Rituximab for Treatment of Systemic Sclerosis-Associated Pulmonary Arterial Hypertension (SSc-PAH): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Rituximab for Treatment of Systemic Sclerosis-Associated Pulmonary Arterial Hypertension (SSc-PAH) (NCT01086540), a randomized phase 2 study. The primary outcome is Change From Baseline in Distance Walked During a Six Minute Walk Test.

2. Clinical Question

The clinical rationale in the registry record concerns whether immune modulation might affect SSc-PAH. The record describes the condition as a serious manifestation of systemic sclerosis and notes that treatment is limited to vasodilator therapy used in PAH. It also cites prior immunotherapy research in SSc-interstitial lung disease and pre-clinical and anecdotal evidence as motivation for testing rituximab. Those points explain the study question; they are not results of this trial.

3. Trial Design

This was a randomized, double-blind, placebo-controlled, phase II, multicenter trial with a parallel-group model. The registry lists quadruple masking. Enrollment was 57, and the record lists the trial status as completed. The start date was 2011-06-24 and the primary completion date was 2018-06-05. The sponsor was the National Institute of Allergy and Infectious Diseases (NIAID).

The intervention groups were rituximab plus pulmonary arterial hypertension standard-of-care therapy and placebo plus that same standard-of-care context. Both groups were described as receiving two intravenous infusions two weeks apart. The registry also lists CMRI, prednisone, methylprednisolone, diphenhydramine, and acetaminophen among the interventions, but the record does not explain their specific roles in the posted comparison. Further details about allocation procedures, concealment, or the masking roles are not reported in the registry record.

The primary outcome was change from baseline in six-minute walk distance, measured in meters from baseline before treatment initiation to Week 24. The Modified Intent-to-Treat definition includes randomized participants who met entry criteria and initiated therapy; participants who discontinued assigned therapy remained included in their randomized groups. The primary outcome groups each list 27 participants. The record does not report a fuller account of the analysis population flow, including reasons for any exclusions from the randomized enrollment.

The registry lists 19 outcome measures and 15 analyses, with secondary outcomes covering pulmonary vascular resistance, walking distance at later follow-up, clinical worsening, PAH medication changes, quality of life, and digital ulcers. Not every listed outcome has a posted analysis in the data used for this account. The original statistical plan, sample-size justification, planned interim analyses, and detailed protocol 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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The Modified Intent-to-Treat (ITT) population included all randomized participants who met entry criteria and initiated therapy. Participants who, for whatever reason, did not complete their assigned therapy were included in the ITT population in the groups to which they were randomized.

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: All randomized participants

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in Distance Walked During a Six Minute Walk Test, measured over Baseline (Pre Treatment Initiation) to Week 24.

The primary endpoint is change from baseline in distance walked during a six-minute walk test, measured in meters from pre-treatment baseline to Week 24. Participants are asked to walk as far as possible for six minutes on a hard, flat surface, at a self-selected pace, with rest permitted as needed. The recorded total distance is the outcome; the registry states that longer distances indicate better outcomes.

This test provides a continuous measure of walking capacity. A change score compares a participant’s recorded distance at follow-up with their baseline distance, allowing the analysis to focus on change over the specified period rather than follow-up distance alone. A group comparison can describe whether the average or modeled change differs between treatment groups. It does not, by itself, explain why an individual’s walking distance changed or establish the effects of treatment on every aspect of SSc-PAH.

Walking distance is one functional measure among the outcomes in the registry. The record also lists measures of pulmonary vascular resistance, quality of life, clinical worsening, PAH medication changes, and digital ulcers. These outcomes address different aspects of health and should not be treated as interchangeable with the primary endpoint. The six-minute walk test was selected as the primary measure in this trial, but the reason for that choice and any prespecified threshold for a clinically important change are not reported in the registry record.

7. Results Posted in the Registry

• Rituximab: mean 23.60 versus 0.50 on control; difference 23.10 (95% CI -5.79 to 51.99), standardized effect d = 0.43; z-test p = 0.117.

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.

Change From Baseline in Pulmonary Vascular Resistance Measured by Right Heart Catheterization at Week 24

• 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:
  • Rituximab: mean -0.50 versus 0.10 on control; difference -0.60 (95% CI -1.99 to 0.79), standardized effect d = -0.23; z-test p = 0.397.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Rituximab and the control. The interval gives the range of effects that remain compatible with the data.

