A Phase 2 Study For Patients With A Physician's Diagnosis Of Rheumatoid Arthritis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Phase 2 Study For Patients With A Physician's Diagnosis Of Rheumatoid Arthritis (NCT00550446), a randomized phase 2 study. The primary outcome is Percentage of Participants Achieving American College of Rheumatology 20% (ACR20) Response at Week 12.

2. Clinical Question

The registry reports 386 participants enrolled in a randomized, parallel-group study with quadruple masking. Its stated purpose was to assess effectiveness and safety of five CP-690,550 doses over 6 months. The primary response assessment came earlier, at Week 12, so it represents a point during the treatment period rather than the full treatment duration.

The central statistical question is about the proportion meeting a composite response definition in each group. A higher observed percentage indicates more participants met that definition in the analyzed population; it does not by itself establish the size or certainty of a treatment effect. Comparisons with placebo are accompanied by recalculated unadjusted estimates and uncertainty intervals, and those should be interpreted in light of the small group sizes and the number of dose comparisons.

3. Trial Design

This was a phase 2, randomized, double-blind, placebo-controlled active-comparator study with a parallel-group model and quadruple masking. The registry identifies Pfizer as sponsor and lists 386 participants enrolled. The study is marked completed. Its start is recorded as 2007-09 and its primary completion as 2009-01.

The official title describes a multicenter study comparing five CP-690,550 dose regimens and adalimumab with placebo, administered for 6 months in people with active rheumatoid arthritis. The registry’s brief summary describes the allocation plan as five out of seven subjects receiving CP-690,550, with one out of seven receiving adalimumab and one out of seven receiving placebo. The reported primary endpoint, however, is the percentage achieving ACR20 at Week 12.

There are seven treatment groups in the outcome results: CP-690,550 1 mg, 3 mg, 5 mg, 10 mg, and 15 mg; adalimumab; and placebo. The placebo group is the reference for the posted recalculated comparisons. Each treatment group has a reported Week 12 ACR20 percentage, with the highest listed percentages in the 10 mg and 15 mg groups. Group sizes differ, and the arm descriptions are blank in the registry record.

The registry lists several secondary measures, including ACR50, ACR70, and ACR90 response, an ACR-n response-curve measure, tender joint count, and swollen joint count. It records 39 outcome measures and 30 posted secondary outcomes. The original sample-size rationale, detailed allocation procedures, and the trial’s own full 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.

Only the first 6 of 11 groups are shown.

Up To Week 12

Reasons for not completing this period:

Post Week 12

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set (FAS) included all randomized participants who received at least 1 dose of study medication and had at least 1 post-baseline measure. The analysis used Baseline Observation Carried Forward (BOCF) imputation for missing values.

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.

Only the first 6 of 8 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants Achieving American College of Rheumatology 20% (ACR20) Response at Week 12, measured over Week 12.

The primary endpoint is the percentage of participants achieving an ACR20 response at Week 12. ACR20 is a composite response definition, rather than a measurement of only one symptom or joint count. To qualify, a participant had to achieve at least 20% improvement in tender joint count and at least 20% improvement in swollen joint count, along with at least 20% improvement in at least three of five additional core measures: participant assessment of pain, participant global assessment of disease activity, physician global assessment of disease activity, self-assessed disability using the HAQ disability index, and C-reactive protein.

Composite response measures are used to represent improvement across several aspects of disease status. Requiring improvement in joint counts and other measures makes the endpoint broader than a single measure, but it also means the result depends on the full set of criteria being met. The percentage is therefore a group-level summary of how many participants met the response definition; it does not describe the degree of improvement among those who did not meet it.

For this endpoint, the registry defines the Full Analysis Set as randomized participants who received at least one dose and had at least one post-baseline measure. Missing values were imputed using Baseline Observation Carried Forward. That approach assigns the baseline observation to a missing follow-up value, rather than using a later observed value. The original rationale for selecting this imputation method is not reported in the registry record.

