Lenalidomide and Vaccine Therapy in Treating Patients With Early-Stage Asymptomatic Chronic Lymphocytic Leukemia or Small Lymphocytic Lymphoma: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Lenalidomide and Vaccine Therapy in Treating Patients With Early-Stage Asymptomatic Chronic Lymphocytic Leukemia or Small Lymphocytic Lymphoma (NCT01351896), a randomized phase 2 study. The primary outcome is Proportion of Patients Who Achieve an Antibody Response.

2. Clinical Question

3. Trial Design

This is a phase II, randomized, parallel-group trial with no masking. The registry lists an enrollment of 49 and two groups: concurrent PCV13 and lenalidomide, and sequential PCV13 followed by lenalidomide. The posted primary outcome denominators are 24.0 in Arm A and 25.0 in Arm B. The registry lists the study status as active, not recruiting.

The treatment contrast concerns timing, not whether participants received lenalidomide or PCV13: both groups were assigned both interventions, but the vaccine was scheduled differently relative to lenalidomide. Arm A received lenalidomide from course 1 and PCV13 on day 1 of courses 3 and 5. Arm B received PCV13 on days 1 and 78, then began lenalidomide in course 4. The lenalidomide schedule was once daily by mouth on days 1-28, with 28-day cycles and a planned duration of at least 24 cycles unless disease progression or unacceptable toxicity occurred.

The study also lists biospecimen collection, bone marrow aspiration and biopsy, and computed tomography among its procedures. The registry record gives a start date of 2011-11-02 and a primary completion date of 2024-07-08. It does not report the trial's original sample-size justification, detailed randomization procedure, allocation concealment, or protocol-specific analysis plan. These should not be inferred from the randomized label or from the posted results.

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

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 Proportion of Patients Who Achieve an Antibody Response, measured over Up to 1 month.

The primary endpoint is the proportion of participants who achieve an antibody response after vaccination, assessed up to 1 month. The registry definition requires either at least a four-fold increase in post-vaccination serotype-specific IgG titers or serotype-specific IgG concentrations of at least 0.35 ug/mL for 6 of 7 serotypes measured by a standard enzyme linked immunosorbent assay.

This endpoint is used to assess a vaccine-related immune response. In this trial, comparing the response proportions between the concurrent and sequential schedules addresses whether antibody responses differed by timing of PCV13 relative to lenalidomide. It does not, by itself, measure whether participants had fewer infections, delayed disease progression, or improved survival. Those are different clinical questions; the registry lists outcomes such as progression-free survival and overall survival separately.

Because the endpoint is binary, each participant is classified as having achieved or not achieved the defined response, and the result is expressed as a percentage. The posted primary response percentages are based on the participants included in each arm's reported denominator. The registry record does not describe how missing antibody measurements were handled or whether the primary analysis used a prespecified analysis population.

7. Results Posted in the Registry

• Arm B (Sequential PCV13 and Lenalidomide): 88.0% (22/25) versus 75.0% (18/24) on control; risk difference 13.0 percentage points (95% CI -8.5 to 34.5), risk ratio 1.17 (0.89–1.54); unadjusted two-proportion z-test p = 0.240.

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.

Complete Response Rate

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Arm B (Sequential PCV13 and Lenalidomide): 0.0% (0/20) versus 6.2% (1/16) on control; risk difference -6.2 percentage points (95% CI -18.1 to 5.6); unadjusted two-proportion z-test p = 0.257.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm B (Sequential PCV13 and Lenalidomide) and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists 32 posted secondary outcomes covering immune response, disease response, time-to-event outcomes, adverse events, pharmacokinetic measures, and changes in serum immunoglobulin. The named outcomes include seroconversion rates, complete response rate, time to first treatment, overall survival, progression-free survival, number of adverse events, lenalidomide pharmacokinetic parameters, and change in serum immunoglobulin. This range reflects different kinds of questions and measurement scales.

