The Effects of Tysabri Treatment on Vaccination Response and Lymphocyte Subsets in Subjects With Relapsing Forms of Multiple Sclerosis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effects of Tysabri Treatment on Vaccination Response and Lymphocyte Subsets in Subjects With Relapsing Forms of Multiple Sclerosis (NCT00536120), a randomized phase 4 study. The primary outcome is Percentage of Keyhole Limpet Hemocyanin (KLH) Responders at Day 28 Post-Vaccination.

2. Clinical Question

3. Trial Design

This was a randomized, open-label, parallel-group Phase 4 study of participants with relapsing forms of multiple sclerosis. The registry lists enrollment of 60 and a status of completed. The start is recorded as 2008-01 and primary completion as 2009-11. The sponsor was Biogen. Because masking is listed as none, participants and study personnel were not blinded according to the registry record.

One group received Tysabri plus vaccinations. Its description specifies 9 monthly doses of Tysabri 300 mg intravenous, with KLH and Td vaccinations at Month 6 following the 7th dose. The other group received vaccinations only: KLH at Month 0 and 14 and 28 days later, and Td at Month 0. That group did not receive multiple-sclerosis treatment during the study and remained through Month 2. The endpoint timeframe is stated as 28 days after immunization, corresponding to Day 28 in the Vaccinations Only group and Day 196 in the Tysabri Plus Vaccinations group.

The primary objectives were to assess antibody responses to KLH, a neoantigen, and Td, a recall antigen, and to evaluate circulating CD3+, CD4+, CD8+, CD19+, and CD56+ lymphocyte subsets over time. The secondary objective concerned alpha4-integrin saturation and expression. The record names four secondary outcome categories: percentage change in circulating lymphocyte subsets at Month 3 and Month 6 of Tysabri therapy, and mean alpha4-integrin saturation and expression at baseline, Month 3, and Month 6. Numerical results for these outcomes are not reported in the registry record.

The reported primary endpoint is based on participants with an assessment at the specified post-vaccination time. The record says no imputation methods were used in the primary analyses. Details such as the randomization procedure, allocation concealment, the original sample-size justification, and the complete statistical analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Participants with an assessment at Day 28. No imputation methods were used in the primary analyses.

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 Percentage of Keyhole Limpet Hemocyanin (KLH) Responders at Day 28 Post-Vaccination, measured over 28 days after immunization (Day 28 for Vaccinations Only Group/Day 196 for Tysabri Plus Vaccinations Group).

The primary endpoint is the percentage of participants classified as KLH responders at Day 28 after vaccination. A responder was defined as a participant with at least a 2-fold increase over the pre-immunization level of anti-KLH antibodies in blood at 28 days after KLH vaccination. The endpoint therefore reduces an antibody measurement to a binary outcome: each assessed participant either met the response definition or did not.

The registry specifies different calendar days for the two groups while preserving the same interval after immunization: Day 28 for Vaccinations Only and Day 196 for Tysabri Plus Vaccinations. That distinction matters when reading the result because the groups had different vaccination schedules and different study timelines. The endpoint assesses antibody response at the stated post-vaccination interval; it is not a direct measure of clinical outcomes of multiple sclerosis.

A responder threshold provides a straightforward way to report how many participants crossed a prespecified antibody-change criterion. A percentage is easy to interpret at the group level, but it does not convey the full distribution of antibody changes or how far individual participants were above or below the threshold. The registry does not report the continuous antibody measurements or further details about the choice of the 2-fold criterion. The primary analysis population was participants with an assessment at Day 28, and no imputation methods were used.

7. Results Posted in the Registry

• Vaccinations Only: 82.6% (19/23) versus 89.5% (17/19) on control; risk difference -6.9 percentage points (95% CI -27.6 to 13.9), risk ratio 0.92 (0.72–1.18); unadjusted two-proportion z-test p = 0.527.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary: each participant with an assessment is classified as a KLH responder or not. A group percentage describes the proportion meeting the antibody threshold. The registry reports 89.0 for Tysabri Plus Vaccinations and 83.0 for Vaccinations Only. These are the posted arm-level values; the displayed comparison is a risk difference, a measure of the difference between two proportions expressed on the probability scale.

The risk-difference estimate is -0.069. Its confidence interval extends from -0.276 to 0.139. The interval communicates uncertainty around the estimated difference: it gives a range of values compatible with the data and the method used to construct it. Because the range includes zero and values on both sides of zero, the posted results do not pin down the direction of the difference. The interval is also wide, indicating limited precision for this comparison.