7. Results Posted in the Registry

• CP-690,550 1 mg: 31.5% (17/54) versus 23.7% (14/59) on control; risk difference 7.8 percentage points (95% CI -8.7 to 24.2), risk ratio 1.33 (0.73–2.43); unadjusted two-proportion z-test p = 0.356.
• CP-690,550 3 mg: 45.1% (23/51) versus 23.7% (14/59) on control; risk difference 21.4 percentage points (95% CI 3.9 to 38.8), risk ratio 1.90 (1.10–3.29); unadjusted two-proportion z-test p = 0.018.
• CP-690,550 5 mg: 61.2% (30/49) versus 23.7% (14/59) on control; risk difference 37.5 percentage points (95% CI 20.1 to 54.9), risk ratio 2.58 (1.55–4.29); unadjusted two-proportion z-test p = <0.001.
• CP-690,550 10 mg: 72.1% (44/61) versus 23.7% (14/59) on control; risk difference 48.4 percentage points (95% CI 32.8 to 64.0), risk ratio 3.04 (1.87–4.93); unadjusted two-proportion z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

What does the response percentage represent?

The outcome is binary at the participant level: each participant either meets the ACR20 response definition at Week 12 or does not. A group percentage summarizes the frequency of that event. For a binary outcome, the natural comparison is a difference in proportions, often called a risk difference. It expresses how far apart the response proportions are on the absolute scale. The posted recalculations compare each active group with placebo.

The reported response percentages are descriptive arm-level results. They are not adjusted for other variables in the posted calculations. The registry’s primary analysis population and missing-data handling remain important to their interpretation: participants had to be randomized, receive at least one dose, and have a post-baseline measure, and missing values were handled using Baseline Observation Carried Forward.

How should a risk difference be interpreted?

A positive risk difference means the response proportion is higher in the treatment group than in the placebo group; a negative value would mean it is lower. A confidence interval gives a range of values compatible with the observed data under the calculation’s assumptions. If the interval includes zero, the data are compatible with no difference as well as with differences in either direction. If it excludes zero, the interval is inconsistent with zero at the corresponding confidence level under that method. This is not proof that an effect is real or important, and it does not resolve bias, missing-data concerns, or multiplicity.

The recalculated risk differences and intervals come from the posted arm-level summary statistics. They are simple unadjusted recalculations, rather than the sponsor’s full analysis. The registry record does not report a competing official inferential result for the primary endpoint, and the discrepancy flag is false. No adjustment variables or model-based covariate analysis are described in the record.

What does the p-value add?

A p-value measures how surprising the observed data, or data more extreme, would be under a specified null model. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of a difference. The p-values listed for comparisons with placebo are unadjusted. The values for 5 mg, 10 mg, and 15 mg are reported as <0.001; the 3 mg value is 0.018, the 1 mg value is 0.356, and the adalimumab value is 0.07.

Because several treatment groups are compared with one control, repeated testing raises a multiplicity question: across many tests, the chance of at least one apparently unusual result can increase. Whether and how the trial addressed this issue is not reported in the registry record. The recalculated p-values should therefore be treated as nominal, not as evidence that a family-wise testing procedure was satisfied.

Why does the analysis population matter?

The Full Analysis Set excludes randomized participants who did not receive a dose or did not have a post-baseline measure, according to the registry definition. Restricting the analysis in this way can make the analyzed group differ from all randomized participants. The registry record does not provide enough information to assess the effect of those exclusions. An intention-to-treat analysis ordinarily aims to retain participants in their assigned groups regardless of treatment received; the registry’s stated Full Analysis Set definition is not identical to that principle because it includes the dose and post-baseline requirements.

What are the implications of Baseline Observation Carried Forward?

Baseline Observation Carried Forward assigns a participant’s baseline observation to a missing follow-up value. In general, any single imputation method can understate uncertainty because it treats an imputed value as if it were known. Its assumptions can also affect response classification: carrying baseline forward may prevent a participant with missing follow-up from being counted as improved, but it may not represent the participant’s unobserved Week 12 state. The amount and pattern of missing data, reasons for missingness, and sensitivity analyses are not reported in the registry record.

What is over-dispersion, and does it apply?

General: over-dispersion occurs when variability in data is greater than a statistical model expects. It is a concern in some count or rate models and can make standard errors too small if ignored. The primary outcome is a binary response summarized as percentages, not a count outcome analyzed with a reported over-dispersion model. No over-dispersion assessment or model is reported for this endpoint, so it should not be inferred from these results.