The secondary outcomes complement the primary antibody-response endpoint but do not replace it. An antibody measure addresses a vaccine-related immune response, while response status, time to treatment, progression, survival, and safety address other aspects of the trial. A pattern across these outcomes could help characterize the study more broadly, but the registry record does not provide enough posted numerical results in this record to describe a consistent direction across all secondary endpoints. The single detailed secondary result available should not be treated as a summary of all listed outcomes.

Secondary analyses commonly have less evidential weight than a prespecified primary analysis, particularly when many endpoints are examined. In general, testing many hypotheses increases the chance that some results appear noteworthy even when effects are absent. The registry record does not report a multiplicity strategy, hierarchy among the secondary outcomes, or whether analyses were adjusted. Thus unadjusted secondary results should be treated as exploratory descriptions unless a prespecified analysis plan establishes otherwise.

Differences in denominators across outcomes may also affect interpretation. The registry does not explain all analysis populations or missing-data rules. Secondary findings should therefore be considered outcome by outcome, with attention to the number of participants contributing data, the endpoint definition, and the uncertainty of each estimate. They should not be combined informally into a single conclusion about the treatment schedules.

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

• Seroconversion Rates
• Complete Response Rate
• Time to First Treatment
• Overall Survival
• Progression-free Survival
• Number of Adverse Events
• Pharmacokinetic (PK) Parameters of Lenalidomide
• Change in Serum Immunoglobulin

9. Statistical Interpretation

10. Statistical Methods Explained

Statistical methods help distinguish the observed response percentages from the uncertainty around their comparison. The primary outcome is binary: each participant either met the antibody-response definition or did not. A percentage describes the share meeting the definition in an arm, while a risk difference describes the subtraction of one arm's response proportion from the other's. The posted risk difference is 0.13 for Arm B relative to Arm A.

What does the confidence interval express?

In general, a confidence interval represents uncertainty in an estimate under the method used to construct it. Narrower intervals indicate greater precision; wider intervals indicate less precision. For this primary comparison, the interval runs from -0.085 to 0.345. Since zero is within that interval, the posted results are compatible with no difference as well as with differences in either direction. The interval also shows why the point estimate should not be treated as an exact or certain effect.

A confidence interval is not a guarantee that the true value falls within its endpoints, and it is not a range of individual participant outcomes. It describes uncertainty about a population-level comparison, subject to the statistical method and assumptions. The registry record does not report additional details of the method used to calculate the primary comparison interval.

What does the p-value mean?

In general, a p-value measures how unusual results at least as incompatible with a stated null hypothesis would be if that null hypothesis and the test assumptions held. The unadjusted p-value for the primary comparison is 0.24. It should not be interpreted as the probability that the null hypothesis is true, the probability that the observed result occurred by chance, or a measure of the size of a difference. A p-value also does not indicate whether a result is clinically important.

The term unadjusted matters because the registry lists multiple outcomes. When many outcomes or comparisons are examined, the chance of finding a small p-value somewhere can increase. Whether the investigators controlled for this issue, selected a primary comparison in advance, or made other adjustments is not reported in the registry record. The posted p-value should therefore be read as an unadjusted result rather than as a multiplicity-adjusted test.

Why use a risk difference?

In general, the risk difference expresses the contrast between two proportions on the original probability scale. It is directly tied to the endpoint's percentage-of-participants interpretation. A value of zero represents equal proportions; positive or negative values indicate the direction of the contrast according to the stated arm ordering. For this comparison, Arm B is contrasted with Arm A. The registry also includes relative measures, but the risk difference and its interval provide the principal direct description used in the posted comparison.

For a binary outcome, the number of participants meeting the endpoint and the denominator both matter. The primary response counts are 18 of 24.0 in Arm A and 22 of 25.0 in Arm B. The percentages alone do not convey all the information about how much data underlies each estimate. A small trial can produce substantial uncertainty even when the observed proportions differ.

