Secukinumab Dosage Optimisation in Partial Responders With Moderate to Severe Plaque-type Psoriasis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Secukinumab Dosage Optimisation in Partial Responders With Moderate to Severe Plaque-type Psoriasis (NCT02474069), a randomized phase 3 study. The primary outcome is Number of Participants With PASI 90 Response at Week 32.

2. Clinical Question

The trial therefore addresses a specific treatment-stage question, not a comparison of secukinumab with placebo or with another drug. Participants had already received standard dosing for 16 weeks, and the comparison concerns what happened after the study assigned them to one of the two dosing schedules. The primary endpoint was a PASI 90 response, defined as at least 90% improvement from baseline. The registry’s stated purpose was to explore whether shortening the dosage interval could help participants in this partial-response group achieve that endpoint by week 32.

The posted arm counts show 105 participants with a response among 163 assigned to every-2-week dosing, and 93 among 162 assigned to every-4-week dosing. These counts describe the posted results; they do not, by themselves, establish how confidently the underlying treatment-group response probabilities differ. The uncertainty around the comparison and the sponsor’s separately reported analysis are.

3. Trial Design

This was a phase 3, randomized, double-blind, parallel-group study sponsored by Novartis Pharmaceuticals. The registry describes it as multicenter. The study is marked completed. Its recorded start date is 2015-02-08, and its primary completion date is 2016-09-15. The registry records enrollment of 772 participants, while the primary comparative dosing results are reported for the two smaller arm populations shown in the results display.

The treatment question arose after a selection phase in which participants received standard secukinumab dosing. Those who had less than almost clear skin after 16 weeks were considered for the comparative dosing phase. In that phase, the registry reports a randomized comparison of secukinumab 300 mg subcutaneously every 2 weeks against continued 300 mg subcutaneously every 4 weeks. The listed comparative groups included 163 participants in the every-2-week arm and 162 in the every-4-week arm.

Randomization and double masking are recorded, but further operational details are not reported in the registry record. The specific randomization method, allocation concealment procedures, masking procedures, and whether any features differed between study sites are not reported in the registry record. The registry also does not report the original sample-size justification or the design assumptions used to determine enrollment. Those details should not be inferred from the later planning illustration, which uses the observed effect and is not the trial’s original design calculation.

The primary outcome was the number of participants with a PASI 90 response at week 32. The primary population is described as the Full Analysis Set for the Comparative Dosing Phase. The description says this set consisted of participants randomized and treated in that phase who had at least one post-randomization assessment. The registry text concerning how missing week 32 PASI assessments were handled ends mid-sentence after describing nonresponse imputation, so the complete rule is not available in the 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: and randomized 1:1 to: a.standard treatment: 300 mg s.c. secukinumab treatment every 4 weeks (weeks 16, 20, 24, \& 28) and, to maintain the blind, placebo every 4 weeks b. OR dosage interval shortening: 300 mg s.c. secukinumab treatment every 2 weeks Those who achieved at least clear or almost clear skin (≥ PASI 90) at week 16 discontinued study

Selection Phase (SP)

Reasons for not completing this period:

Comparative Dosing Phase (CDP)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set (FAS) - Comparative Dosing Phase (CDP): consisted of all patients who were randomized and received at least one dose of study drug during the CDP and had at least one post-randomization assessment. Patients with missing PASI at week 32 were counted as non-responders, unless they were responders already at their last reported PASI.

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 Number of Participants With PASI 90 Response at Week 32, measured over at 32 weeks.

The primary endpoint counts participants achieving PASI 90 at week 32. PASI 90 means at least 90% improvement from baseline in the Psoriasis Area and Severity Index. PASI combines assessments of lesion severity and the affected skin area into one score. The body is divided into four regions, and each region is assessed for the proportion of skin involved and for clinical signs including erythema, induration, and desquamation. The final score ranges from 0, indicating no disease, to 72, indicating maximal disease, as described in the registry.

A response threshold is useful because it turns a continuous severity measure into an interpretable count: the number of participants who crossed the specified improvement threshold. The endpoint is particularly aligned with this trial’s stated question about achieving substantial improvement by week 32 after a partial response to standard dosing. However, the count does not show how far above or below the threshold each participant was, nor does it describe the full distribution of PASI scores. The registry also lists PASI 50, PASI 75, PASI 100, total PASI score, IGA, and quality-of-life measures as secondary outcomes, but these do not replace the specified primary endpoint.