What analysis details remain unknown?

The registry record does not report the trial’s original sample-size justification, a detailed statistical analysis plan, an interim-analysis plan, or a multiplicity procedure. It also does not report the original sponsor model details or sensitivity analyses for missing data. These unknowns limit how closely the unadjusted recalculations can be aligned with the intended confirmatory analysis. The record lists 39 outcome measures and 30 posted secondary outcomes, while no registry analysis entries are reported. That makes clear separation between the posted outcome summaries and formal prespecified inferential claims especially important.

10. Confidence Intervals and Precision

The comparison intervals communicate how precisely the response differences are estimated. A narrower interval would indicate greater precision, while a wider interval would leave more uncertainty about the size and direction of the difference. For the 1 mg and adalimumab comparisons, the recalculated intervals include zero. For the 3 mg, 5 mg, 10 mg, and 15 mg comparisons, they exclude zero. Exact interval limits are not repeated in this explanation; the key interpretive point is whether each interval includes the no-difference value.

Precision is limited by the group sizes, which range from 49 to 61 participants across the five CP-690,550 groups, with 53 in the adalimumab group and 59 in placebo. These are the outcome group sizes used for the reported percentages. With relatively small groups, a few participant outcomes can influence the estimated proportion, and the uncertainty interval is important context for each point estimate.

The intervals describe sampling uncertainty under the recalculation’s assumptions. They do not account for all possible sources of uncertainty, including missing-data assumptions, exclusions from the Full Analysis Set, departures from the model assumptions, or multiple comparisons. Nor do they tell whether a difference is clinically meaningful. The registry record does not give a minimum clinically important difference for ACR20 or a prespecified threshold for interpreting the interval.

The recalculated intervals are unadjusted. Their coverage interpretation applies to each individual comparison, not necessarily to the set of all dose-versus-placebo comparisons considered together. The registry record does not report whether multiplicity-adjusted intervals were calculated in the sponsor’s analysis. Consequently, the precision statements should be read as comparison-specific rather than as a simultaneous guarantee across all treatment groups.

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 figures are planning illustrations based on the observed effect, not the original trial design calculation. The displayed counts are participants per arm for 80% power and participants per arm for 90% power. They are not total sample sizes across both arms. The 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.

For each comparison, the full observed effect is used as one planning scenario. Other scenarios use 75% and 50% of that observed effect, representing progressively smaller effects to detect. The figures generally increase as the assumed effect gets smaller: a more modest difference is harder to distinguish from random variation, so planning for it requires more participants per arm. The two power columns answer different planning questions: the 80% column gives the per-arm count under an 80% target probability of detecting the assumed effect, and the 90% column gives the count under a 90% target. The higher target generally requires more participants.

For example, planning for 75% of the observed effect gives 132 participants per arm for 80% power and 176 participants per arm for 90% power for the 3 mg comparison. For the 10 mg comparison, the corresponding figures are 28 and 37. These numbers are not observed group sizes and do not show what power the completed study achieved. This is not observed power.

The estimates depend on the observed effect, which can be unstable in a small study and may be larger or smaller than the effect in a future study. The registry record does not report the trial’s original design assumptions or sample-size justification. These calculations therefore illustrate how assumed effect size and target power affect planning under the stated statistical assumptions; they do not establish that the original trial was adequately sized.

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 = 0.237; treatment proportion p₁ = 0.315; average p̄ = 0.276.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6322 = 1.2391.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6298 = 0.5301.
4. n = (1.2391 + 0.5301)² / (0.0775)² = 520.8, rounded up to 521 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 <- 0.23728813559322                          # control proportion
p1 <- 0.314814814814815                          # 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(550446)
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 = 521 (80% power), 697 (90% power)
 75% of observed effect: n per arm = 907 (80% power), 1,213 (90% power)
 50% of observed effect: n per arm = 1,993 (80% power), 2,667 (90% power)
power.prop.test: 520.8 
Simulated power at n = 521 per arm: 0.799 (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. Multiplicity, Missing Data and Analysis Populations

The trial compares five CP-690,550 dose groups with the same placebo group, and it also includes an adalimumab group. Each comparison creates an opportunity for a nominally unusual result, even if the treatments did not differ from placebo. In general, testing several hypotheses without accounting for multiplicity can increase the overall chance of a false-positive finding. A prespecified hierarchy, an adjustment procedure, or a clearly exploratory interpretation can address this issue, but the registry record does not report which approach was planned or used.