The registry reports an unadjusted p-value of 0.527. In general, a p-value measures how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the test assumptions held. It is not the probability that the null hypothesis is true, and it does not tell readers whether a difference is important. The specific statistical test used for the registry comparison is not reported in the registry record. The p-value is labelled unadjusted, and the registry does not report a multiplicity adjustment for this comparison.

What does a risk difference express?

A risk difference compares the proportions with an event or response in two groups by taking one proportion relative to the other. In this trial, the event is meeting the KLH responder definition. A value of zero corresponds to equal proportions. Positive or negative values indicate which group has the larger recorded proportion only when the subtraction order is clear. The posted estimate is associated with the comparison of Vaccinations Only against the listed control group, Tysabri Plus Vaccinations; readers should use the registry’s displayed contrast and not infer a different contrast from arm labels alone.

Other relative measures can describe binary outcomes, but the main comparison reported for this endpoint is the risk difference. The registry also lists ratio-based estimates in the comparison record, but the confidence interval for the risk difference is the direct absolute-scale uncertainty measure. The arm percentages and the comparison estimate are rounded registry results and need not appear identical when read as a simple subtraction. No recalculation is needed to interpret the sponsor’s posted result.

Why does the confidence interval matter?

A point estimate is a single summary, while a confidence interval shows how uncertain that estimate is under the analysis method. An interval that spans zero means the observed data are compatible with no difference as well as with differences in either direction. It does not prove equality. A narrow interval would indicate greater precision, whereas a wider interval leaves more uncertainty about the size and direction of the contrast. The interval should be considered together with the limited endpoint analysis counts and the distinction between the groups’ assessment days.

General statistical interpretation also depends on design and analysis choices, including how the endpoint population was defined and how missing observations were handled. The registry identifies participants with an assessment at Day 28 and says no imputation methods were used. It does not describe a specific inferential test, a confidence-interval construction method, or other adjustments. Those details are not reported in the registry record, so they should not be assumed.

What is and is not established?

The posted statistics quantify the observed responder percentages and their comparison. They do not establish a causal mechanism, explain the antibody response of individual participants, or demonstrate a difference in clinical outcomes. Randomization is part of the design, but open-label conduct and incomplete reporting of allocation and analysis details limit what can be assessed from the registry record alone. Statistical significance, even if reported, would not by itself establish clinical importance; in this case the interval and p-value should be read as evidence of substantial uncertainty rather than as proof of no difference.

10. Confidence Intervals and Precision

The reported risk-difference estimate is -0.069, with a confidence interval from -0.276 to 0.139. The interval includes zero and extends to values on both sides of it. This means the endpoint data do not precisely identify the direction of the difference between the groups. The interval is wide relative to the point estimate, so considerable uncertainty remains about the size of any difference compatible with the results.

A confidence interval is a statistical range constructed by a method that, under its assumptions, has a stated long-run coverage property. It is not a guarantee that the true value lies in this particular interval, nor does it assign a probability to each value within the interval. The specific interval method is not reported in the registry record. Its interpretation also depends on the endpoint definition and analysis population: the primary analysis used participants with an assessment at Day 28, with no imputation methods.

The displayed arm percentages are 89.0 for Tysabri Plus Vaccinations and 83.0 for Vaccinations Only. The endpoint comparison includes 19 and 23 participants, respectively. Those counts and the interval should be considered together: the posted comparison is based on a modest number of endpoint assessments, and the interval reflects limited precision. The record does not explain the difference between overall enrollment and the endpoint analysis counts.

The unadjusted p-value is 0.527. It does not replace the interval or describe effect size. The interval is more informative about the range of contrasts compatible with the analysis, while the p-value addresses a test under a null hypothesis. Neither statistic tells whether a difference is clinically important. The registry does not report a threshold for an important difference, so precision should be judged from the estimate and uncertainty without assigning an unreported clinical meaning.

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 endpoint effect, not the trial’s original design assumptions. They give participants per arm for 80% power and participants per arm for 90% power. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The planning effect is a stated fraction of the observed effect.

For planning for 100% of the observed effect, the illustration gives 399 participants per arm for 80% power and 534 participants per arm for 90% power. For planning for 75% of the observed effect, it gives 673 participants per arm for 80% power and 901 participants per arm for 90% power. For planning for 50% of the observed effect, it gives 1,431 participants per arm for 80% power and 1,915 participants per arm for 90% power.

In general, power is the chance that a planned study will detect an effect of the specified size under the assumptions used, if that effect is present. The 80% and 90% columns represent different target chances of detecting the planning effect. A higher target power generally requires a larger planned sample. Smaller effects require more participants to distinguish them from random variation, which is why the illustrations require more participants as the assumed fraction of the observed effect decreases.