Why can over-dispersion matter?

In general, over-dispersion means that observed variability is greater than a statistical model assumes. If a model underestimates variability, its standard errors may be too small and its confidence intervals too narrow. Over-dispersion is especially relevant to some count or clustered-data models; it is not automatically a feature of every binary endpoint. The registry record does not report an over-dispersion assessment or a model-based primary analysis, so it would be inappropriate to claim that it affected this result.

The primary endpoint is a participant-level binary response, and the registry presents arm percentages and an unadjusted comparison. It does not report the detailed test specification, covariate adjustment, handling of any clustering, or diagnostic checks. General statistical concepts can help explain possible methods, but cannot establish which procedures were used in this trial.

What can randomization establish?

In general, random assignment is intended to make treatment groups comparable with respect to both measured and unmeasured factors, on average. It supports a between-group comparison, but does not guarantee balance in a small trial, ensure complete outcome data, or remove uncertainty. The registry identifies allocation as randomized and the design as parallel, but does not describe sequence generation, concealment, or the specific analysis population. Those details are not reported in the registry record.

11. Confidence Intervals and Precision

The primary comparison is reported with a risk difference of 0.13 and a 95% confidence interval from -0.085 to 0.345. This interval is wide enough to include zero and values on both sides of zero. The point estimate therefore does not tell the full story: the posted data leave considerable uncertainty about the direction and size of the contrast.

In general, confidence intervals communicate precision. An interval that spans a broad range of plausible values gives less precise information than a narrow interval. The primary interval is a comparison interval, not a confidence interval for each arm's response percentage. The registry record does not report arm-specific confidence intervals for the primary outcome, so those should not be inferred from the comparison interval.

The primary denominators are 24.0 and 25.0 participants. With these group sizes, each observed response contributes to an estimate based on a relatively limited number of participants; the interval reflects uncertainty in the group contrast. The posted result should be read as a point estimate accompanied by an interval, not as a precise forecast for future participants or as proof of a particular effect.

The confidence level describes the long-run performance of the interval procedure under its assumptions; it does not mean there is a 95% probability that this particular interval contains the true value. The registry record does not report enough methodological detail to assess all assumptions underlying the interval calculation. Precision should therefore be judged from the posted range while recognizing that details of the analysis are not reported in the registry record.

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 planning figures are participants per arm, not total event counts. That distinction fits this primary endpoint, which is a binary response measured in participants. In general, a sample-size calculation asks how many participants a future study might need under stated assumptions; it does not describe the number actually enrolled in this trial.

The registry's planning illustration uses the observed effect as its reference and considers planning for 100%, 75%, or 50% of that observed effect. It assumes 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. These are assumptions for the posted planning illustration, not the original design assumptions for the trial; the trial's own sample-size justification is not reported in the registry record.

The 80% power column indicates the number of participants per arm the illustration estimates would be needed for an 80% chance of detecting the assumed effect under those assumptions, if the effect and model assumptions were correct. The 90% power column gives the corresponding planning number for a 90% chance. These are target power levels for a hypothetical design, not probabilities that the observed trial result is correct.

Planning for a smaller fraction of the observed effect requires more participants per arm in the illustration. That is a general feature of study planning: smaller differences are harder to distinguish from random variation. The figures are not observed power and should not be used to claim that the completed or ongoing trial had a particular chance of success. They also do not establish what sample size the investigators originally intended.