The recalculated p-values are unadjusted. The intervals are also comparison-specific, not multiplicity-adjusted simultaneous intervals. The findings for the individual contrasts should therefore not be read as if a family-wise error strategy had been applied. No registry analysis entries are reported, and the record does not provide a detailed statistical analysis plan or interim-analysis information.

Missing data are handled using Baseline Observation Carried Forward for the primary outcome. The registry record does not report how many Week 12 observations were missing, why they were missing, or whether sensitivity analyses tested other assumptions. In general, the effect of an imputation method depends on both its assumptions and the amount and pattern of missingness. The stated method is part of the reported analysis definition, but its consequences cannot be fully assessed from the available registry information.

The Full Analysis Set includes randomized participants who received at least one dose and had at least one post-baseline measure. This is the population specified for the reported primary analysis. The registry record does not give a participant flow account sufficient to assess exclusions from the randomized population or to compare results under other analysis populations.

The record lists 39 outcome measures and 30 posted secondary outcomes. That breadth reinforces the need to distinguish the primary endpoint from secondary and exploratory outcomes, and to consider multiplicity when interpreting results across outcomes and treatment contrasts. The original protocol’s hierarchy, multiplicity strategy, and handling of missing secondary outcomes are not reported in the registry record.

14. 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 2% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: pneumonia (5.4%), anaemia (2.9%), gastric ulcer (2.9%), wound infection (2.9%), panic attack (2.9%).

The registry safety results list serious adverse events and other adverse events by reported safety group. These are counts of participants affected among participants at risk in each group, not event rates calculated. For example, the serious adverse event entry is 2 among 37 at risk for CP-690,550 1 mg, 0 among 49 at risk for CP-690,550 5 mg, 1 among 61 at risk for 10 mg, and 4 among 57 at risk for 15 mg. Placebo is listed as 2 among 34 at risk. The groups include treatment-switch entries, which are listed separately from the original dose groups and should not be combined without further information.

The registry also lists serious adverse event terms and percentages, including pneumonia at 5.4%, anaemia at 2.9%, gastric ulcer at 2.9%, wound infection at 2.9%, panic attack at 2.9%, and acute pyelonephritis at 2.3%. These entries describe reported events; they do not establish that a treatment caused them. The number of deaths is not reported in the registry record.

Safety counts are descriptive. Group sizes and exposure may differ, and the record does not provide enough detail to make adjusted comparisons or to assess timing and duration. These figures should be interpreted as registry-reported counts, not as a complete causal evaluation of treatment safety.

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

The posted Week 12 data show that the observed ACR20 response percentage was higher in each CP-690,550 group than in placebo. The percentages were 31.48% for 1 mg, 45.1% for 3 mg, 61.22% for 5 mg, 72.13% for 10 mg, and 71.93% for 15 mg, compared with 23.73% for placebo. Adalimumab was 39.62%. The pattern is a description of this study’s analyzed participants and endpoint, not proof that any regimen works or fails.

The unadjusted recalculations show intervals excluding zero for the 3 mg, 5 mg, 10 mg, and 15 mg comparisons with placebo, and intervals including zero for 1 mg and adalimumab. Those results express statistical evidence under the recalculation assumptions. They do not show that the groups were balanced on all relevant factors, account for missing-data uncertainty, or resolve the multiplicity of comparing several groups with one control.

ACR20 captures a specified level of improvement across joint counts and other core measures. It does not indicate how much participants improved beyond the threshold, how long any response lasted, or whether the response matters to an individual participant. The primary measure is at Week 12, while the study treatment period is described as 6 months; the result alone does not describe later outcomes.