These figures are planning illustrations, not observed power and not evidence about what the completed trial was designed to detect. The registry’s original sample-size justification and design assumptions are not reported in the registry record. The figures are participants per arm, not total events; the trial endpoint is a binary response rather than a time-to-event outcome.

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 = 0.895; treatment proportion p₁ = 0.826; average p̄ = 0.860.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4901 = 0.9606.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4877 = 0.4105.
4. n = (0.9606 + 0.4105)² / (-0.0686)² = 398.9, rounded up to 399 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 <- 0.894736842105263                          # control proportion
p1 <- 0.826086956521739                          # 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(536120)
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 = 399 (80% power), 534 (90% power)
 75% of observed effect: n per arm = 673 (80% power), 901 (90% power)
 50% of observed effect: n per arm = 1,431 (80% power), 1,915 (90% power)
power.prop.test: 398.9 
Simulated power at n = 399 per arm: 0.809 (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 had more than one stated objective and several named outcomes. Alongside the primary KLH responder endpoint, the registry describes antibody response to Td, circulating lymphocyte subsets, and alpha4-integrin saturation and expression. Four secondary outcome categories are listed: percentage change in CD3+, CD4+, CD8+, CD19+, and CD56+ subsets at Month 3 and Month 6 of Tysabri therapy, and mean alpha4-integrin saturation and expression at baseline, Month 3, and Month 6. Numerical results for those secondary outcomes are not reported in the registry record.

When multiple outcomes or comparisons are tested, the chance of at least one false-positive result can increase if each is assessed separately without adjustment. General approaches to multiplicity include defining a hierarchy, adjusting significance thresholds, or treating results as exploratory. The registry record does not report a multiplicity strategy, a hierarchy among the secondary outcomes, or adjusted statistical results. The primary comparison is labelled unadjusted. It is therefore not possible to determine from the record how the overall set of questions was handled statistically.

The primary analysis population is described as participants with an assessment at Day 28, and the record states that no imputation methods were used in the primary analyses. This indicates that missing primary endpoint values were not filled in by an imputation procedure. The record does not report the reasons for missing assessments, how many randomized participants lacked an endpoint assessment, or whether a sensitivity analysis examined the effects of missing data. The enrolled total and the endpoint analysis counts are not the same, but the reason for that difference is not reported in the registry record.

The registry does not provide a detailed statistical analysis plan, information on interim analyses, or a full description of the analysis populations. It is therefore not possible to establish whether all planned analyses were reported or whether any analysis choices were made after results were known. These are reporting limitations, not evidence that a particular procedure was or was not used. Interpretation should remain anchored to the posted endpoint results and the specific analysis population that the record identifies.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: multiple sclerosis relapse (3.3%), herpes zoster disseminated (3.3%), basal cell carcinoma (3.3%), angina unstable (3.3%), gastroenteritis (3.3%).

The serious adverse event summary lists 30 participants at risk in each group. Serious adverse events affected 3 participants in Tysabri Plus Vaccinations and 2 in Vaccinations Only. The registry also lists other adverse events among 30 participants at risk in each group: 25 affected in Tysabri Plus Vaccinations and 19 in Vaccinations Only. These figures are counts of affected participants as reported, not a comparison adjusted for differences in follow-up or participant characteristics.

The registry lists multiple sclerosis relapse, herpes zoster disseminated, basal cell carcinoma, angina unstable, and gastroenteritis among the serious adverse event terms, each at 3.3%. The posted summary does not make clear in this listing which group each term belongs to. Deaths are not reported in the registry record.

Adverse event counts are descriptive. They do not by themselves establish that an event was caused by a study treatment, and these summaries should not be read as a comparative safety analysis. The record does not provide enough detail about event timing, duration, seriousness criteria, attribution, or exposure-adjusted rates to make those assessments. The two groups also differed in treatment and study duration as described in the registry, which is relevant context when reading counts.

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

The primary result describes how often participants met a defined KLH antibody-response threshold in each group at the specified post-vaccination assessment. The registry reports 89.0 in Tysabri Plus Vaccinations and 83.0 in Vaccinations Only, with a risk difference of -0.069 and a confidence interval from -0.276 to 0.139. The interval includes zero and allows differences in either direction, so the comparison is imprecise. The unadjusted p-value of 0.527 does not provide evidence of a statistically clear difference under the reported comparison.

This result does not prove the groups are equivalent. A lack of a statistically clear difference is not the same as evidence that any possible difference is negligible. The registry does not report an equivalence or non-inferiority margin, and the confidence interval covers a range of possible effects. Likewise, the result does not establish that one group’s approach is superior or inferior.

The endpoint is an antibody measure defined by a threshold, not a direct clinical outcome. It does not show whether participants experienced changes in multiple-sclerosis symptoms, relapses, disability, or other outcomes. Nor does it explain how individual antibody concentrations changed beyond the responder classification. The study’s objectives included lymphocyte subsets and alpha4-integrin measures, but numerical results for those outcomes are not reported in the registry record.