7. Results Posted in the Registry

• CDP - Secukinumab 300 mg s.c. (2-weekly): 64.4% (105/163) versus 57.4% (93/162) on control; risk difference 7.0 percentage points (95% CI -3.6 to 17.6), risk ratio 1.12 (0.94–1.34); unadjusted two-proportion z-test p = 0.195.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary: each participant either met the PASI 90 response definition at week 32 or did not. The registry reports counts by arm, and the recalculation compares the two proportions without adjustment. Such a comparison is an accessible summary of the observed group difference, but it does not account for covariates or other features of the sponsor’s model. It should be distinguished from the sponsor’s ANCOVA result, which is expressed as an odds ratio.

What does a risk difference describe?

A risk difference subtracts the response proportion in one group from the response proportion in the other, according to the comparison’s stated direction. It is expressed on the probability scale, so a value of zero represents equal proportions. Here, the recalculated estimate favors a higher observed response proportion in the every-2-week group, while the confidence interval extends from a negative value to a positive value. Because that interval includes zero, the data are compatible with no difference as well as with differences in either direction. This uncertainty is also reflected in the unadjusted p-value of 0.195.

The phrase “unadjusted” means that this calculation uses the posted arm counts rather than adjusting for baseline or other variables. It is a simple recalculation from the summary results, not a replacement for the sponsor’s analysis. It can help readers see the direct contrast in observed proportions, but it may not match an analysis that uses a model, a different analysis population, or different handling of data.

How does an odds ratio differ?

An odds ratio compares odds rather than probabilities. Odds are the probability of an event divided by the probability of no event. An odds ratio of 1 represents equal odds under the model and group coding used. The sponsor reports an odds ratio of 0.64 with a 95% confidence interval from 0.39 to 1.07 and p = 0.087. Because the interval includes 1, it does not exclude the null value for that measure. Odds ratios and risk differences are not on the same scale, and an odds ratio should not be read as a direct percentage-point difference.

The registry identifies the sponsor method as ANCOVA. ANCOVA generally refers to a model that compares outcomes while incorporating covariates, but the full model specification, covariates, link function, and coding are not reported in the registry record. It is therefore not possible to reproduce the sponsor estimate from the posted counts alone or to identify precisely how each modeling choice influenced it.

What does a confidence interval communicate?

A confidence interval gives a range of estimates compatible with the data and the method used, under the assumptions of that method. It communicates precision as well as direction. A narrower interval indicates greater precision on the scale being estimated; a wider interval leaves more possible values consistent with the observations. The interval is not a guarantee that the true effect lies within its endpoints, and it does not assign a probability to a particular effect after the study is complete. In this comparison, the unadjusted interval crosses zero for the risk difference, while the sponsor interval crosses 1 for the odds ratio. Both intervals therefore include their respective null values.

Why can the two analyses differ?

The direct recalculation and the sponsor analysis use different effect measures, and the sponsor analysis is described as ANCOVA. Adjusted and unadjusted analyses can yield different estimates or uncertainty because they use different statistical formulations and may incorporate different information. The registry does not report enough detail to attribute the difference between the p-values to any specific model feature. The recalculated result should be understood as a transparent summary based on the posted arm counts; the sponsor result should be understood as the analysis reported by the trial sponsor.

Multiplicity is another general statistical consideration. When a study examines several outcomes, response thresholds, and timepoints, repeated testing can increase the chance of at least one apparently unusual result if no adjustment or testing hierarchy is used. The registry lists multiple secondary outcomes, but a multiplicity procedure or prespecified hierarchy is not reported in the registry record. The primary endpoint can be described on its own, but the record does not establish how the broader family of results was handled statistically.

Why does over-dispersion matter?

Over-dispersion is a general issue for some models of count data, when observed variability exceeds what a model assumes. The primary endpoint is a participant count arising from a binary response, and the registry’s reported sponsor method is ANCOVA; it does not identify a count model for the primary comparison. Over-dispersion is therefore not a stated issue for this posted analysis. In general, if an analysis does use a count model and ignores over-dispersion, standard errors may be too small and confidence intervals too narrow. That general point should not be mistaken for evidence that over-dispersion occurred in this trial.