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

Worked calculation for this trial

1. Control proportion p₀ = 0.750; treatment proportion p₁ = 0.880; average p̄ = 0.815.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5491 = 1.0763.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5414 = 0.4556.
4. n = (1.0763 + 0.4556)² / (0.1300)² = 138.9, rounded up to 139 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 <- 0.75                          # control proportion
p1 <- 0.88                          # 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(1351896)
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 = 139 (80% power), 186 (90% power)
 75% of observed effect: n per arm = 265 (80% power), 354 (90% power)
 50% of observed effect: n per arm = 632 (80% power), 845 (90% power)
power.prop.test: 138.9 
Simulated power at n = 139 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.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and a broad set of secondary outcomes, including immune, disease-response, time-to-event, pharmacokinetic, and safety measures. Evaluating many outcomes creates a multiplicity concern: in general, the more statistical tests conducted, the greater the possibility that at least one result will appear notable by chance. The registry record does not report whether the investigators used a multiplicity adjustment, a hierarchy for testing, or another method to control the overall error rate. It also does not report an interim-analysis plan.

The primary comparison is labeled with an unadjusted p-value. That value should not be interpreted as if it had been adjusted for all outcomes or analyses. The registry lists 33 outcome measures and 0 reported analyses in its analysis count, while also displaying posted outcome results. The relationship between that analysis count and the displayed results is not explained in the registry record, so it should not be used to infer the complete analysis history.

Missing-data handling and analysis populations are also not reported in the registry record. The primary outcome denominators are 24.0 and 25.0, while the detailed secondary outcome has denominators of 16.0 and 20.0. The record does not explain why those secondary denominators differ, whether participants lacked measurements, whether any participants were excluded, or how missing observations were treated. No intention-to-treat, per-protocol, or other named population is specified in the posted record.

These omissions matter because the interpretation of percentages and comparisons depends on who was included and how incomplete data were handled. In general, analyses restricted to participants with available measurements can differ from analyses that retain all randomized participants under a prespecified missing-data approach. Without the applicable analysis plan and participant accounting, the posted results can be described, but the effect of missing data or exclusions cannot be assessed.

15. 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: lung infection (12.5%), neutrophil count decreased (8.3%), dehydration (8.3%), rash maculo-papular (8.3%), abdominal pain (8.0%).

The registry reports serious adverse events in 12 of 24 participants at risk in Arm A and 13 of 25 participants at risk in Arm B. It also reports other adverse events in 24 of 24 participants at risk in Arm A and 25 of 25 participants at risk in Arm B. The deaths field lists 0 for Arm A and 1 for Arm B. These counts describe the posted safety record; they do not establish that an event was caused by a study intervention.

The listed serious-event terms and percentages include lung infection at 12.5%, neutrophil count decreased at 8.3%, dehydration at 8.3%, rash maculo-papular at 8.3%, abdominal pain at 8.0%, and fever at 8.0%. The registry record does not specify in the listed terms whether these percentages refer to participants, events, an arm-specific denominator, or a pooled denominator. It also does not provide enough detail to determine overlap among terms or the timing and duration of events.

These figures should be read as counts and listed event frequencies, not as a formal comparison of safety between schedules. The record does not report an adjusted safety analysis or a causal attribution for these events.

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

The primary result describes the proportion of participants who met a prespecified antibody-response definition in each treatment-timing group. The observed proportions were higher in the sequential arm, and the reported risk-difference point estimate is positive for Arm B relative to Arm A. However, the comparison interval includes zero and extends in both directions, and the unadjusted p-value is 0.24. Taken together, these results do not provide a precise estimate of the direction or size of the difference.

The endpoint is an immune measurement. It does not by itself establish that vaccination prevented infection, altered the course of CLL/SLL, delayed the need for treatment, or changed survival. The registry lists those clinical outcomes separately. The antibody response can be interpreted as evidence about the measured immune outcome only, not as a substitute for other clinical endpoints.

The trial compares two schedules in a randomized phase II design, but the total registered enrollment is 49. The results are therefore specific to the participants and measurements represented in the record. Missing-data handling, analysis populations, and details of the original statistical plan are not reported in the registry record, limiting the ability to assess how representative or robust the posted estimates are.