The comparison is based on endpoint assessments from 19 participants in Tysabri Plus Vaccinations and 23 in Vaccinations Only. The overall enrollment was 60, and the registry does not explain the difference between enrollment and these analysis counts. No imputation methods were used in the primary analyses. Together, the limited endpoint counts and the broad interval mean that the result should be interpreted with caution and kept within the narrow scope of the posted KLH responder endpoint.

These statistics describe the registry results; they do not provide medical advice or establish what an individual participant’s response would be. They also do not resolve questions about other vaccine responses, longer-term outcomes, or the broader effects of Tysabri. Those matters are not answered by the primary endpoint comparison reported in the registry.

16. Why This Trial Matters Statistically

This study is statistically interesting because its primary endpoint turns an immune measurement into a responder classification and compares the percentages between randomized groups. That design makes the endpoint easy to express as a group-level proportion, but the result depends on the threshold chosen: participants qualify if their anti-KLH antibody level reaches at least a 2-fold increase over pre-immunization. A binary endpoint does not retain all the detail in the underlying antibody measurements.

The comparison also requires attention to timing. The registry defines the same interval after immunization but identifies Day 28 for Vaccinations Only and Day 196 for Tysabri Plus Vaccinations. The intervention group’s schedule includes Tysabri doses before vaccination, whereas the comparator group’s vaccination schedule begins at Month 0. Reading the result as a simple comparison without considering these different schedules would miss an important feature of the trial design.

Precision is central to interpreting this result. The reported confidence interval crosses zero and extends in either direction, and the endpoint analysis includes 19 and 23 participants. The point estimate alone therefore gives an incomplete picture. The interval makes the uncertainty visible and helps prevent an overconfident reading of the two arm percentages.

Finally, the registry names multiple immune outcomes but does not report numerical results for the listed secondary outcomes or a multiplicity strategy. This illustrates why a single primary result cannot answer every question in a trial with several objectives. Distinguishing the endpoint actually reported from outcomes that are only described is necessary for a disciplined statistical 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 registry record leaves several design and analysis details unreported. It identifies the study as randomized and open-label, but does not describe the randomization procedure, allocation concealment, or the detailed statistical analysis plan. The original sample-size justification and any planned interim analyses are also not reported in the registry record. Consequently, the displayed planning illustrations should not be mistaken for the trial’s original design rationale.

The primary endpoint analysis was limited to participants with an assessment at Day 28, and no imputation methods were used. The record does not explain the reasons for missing assessments, enumerate all participants without an endpoint result, or report sensitivity analyses addressing missing data. The endpoint counts of 19 and 23 are lower than the enrollment of 60, but the registry does not explain the difference.

The groups followed different vaccination schedules and had different endpoint calendar days: Day 28 for Vaccinations Only and Day 196 for Tysabri Plus Vaccinations. The stated interval after immunization is 28 days in both groups, but the distinct schedules remain relevant context for the comparison. Open-label conduct is another design feature; the record lists masking as none.

The primary endpoint is a threshold-based antibody response, and the registry does not report the underlying continuous antibody measurements or a threshold for a clinically important difference. It also does not report numerical results for the named secondary outcomes or explain how multiplicity was handled. The specific test and confidence-interval construction method are not reported in the registry record. These gaps limit assessment of the full analysis and the clinical meaning of the observed endpoint contrast.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: The Effects of Tysabri Treatment on Vaccination Response and Lymphocyte Subsets in Subjects With Relapsing Forms of Multiple Sclerosis — NCT00536120.
• Registry record last updated 2017-02-15; status last verified 2016-12.
• Results first posted 2011-07-29.
• 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 completed Phase 4 study, NCT00536120, was a randomized, open-label, parallel-group trial in participants with relapsing forms of multiple sclerosis. The registry lists enrollment of 60, a start of 2008-01, primary completion of 2009-11, and Biogen as sponsor.

The primary endpoint was the percentage of KLH responders 28 days after vaccination, defined by at least a 2-fold increase over pre-immunization anti-KLH antibody level. The registry reports 89.0 for Tysabri Plus Vaccinations and 83.0 for Vaccinations Only. The risk difference was -0.069, with a confidence interval from -0.276 to 0.139 and an unadjusted p-value of 0.527.

The endpoint analysis included 19 and 23 participants in the respective groups; no imputation methods were used. Numerical results for the listed secondary outcomes are not reported in the registry record. Serious adverse events affected 3 participants in the Tysabri Plus Vaccinations group and 2 in the Vaccinations Only group.