Finally, the analysis population and missing outcomes affect interpretation. The Full Analysis Set description requires randomization, at least one dose in the comparative phase, and at least one post-randomization assessment. The registry says missing week 32 PASI values were counted as nonresponders, but its description of any exception is incomplete. These details are part of the estimand being summarized: the analysis is not simply a count among every participant originally enrolled, and the posted record does not fully resolve the treatment of all missing assessments.

10. Confidence Intervals and Precision

Precision is best judged from the confidence intervals, not from the point estimates alone. The unadjusted risk-difference interval extends from below zero to above zero. Zero represents no difference in response proportions. Thus, the interval allows for a range that includes both a possible advantage for the every-2-week schedule and a possible advantage for the every-4-week schedule, as well as no difference. Its breadth indicates that the posted data do not pin down the size or direction of the difference precisely.

The sponsor’s 95% confidence interval for the odds ratio runs from 0.39 to 1.07. The null value for an odds ratio is 1, and this interval includes that value. The sponsor estimate is therefore also uncertain with respect to whether the groups differ on the modeled odds scale. The interval is not directly comparable in width to the risk-difference interval because the measures use different scales and come from different analyses.

A confidence interval is not a range of outcomes for individual participants. It describes uncertainty in an estimated group-level effect under the analysis assumptions. Nor does an interval containing a null value demonstrate that the treatments are equivalent. Equivalence requires a defined margin and a design and analysis intended to assess whether effects fall within that margin; such a margin is not reported in the registry record.

The size of the comparative groups and the number of observed responses are relevant to precision, but they should not be used to overstate certainty. The posted estimates indicate a numerical difference in the observed proportions, while both analyses leave uncertainty around the comparative effect. Readers should consider the intervals together with the study population, endpoint definition, analysis method, and incomplete detail about missing-data handling.

11. 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 display is a planning illustration based on the observed effect, not a report of the study’s original design justification. Its rows show planning for 100%, 75%, and 50% of the observed effect. For each assumed effect, the columns give the participants per arm for 80% power and the participants per arm for 90% power. For example, the row planning for 75% of the observed effect lists 1,362 participants per arm for 80% power and 1,823 participants per arm for 90% power.

In plain terms, power is the chance that a study would detect an effect of the assumed size under the planning model and its assumptions. The 80% and 90% columns show two different target probabilities of detecting that assumed effect, if it were present and the planning assumptions held. A higher power target generally requires more participants. The table’s assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect.

The figures are participants per arm, not total participants and not total events. The sample-size assumptions note that time-to-event tables would instead show total events, but this is a binary-outcome illustration. Smaller effects require more participants, which is why the rows using a smaller fraction of the observed effect have larger planning numbers. These figures are not observed power.

The curve and table are useful for showing how planning needs change when the assumed effect or target power changes. They should not be treated as evidence that the trial was designed around these exact assumptions: the registry’s original sample-size justification and design assumptions are not reported in the registry record.

12. 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.574; treatment proportion p₁ = 0.644; average p̄ = 0.609.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6901 = 1.3525.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6883 = 0.5793.
4. n = (1.3525 + 0.5793)² / (0.0701)² = 759.5, rounded up to 760 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
p0 <- 0.574074074074074                          # control proportion
p1 <- 0.644171779141104                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(2474069)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 760 (80% power), 1,017 (90% power)
 75% of observed effect: n per arm = 1,362 (80% power), 1,823 (90% power)
 50% of observed effect: n per arm = 3,087 (80% power), 4,132 (90% power)
power.prop.test: 759.5 
Simulated power at n = 760 per arm: 0.798 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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.

13. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary comparison as an ANCOVA analysis with an odds ratio of 0.64, a 95% confidence interval from 0.39 to 1.07, and p = 0.087. The groups are listed as the every-4-week arm followed by the every-2-week arm. The record does not give the full model specification or enough detail to interpret the exact odds-ratio coding beyond that listing.

