estimate. Counting participants with treatment-emergent adverse events is a way to describe safety experience; it does not by itself estimate a treatment effect against a control condition. The registry's secondary outcome list includes HAE attack measures, but their numerical results are not reported in the registry record. Readers therefore need to distinguish registered outcomes from reported estimates.

Follow-up varies by cohort, another reason to be careful with direct comparisons. Raw participant counts do not adjust for duration of observation. In general, unequal observation time can complicate interpretation of event counts; the registry entries do not report time-adjusted analyses. Finally, the record's planning assumptions are explicitly illustrations based on an observed effect, rather than an account of the trial's design rationale. They should not be mistaken for observed power or as proof that a particular analysis was prespecified.

Taken together, these features make transparent reporting of outcome estimates, uncertainty, analysis populations and missing-data handling especially important. Those details are not reported in the registry entries. Statistical interpretation must therefore remain descriptive and bounded by the information actually recorded.

15. 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 principal trial-specific limitation is the non-randomized design. The three cohorts used different dose schedules, with no randomized comparator reported. Any between-cohort contrast would be vulnerable to differences in participant composition, enrollment sequence or other factors that the registry entries do not describe. The study cannot be treated as a like-for-like controlled comparison.

Observation periods also differ: the primary endpoint follow-up runs through Day 448 for Cohort 1, Day 531 for Cohort 2 and Day 475 for Cohort 3. The raw safety counts do not account for these differences in duration. No time-adjusted event rates or methods to account for follow-up are reported in the registry entries.

The registry entries do not include efficacy estimates, confidence intervals, hypothesis tests or detailed analyses of the registered HAE attack outcomes. They also do not report a statistical analysis plan, missing-data procedures, multiplicity handling, cohort-entry rules or outcome-specific analysis populations beyond the stated Safety Analysis Set. These gaps restrict assessment of the precision and robustness of any result.

Finally, the safety counts are descriptive, and the adverse-event definition does not require causation. Zero recorded serious events in the cohorts does not establish absence of risk, and reported nonserious events cannot be attributed to navenibart from these counts alone. The limitations concern what can be concluded from the registry information; they do not imply that unreported methods or results were absent from other study materials.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: A Study of Navenibart (STAR-0215) in Participants With Hereditary Angioedema — NCT05695248.
• Registry record last updated 2026-05-08; status last verified 2026-04.
• Results first posted 2026-05-08.
• 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.

19. Record Summary

The registry record describes ALPHA-STAR, a completed Phase 1b/2, non-randomized, unmasked, sequential study of navenibart in participants with hereditary angioedema. It reports three cohorts with single- or multiple-dose schedules and lists treatment-emergent adverse events as the primary outcome. The safety population consists of participants who received any amount of navenibart.

Serious adverse event counts and death counts are zero in each cohort. Other adverse events were reported for 4 of 4 participants in Cohort 1, 9 of 13 in Cohort 2 and 12 of 12 in Cohort 3. These descriptive counts do not establish causation or support randomized comparisons.

The registry lists secondary HAE attack and pharmacokinetic outcomes, but numerical results for them, detailed statistical methods, missing-data handling and multiplicity procedures are not reported in the registry record details. Interpretation is therefore limited to the recorded design and safety information.