Time to Clinical Worsening

• 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 deviations.
• Result:
  • Rituximab: mean 21.20 versus 26.20 on control; difference -5.00 (95% CI -10.56 to 0.56), standardized effect d = -0.48; z-test p = 0.078.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Rituximab and the control. The interval gives the range of effects that remain compatible with the data.

Time to the Change or Addition of New Pulmonary Arterial Hypertension (PAH) Therapeutic Medications

• 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 deviations.
• Result:
  • Rituximab: mean 21.20 versus 26.70 on control; difference -5.50 (95% CI -11.13 to 0.13), standardized effect d = -0.52; z-test p = 0.055.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Rituximab and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes span physiological measures, functional status, clinical events, medication changes, quality of life, and digital ulcers. The posted inferential results available for discussion include pulmonary vascular resistance and two time-to-event outcomes. These do not form a single consistent signal that independently confirms the primary walking-distance result. The record lists additional secondary outcomes, but their results are not reported in the registry record used for these comparisons.

The pulmonary vascular resistance recalculation has an interval spanning zero, and the sponsor’s mixed models analysis reports p = 0.42. The sponsor reports log-rank p-values of 0.92 for time to clinical worsening and 0.36 for time to PAH medication change or addition. These analyses do not establish a clear between-group difference on those outcomes. They also should not be taken as proof that the groups are equivalent or that an effect is absent; the posted summaries do not provide the full effect estimates and precision information for those time-to-event comparisons.

Secondary outcomes relate to the primary result by showing whether other measured domains point in a similar direction or suggest a broader pattern. They are not substitutes for the primary endpoint, which was change in six-minute walk distance at Week 24. Differences in outcome type, timeframe, and analysis method mean that results cannot simply be combined into one overall effect.

Unadjusted secondary results carry less weight because multiple endpoints and analyses create more opportunities for chance findings. The registry does not report a multiplicity adjustment or a complete prespecified hierarchy for interpreting secondary outcomes. Accordingly, isolated secondary p-values should be treated as exploratory evidence and interpreted with the primary result, uncertainty, and missing analysis details in mind, rather than as definitive confirmation.

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

• Change From Baseline in Pulmonary Vascular Resistance Measured by Right Heart Catheterization at Week 24
• Change From Baseline in Distance Walked During a Six Minute Walk Test at Week 24 and Week 48
• Time to Clinical Worsening
• Time to the Change or Addition of New Pulmonary Arterial Hypertension (PAH) Therapeutic Medications
• Change From Baseline in Quality of Life as Measured by the Short Form Health Survey (SF-36): Mental Component Summary Score
• Change From Baseline in Quality of Life as Measured by the Short Form Health Survey (SF-36): Physical Component Summary Score
• Change in Quality of Life as Measured by the Disability Index of the Scleroderma Health Assessment Questionnaire (HAQ-DI)
• Number of New Digital Ulcers

9. Statistical Interpretation

10. Statistical Methods Explained

The registry combines descriptive arm summaries with analyses comparing the randomized groups. These serve different purposes. An arm estimate describes the outcome within that group; a between-group estimate addresses the treatment comparison. For the primary endpoint, the posted arm values are least-squares means for change, with standard errors. The simple recalculation uses the posted summary statistics to estimate an unadjusted mean difference and an interval. It is not a replacement for the trial’s reported model-based analysis.

What does a standard error describe?

A standard error describes the estimated uncertainty around a group summary, rather than the spread of individual participant outcomes. A smaller standard error generally indicates a more precisely estimated summary, while a larger one indicates greater uncertainty. It should not be read as the range in which most individual outcomes fall. The record reports standard errors for the primary and pulmonary vascular resistance arm summaries; it does not provide participant-level data or enough detail to reconstruct the full fitted models.

The primary registry analysis is described as a mixed models analysis, and its parameter is labeled “Median Difference (Final Values).” The endpoint itself is described as change from baseline, and the displayed arm summaries are least-squares mean changes. These labels describe different aspects of the reported result and should not be silently treated as identical estimands. The registry does not report model specification, covariates, covariance structure, or the precise relationship between the final-value analysis and the change-score summaries. The sponsor’s reported analysis is therefore best quoted as posted, with the simple recalculation identified separately.

What does the recalculated comparison add?

The recalculated primary comparison uses the posted summaries to give a transparent unadjusted mean difference, interval, and p-value. The estimate is 23.1 meters, the interval is -5.792 to 51.99, and the unadjusted p-value is 0.117. Because the recalculation is based on summary statistics rather than participant-level records, it cannot reproduce adjustments or other features of the sponsor’s model. The registry record does not report a discrepancy flag, but the difference in analysis descriptions remains important when interpreting the two results.