The record lists the study as active, not recruiting, and gives a primary completion date. It does not establish from the status alone that every analysis is final or that all planned outcomes have complete results. The posted evidence should be read as a report of observed trial data with uncertainty, rather than as a conclusive verdict about either schedule or about treatment effects beyond the endpoint measured.

17. Why This Trial Matters Statistically

This trial raises a statistical question about timing: whether an antibody response differs when PCV13 is administered concurrently with lenalidomide or before lenalidomide begins. Because both arms include both interventions, the comparison is about sequencing rather than a simple treatment-versus-no-treatment contrast. That distinction is essential when interpreting the group results.

The study also illustrates why point estimates, uncertainty intervals, and endpoint meaning need to be read together. The observed response percentages and the risk-difference estimate offer a direct comparison, while the confidence interval indicates that the estimate is imprecise. A single percentage or p-value cannot convey all of that information. The primary outcome's immunologic definition also sets a boundary on what the result can say: it measures an antibody response, not a clinical outcome such as infection or survival.

The registry lists a range of secondary outcomes that could address further questions about disease response, time to treatment, survival, pharmacokinetics, and safety. Those questions are related but distinct, and multiplicity, incomplete reporting, and differences in analysis denominators affect how strongly secondary findings can be interpreted. The registry record does not report the full statistical plan needed to evaluate those issues comprehensively.

For biostatisticians and clinical researchers, the record is a useful example of separating the randomized design from the details needed to judge analysis quality. Randomization is important, but does not by itself resolve uncertainty, missing-data questions, multiplicity, or the clinical meaning of a surrogate immune endpoint. Transparent reporting of those elements is necessary for a fuller assessment.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The primary comparison is based on a total registered enrollment of 49, with primary endpoint denominators of 24.0 and 25.0. The confidence interval is broad and includes zero, limiting precision about the direction and size of the observed contrast. The registry record does not provide arm-specific confidence intervals for the primary response proportions.

The primary outcome is a laboratory-defined antibody response assessed up to 1 month. It does not directly measure infection, progression, time to first treatment, or survival. Those outcomes are listed separately, but the registry record does not provide enough numerical detail to assess their overall pattern or relationship to the primary result.

Important analytical details are not reported in the registry record, including the original sample-size justification, the prespecified analysis population, missing-data handling, detailed test specification, multiplicity control, and interim-analysis plan. The record also does not explain the differing denominators for the detailed secondary result or the denominator basis for each listed serious adverse-event percentage. Without these details, potential selection effects, analysis choices, and the impact of incomplete measurements cannot be evaluated.

The trial is randomized and parallel, but the registry does not describe the randomization procedure or allocation concealment. The posted primary p-value is unadjusted, and the record does not state whether other analyses were adjusted. The study status is active, not recruiting; that status alone does not establish that every outcome is fully reported or that the posted results represent the complete analysis record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Lenalidomide and Vaccine Therapy in Treating Patients With Early-Stage Asymptomatic Chronic Lymphocytic Leukemia or Small Lymphocytic Lymphoma — NCT01351896.
• Registry record last updated 2026-05-27; status last verified 2026-05.
• Results first posted 2025-08-22.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

NCT01351896 is a randomized, unmasked, parallel phase II study of concurrent versus sequential PCV13 and lenalidomide in people with early-stage, asymptomatic CLL/SLL and high-risk genomic features. The registry lists an enrollment of 49 and a status of active, not recruiting.

The primary endpoint is the proportion achieving the defined antibody response up to 1 month. The posted arm proportions are 75.0% and 88.0%; the risk difference is 0.13, with a 95% confidence interval from -0.085 to 0.345 and an unadjusted p-value of 0.24. The interval reflects substantial uncertainty about the comparison.

The record lists secondary outcomes and adverse events, but does not report several details needed for full statistical assessment, including missing-data methods, analysis populations, multiplicity control, and the original sample-size justification. The antibody endpoint should be distinguished from clinical outcomes such as disease progression or survival.