The recalculation uses the posted response counts to make an unadjusted comparison on the risk-difference scale. It has an unadjusted p-value of 0.195, and its interval includes no difference. These analyses need not match: one uses an odds ratio and a sponsor-reported ANCOVA model, while the other is a direct, unadjusted calculation from the counts. The registry marks the results as having no discrepancy, so there is no recorded conflict flag between them; that does not make the distinct estimates interchangeable.

The sponsor analysis is the trial’s reported model-based result, while the recalculation is a supplementary summary of the arm counts. Neither analysis excludes its own null value at the interval shown. The registry record does not report further details that would allow the sponsor result to be independently reproduced or its model assumptions fully evaluated.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists several secondary outcomes, including PASI response thresholds, PASI total scores, IGA response, and DLQI measures. Testing multiple outcomes or thresholds raises a general multiplicity concern: without an adjustment or prespecified testing hierarchy, the chance of at least one result appearing statistically notable can increase across a collection of tests. The registry record does not report whether multiplicity was controlled, how the primary endpoint related to the secondary endpoints in a testing sequence, or whether any outcomes were designated exploratory. Accordingly, the primary result should not be read as resolving all the listed secondary questions.

The analysis population is described as the Full Analysis Set for the Comparative Dosing Phase. It includes participants who were randomized, received at least one dose of study drug during that phase, and had at least one post-randomization assessment. This is the registry’s stated definition; the record does not provide a complete participant flow or enough detail to assess every exclusion from the analysis.

For missing week 32 PASI values, the registry states that participants were counted as nonresponders unless an additional condition applied. The text cuts off after “unless they we,” so the exception and the full missing-data rule are not reported in the registry record. Nonresponder imputation is a general approach that treats a missing binary response as no response. Its consequences depend on how much outcome data are missing and whether missingness differs between groups; those details are not fully. The registry record does not describe sensitivity analyses for alternative missing-data assumptions.

The original statistical analysis plan, prespecified covariate adjustments, interim analyses, multiplicity strategy, and original sample-size justification are not reported in the registry record. Their absence limits assessment of how closely the posted analyses follow the prespecified plan. It is not appropriate to infer that such procedures were or were not used from the results alone.

15. 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 0.0001% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: chest pain (0.6%), impaired healing (0.6%), erysipelas (0.6%), mastoiditis (0.6%), pyoderma (0.6%).

The registry lists serious adverse events for the comparative dosing groups as 8 among 162 participants in the every-4-week arm and 4 among 163 in the every-2-week arm. For the selection-phase group receiving every-4-week dosing, it lists 32 among 772. These figures are presented with different phase populations; the selection-phase count should not be treated as a randomized comparison with either comparative-phase arm.

The registry also lists other adverse events as 85 among 162 in the every-4-week comparative group and 87 among 163 in the every-2-week group, alongside 510 among 772 for the selection-phase group. The top serious-event terms listed are CHEST PAIN, IMPAIRED HEALING, ERYSIPELAS, MASTOIDITIS, PYODERMA, and SINUSITIS, each shown as 0.6%. The record does not attach those terms to a specific comparative arm in the displayed information.

These are descriptive counts, not a formal estimate of comparative safety. Death counts are not reported in the registry record. The figures alone do not establish whether an event was caused by treatment or whether the dosing schedules differ in safety.

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

The result addresses a focused question: among participants who had less than almost clear skin after 16 weeks of standard secukinumab dosing, how many achieved PASI 90 by week 32 under every-2-week dosing compared with continued every-4-week dosing? The posted counts are 105 of 163 and 93 of 162, respectively. The recalculated comparison points toward a higher observed response proportion with the shortened interval, but the confidence interval includes no difference. The sponsor’s odds-ratio confidence interval also includes its null value.

This means the posted analyses do not provide a precise, conclusive estimate of a difference for the primary endpoint. It does not mean the schedules are equivalent, and it does not show that a clinically meaningful difference is impossible. A result that does not exclude the null can reflect uncertainty in the estimate; a properly designed equivalence or noninferiority conclusion would require a specified margin and corresponding methods, which are not reported in the registry record.