The registry record does not report the original sample-size justification, a complete statistical plan, multiplicity handling, missing-data sensitivity analyses, or formal adjusted sponsor estimates. The sample-size illustrations are planning exercises rather than evidence about the power of the completed trial. The safety entries are descriptive and do not establish causation. Taken together, the posted results support a careful account of observed response proportions and their uncertainty, not a definitive treatment ranking or a broad conclusion beyond this trial’s population, endpoint, time point, and analysis.

16. Why This Trial Matters Statistically

This study presents a useful statistical setting: several dose groups are compared with a shared placebo group, a composite binary endpoint is used, and the main registry outcome is reported as a percentage. That combination makes it important to separate the observed arm percentages from the uncertainty around each comparison. A visibly higher response percentage is not automatically a precise or clinically important difference.

The dose-group pattern also illustrates why results should not be reduced to a simple dose-response claim. The observed percentages increase across the first four listed doses, while the 10 mg and 15 mg values are similar. The registry’s recalculated comparisons address each treatment group against placebo, not dose-to-dose contrasts. Without direct comparisons and the original analysis plan, the observed ordering alone cannot establish that one dose is superior to another or identify a preferred dose.

The study also highlights the interpretive role of missing-data rules. Baseline Observation Carried Forward is explicitly part of the primary outcome analysis, so the reported response percentages are conditional on that approach. Without the missingness pattern and sensitivity analyses, readers cannot tell how alternative assumptions might change the results.

Finally, the multiplicity issue is visible from the design: multiple doses, an active comparator, and many listed outcomes. The registry record does not report a procedure for controlling the error rate across comparisons. The unadjusted p-values and intervals can still describe individual contrasts, but they do not settle the broader family of questions. These features make the trial statistically informative as a set of estimates while placing clear limits on confirmatory interpretation.

17. 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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The primary analysis is based on the Full Analysis Set rather than all randomized participants: participants had to receive at least one dose and have at least one post-baseline measure. The registry record does not provide sufficient participant-flow details to assess how many randomized participants were excluded under this definition or whether exclusions differed across groups.

The primary endpoint uses Baseline Observation Carried Forward for missing values. The number and pattern of missing Week 12 observations, reasons for missingness, and sensitivity analyses are not reported in the registry record. The effect of the imputation choice therefore cannot be evaluated from the posted summary alone.

The recalculated comparisons are unadjusted and compare each treatment group with placebo. The registry record does not report a multiplicity procedure, adjusted estimates, or direct comparisons among dose groups. The many listed outcome measures and multiple treatment contrasts make this a material limitation when interpreting nominal p-values.

Although the study is described as lasting 6 months, the primary endpoint is at Week 12. The posted primary result does not establish how response changed over the remainder of the treatment period. The registry record also does not report the original sample-size justification, detailed analysis plan, interim-analysis plan, or the rationale for the selected outcome analysis.

The safety listing contains original-treatment and treatment-switch groups. Without further details about exposure and event attribution, the separate counts should not be combined into a treatment-level causal comparison. Death counts are not reported in the registry record. Finally, the study is identified as phase 2, and the results apply to the registry-defined population, endpoint, time point, and analysis rather than to all people with rheumatoid arthritis or all treatment settings.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: A Phase 2 Study For Patients With A Physician's Diagnosis Of Rheumatoid Arthritis — NCT00550446.
• Registry record last updated 2013-01-03; status last verified 2012-11.
• Results first posted 2013-01-03.
• 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.

21. Record Summary

The registry record identifies NCT00550446 as a completed phase 2 randomized, quadruple-masked, parallel-group study sponsored by Pfizer. It enrolled 386 participants with active rheumatoid arthritis and compared five CP-690,550 dose regimens with adalimumab and placebo. The study is described as administering treatment for 6 months.

The primary endpoint was the percentage achieving ACR20 at Week 12. The analysis population was the Full Analysis Set, defined as randomized participants who received at least one dose and had at least one post-baseline measure; Baseline Observation Carried Forward was used for missing values. Posted response percentages were highest in the 10 mg and 15 mg groups, and the recalculated comparisons with placebo were unadjusted.

The record lists 39 outcome measures and 30 posted secondary outcomes. The original sample-size rationale, multiplicity procedure, detailed statistical plan, and missing-data sensitivity analyses are not reported in the registry record. Safety results include serious and other adverse event counts by reported group, but death counts are not reported.