For pulmonary vascular resistance, the registry reports least-squares mean changes with standard errors, and the recalculated comparison is likewise a simple unadjusted mean difference. For the time-to-event outcomes, the sponsor reports log-rank tests. A log-rank test compares the pattern of event timing between groups using event-time information; it is not equivalent to comparing arithmetic mean weeks. The displayed descriptive means and the inferential log-rank p-values answer different questions. The registry does not provide hazard ratios, event counts for those comparisons, or corresponding confidence intervals in the reported analyses.

How should p-values be read?

A p-value describes how unusual the observed data, or more extreme data, 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 an effect. The registry reports p = 0.12 for the primary mixed models analysis and p = 0.117 for the unadjusted recalculation. The secondary analyses also include their own p-values. Because the registry does not report a multiplicity procedure, these individual values should not be read as if each were the sole planned test.

General statistical context: confidence intervals express uncertainty about an estimated quantity under the analysis assumptions. Their width reflects precision, and the range of values they cover is often more informative than a binary significant/not-significant label. Here, the recalculated primary interval includes zero and spans negative and positive effects. The confidence level for the intervals is not reported in the registry record, so it is not named.

The registry describes the primary analysis population as Modified Intent-to-Treat. This includes eligible randomized participants who initiated therapy and keeps participants who did not complete assigned therapy in their randomized groups. That definition is useful for understanding who was intended to contribute to the primary comparison. It does not, on its own, tell how missing follow-up measurements were handled or whether all participants had an observed Week 24 test. Those details are not reported in the registry record.

11. Confidence Intervals and Precision

The recalculated primary mean difference is 23.1 meters, with an interval from -5.792 to 51.99 meters. The interval is wide relative to the point estimate and includes zero. This means the posted summaries do not pin down the direction or size of the between-group difference with high precision: values representing some disadvantage for rituximab and values representing a larger advantage are both within the reported range. The confidence level for this interval is not reported in the registry record.

The point estimate is a single value summarizing the comparison, but it should not be mistaken for a precise prediction of the effect in another study or for the effect in every participant. Standard errors of 11.1 meters for rituximab and 9.7 meters for placebo indicate uncertainty in the posted arm summaries. The group comparison’s interval captures uncertainty in the difference under the recalculation’s assumptions. It does not account for every possible limitation, including model choices, outcome missingness, or the fact that a summary-statistic recalculation is not the sponsor’s full analysis.

The sponsor’s mixed models analysis reports a median difference in final values of 23.1 and p = 0.12, but no interval is posted for that analysis. Without that interval, its precision cannot be assessed from the registry result in the same way as the recalculated comparison. The pulmonary vascular resistance recalculation also has an interval that spans zero, from -1.988 to 0.788 Woods Units. The registry’s reported time-to-event analyses provide p-values but no effect estimates or intervals in the posted analysis summaries.

Precision and clinical importance are separate considerations. Even a narrow interval would not establish whether an effect matters to patients without a meaningfulness threshold; a broad interval does not prove that no meaningful effect exists. The registry does not report a clinically important difference threshold for walking distance, limiting interpretation of the primary estimate’s practical significance.

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 translate an observed effect into hypothetical planning scenarios; they are not the trial’s original design calculations. For the continuous outcomes, the figures are participants per arm. For the time-to-event planning entries, they are total numbers of events, not participants per arm. The planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation; each scenario targets a stated fraction of the observed effect. The original trial’s own design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the number of participants per arm, or total events for time-to-event entries, that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect under those assumptions. The 90% power column uses a higher target chance of detection, so it requires more information in the listed scenarios. These are planning illustrations based on the observed effect, not observed power for the completed trial.

Rows for 100% of the observed effect use the estimated effect as the planning target; the 75% and 50% rows consider progressively smaller targets. Smaller effects are harder to distinguish from random variation, so the illustration requires more participants or events to detect them at the same power target. These calculations are sensitive to the estimated effect, which itself is uncertain. In particular, using a trial’s observed estimate as a planning input can yield unstable projections when the estimate is imprecise. The figures are therefore useful for seeing how assumptions affect planning, not as a guarantee that a future study would achieve a particular result.

The curve should be read alongside these assumptions: it illustrates how the planning requirement changes with the effect targeted. It does not show what power this trial achieved, nor does it establish that the original trial was designed around these assumptions.