The findings are specific to the study population, treatment stage, dosing schedules, endpoint, and week 32 assessment. They do not directly answer questions about initial treatment, people with a different response after standard dosing, other doses, other treatments, or outcomes beyond those recorded. PASI 90 captures a threshold response and does not describe every participant’s score trajectory or all dimensions of psoriasis-related health.

The record lists additional efficacy and quality-of-life outcomes, but their presence does not change the interpretation of the primary comparison. Likewise, adverse-event counts provide descriptive safety information but do not alone establish comparative risks or causation. Overall, the result should be read as a randomized comparison with a numerical difference in the observed response counts and substantial uncertainty around the treatment contrast, rather than as a definitive answer about efficacy or safety.

17. Why This Trial Matters Statistically

This trial is statistically informative because it focuses on a treatment decision point rather than on treatment initiation. Participants first received standard dosing, and the comparative question concerned those who had not reached almost clear skin after 16 weeks. That design makes the target population explicit: the results are about partial responders entering a later dosing phase, not all participants with plaque-type psoriasis.

The endpoint also illustrates the difference between a clinically interpretable threshold and a continuous measure. PASI 90 translates improvement into a count of responders, which is straightforward to communicate. At the same time, dichotomizing a score discards information about the degree of improvement on either side of the threshold. The registry’s other measures, including PASI total scores, additional PASI thresholds, IGA, and DLQI, reflect different aspects of response and should be considered separately.

The comparison is a useful example of why point estimates, confidence intervals, and analysis methods belong together. The observed counts favor the every-2-week group numerically, while the recalculated interval includes no difference and the sponsor’s odds-ratio interval includes 1. Reporting the counts without uncertainty could overstate what the data resolve; focusing only on a p-value would also obscure the range of compatible effects.

Finally, the page demonstrates the distinction between trial results and planning illustrations. Sample-size figures based on the observed effect can show how study size changes with assumed effect and power, but they do not reveal the trial’s original design rationale. The registry’s missing details about that rationale, the complete missing-data rule, and multiplicity procedures are important limits on how fully the statistical plan can be assessed.

18. 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 trial-specific details unresolved. The primary analysis population is described, but the full participant flow and the complete handling of missing week 32 assessments are not available. The nonresponder rule is followed by a truncated exception, so the exact rule cannot be reconstructed. The registry does not report sensitivity analyses showing whether conclusions change under alternative assumptions about missing outcomes.

The sponsor’s ANCOVA result is reported without its full model specification. The covariates, link function, parameter coding, and other modeling details are not reported in the registry record. This prevents independent reproduction from the posted arm counts and limits direct comparison with the unadjusted risk-difference recalculation. The reported groups are ordered in the record, but the exact odds-ratio contrast coding is not explained in the posted excerpt.

The record lists multiple secondary outcomes but does not report a multiplicity strategy or testing hierarchy. It also does not report the original sample-size justification, design assumptions, or interim-analysis plan. These omissions limit assessment of the prespecified statistical framework; they do not establish that a particular procedure was absent.

The posted safety figures are descriptive and include groups from different study phases. The serious-event terms shown are not assigned to a specific comparative arm in the displayed record, and deaths are not reported in the registry record. The available figures therefore do not support a complete comparative safety analysis. Finally, the results concern the defined partial-responder population and week 32 PASI 90 endpoint; they should not be generalized automatically to other populations, timepoints, or outcomes.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Secukinumab Dosage Optimisation in Partial Responders With Moderate to Severe Plaque-type Psoriasis — NCT02474069.
• Registry record last updated 2019-07-05; status last verified 2019-04.
• Results first posted 2019-07-05.
• 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.

22. Record Summary

This completed phase 3 randomized, double-blind, parallel-group study compared secukinumab 300 mg subcutaneously every 2 weeks with continued every-4-week dosing in participants with moderate to severe plaque-type psoriasis who had less than almost clear skin after 16 weeks of standard treatment. The primary endpoint was the number achieving PASI 90 at week 32.

The posted counts were 105 of 163 in the every-2-week arm and 93 of 162 in the every-4-week arm. The unadjusted recalculation and the sponsor’s ANCOVA analysis both retain uncertainty around the comparative effect. The registry lists additional efficacy, quality-of-life, and safety outcomes, while several elements of the original design and statistical plan are not reported in the registry record.