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 = 23.100; pooled standard deviation σ = 54.162.
2. n = 2 × (1.96 + 0.842)² × 54.162² / 23.100² = 86.3, rounded up to 87 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 <- 23.1                      # observed difference in means
sigma <- 54.1622562307                     # 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(1086540)
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 = 87 (80% power), 116 (90% power)
 75% of observed effect: n per arm = 154 (80% power), 206 (90% power)
 50% of observed effect: n per arm = 346 (80% power), 463 (90% power)
power.t.test: 87.3 
Simulated power at n = 87 per arm: 0.795 (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

For the primary endpoint, the registry’s reported analysis is a mixed models analysis labeled as a median difference in final values. It reports a value of 23.1 and p = 0.12. The separate recalculation from posted summary statistics gives an unadjusted mean difference of 23.1 meters, an interval from -5.792 to 51.99, and p = 0.117. The point estimates are numerically the same as posted, while the analysis descriptions and p-values are not identical.

The recalculation should be understood as a simple unadjusted check based on summary statistics, not as a reconstruction of the mixed model. It cannot account for model details that are not in the registry record. The sponsor’s analysis and the recalculation therefore have distinct roles: the former is the trial’s reported inferential result, and the latter provides a transparent, limited comparison based on the displayed summaries. The registry does not report a discrepancy flag.

For pulmonary vascular resistance, the reported mixed models analysis gives -0.6 with p = 0.42, while the recalculation gives -0.6 with p = 0.397 and an interval from -1.988 to 0.788. Again, matching point estimates do not make the analyses interchangeable. For time-to-event endpoints, the sponsor reports log-rank p-values; a simple comparison of descriptive mean weeks is not the same analysis. Those log-rank results should be quoted as reported rather than replaced with the mean-difference recalculations.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 19 outcome measures and 15 analyses, and the posted results include a primary endpoint and multiple secondary outcomes. Testing or estimating many outcomes raises a multiplicity question: when each result is assessed separately, the chance of at least one apparently unusual result can increase. A statistical plan can address this through prespecified outcome hierarchies, adjustment procedures, or explicit exploratory labeling. A multiplicity adjustment or hierarchy is not reported in the registry record, so the secondary p-values should not be interpreted as though they necessarily account for the full family of analyses.

The record identifies a Modified Intent-to-Treat population for the primary outcome: randomized participants who met entry criteria and initiated therapy, with participants who did not complete assigned therapy retained in their randomized groups. That is a useful description of the analysis population, but it does not explain how missing endpoint measurements were addressed. The number of missing Week 24 tests, reasons for missingness, imputation methods, sensitivity analyses, and assumptions about missing data are not reported in the registry record.

Missingness matters because a comparison of observed follow-up measurements can be affected if participants without measurements differ systematically from those measured. General statistical context: methods for missing data rely on assumptions about why values are missing, and sensitivity analyses can help assess how conclusions change under alternative assumptions. No such details should be inferred from the population label alone.

The registry describes a randomized, double-blind, placebo-controlled study and supplies an analysis population definition, but does not report the full statistical analysis plan, interim-analysis plan, or detailed model specification. The record also does not provide enough information to assess whether all outcomes were analyzed as initially planned. These absences limit how fully the multiplicity and missing-data risks can be evaluated.

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: right ventricular failure (7.1%), myocardial infarction (6.9%), device related infection (6.9%), cardiac arrest (3.6%), right ventricular dysfunction (3.6%).

The adverse-event summary lists participants at risk and participants affected by serious adverse events and other adverse events, as well as deaths. For serious adverse events, the rituximab group lists 14 affected among 29 at risk, and the placebo group lists 9 affected among 28 at risk. For other adverse events, the corresponding entries are 28 among 29 and 24 among 28. The death counts listed are 8 for rituximab and 5 for placebo.

These figures are descriptive counts from the registry record. They do not establish that an event was caused by the assigned treatment, and they should not be interpreted as a direct treatment comparison without details about event definitions, timing, attribution, exposure, and statistical analysis. The record does not report those details in the adverse-event summary.

The registry lists serious-event terms including right ventricular failure, myocardial infarction, device related infection, cardiac arrest, right ventricular dysfunction, and hyperthyroidism, with percentages of 7.1%, 6.9%, 6.9%, 3.6%, 3.6%, and 3.6%, respectively. The record does not provide enough context in this summary to infer comparative risks from these listed terms. Safety counts should be read alongside the trial’s size, follow-up, and reporting definitions, rather than as proof of safety or harm.

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

The registry results describe a randomized comparison of rituximab and placebo on change in six-minute walk distance over the specified primary period. The posted arm summaries favor a larger mean change in the rituximab group, and the unadjusted recalculation estimates a difference of 23.1 meters. However, the interval from -5.792 to 51.99 includes zero, and the sponsor’s mixed models analysis reports p = 0.12. The evidence therefore does not establish a clear difference on the primary endpoint in the posted analysis.

This does not mean the treatments are equivalent. Demonstrating equivalence or non-inferiority requires a suitable design, prespecified margin, and analysis; those are not reported. Nor does an uncertain estimate prove that no clinically important effect exists. The interval includes a range of possible differences, and the registry does not report a threshold for clinical importance against which to judge them.

The result also does not answer every question about SSc-PAH. The study measured a set of outcomes beyond walking distance, but the secondary findings are incomplete and include different kinds of measures and analyses. The primary outcome is a functional test, not a direct measure of every aspect of disease progression, quality of life, or safety. The registry’s stated aim and rationale explain why rituximab was studied; they do not change what the outcome estimates can establish.

Finally, these results are specific to the trial population and analysis as recorded. The registry does not report enough detail to assess all missing-data assumptions, multiplicity handling, or model choices. The findings should therefore be understood as estimates with uncertainty, not as medical advice or a universal conclusion about treatment.

18. Why This Trial Matters Statistically

This trial is statistically informative because it shows why an estimated treatment difference must be read together with its uncertainty. The primary point estimate is positive, but the recalculated interval crosses zero and is broad. Reporting the estimate alone could overstate certainty; focusing only on the p-value could obscure the range of effects compatible with the data. Both pieces of information matter for interpreting what the trial can resolve.

The study also illustrates the distinction between a trial’s reported model and a simple recalculation from summary statistics. The registry reports a mixed models analysis, while the recalculation uses posted group summaries to provide an unadjusted comparison. Their point estimates align, but their methods are not interchangeable. Statistical transparency depends on keeping the reported analysis, descriptive summaries, and recalculation clearly distinguished.

Its secondary outcomes highlight another recurring issue: trials can assess multiple outcomes of different types, and individual unadjusted results do not automatically add up to a coherent conclusion. The registry does not report multiplicity procedures or full analysis details, making cautious interpretation especially important. The study therefore offers a useful example of how design labels, endpoint definitions, analysis populations, precision, and reporting completeness jointly shape what can be concluded from a trial record.

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 important analytical details unavailable. The mixed models analysis is named, but its specification, covariates, and handling of repeated or missing measurements are not reported in the registry record. The primary endpoint description and the reported analysis parameter also use different labels: change from baseline and least-squares mean change for the endpoint summary, versus median difference in final values for the sponsor analysis. The relationship between these estimands is not explained.

The recalculated primary interval is based on posted summary statistics and is not a participant-level reanalysis. The confidence level is not stated in the registry record. The record also does not report a threshold for a clinically important change in walking distance, so statistical uncertainty cannot be translated directly into clinical importance.

Multiplicities across outcomes and analyses cannot be evaluated fully because an adjustment procedure or hierarchy is not reported. Missing-data counts, reasons, methods, and sensitivity analyses are also not reported. The time-to-event results are presented as log-rank p-values without effect estimates or intervals in the posted analyses, limiting assessment of their magnitude and precision.

The adverse-event summary gives counts and selected terms, but the information needed to interpret comparative safety—including fuller definitions, attribution, and timing—is not reported in that summary. These limitations do not invalidate the posted results, but they restrict how far the estimates can support conclusions beyond the outcomes and analyses explicitly recorded.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Rituximab for Treatment of Systemic Sclerosis-Associated Pulmonary Arterial Hypertension (SSc-PAH) — NCT01086540.
• Registry record last updated 2023-02-21; status last verified 2023-01.
• Results first posted 2020-08-21.
• 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

NCT01086540 is a completed randomized, double-blind, placebo-controlled, phase II, multicenter trial of rituximab versus placebo alongside pulmonary arterial hypertension standard-of-care therapy in systemic sclerosis-associated PAH. The primary endpoint was change in six-minute walk distance from baseline to Week 24 in the Modified Intent-to-Treat population.

The registry’s primary mixed models analysis reports a median difference in final values of 23.1 and p = 0.12. A simple unadjusted recalculation gives a mean difference of 23.1 meters, with an interval from -5.792 to 51.99 and p = 0.117. The interval reflects substantial uncertainty and includes zero. Secondary results and adverse-event counts provide additional context, but interpretation is limited by unreported details on multiplicity, missing data, and analysis methods.