A Study to Evaluate the Efficacy and Safety of Reslizumab (0.3 or 3.0 mg/kg) as Treatment for Patients (12-75 Years of Age) With Eosinophilic Asthma: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Evaluate the Efficacy and Safety of Reslizumab (0.3 or 3.0 mg/kg) as Treatment for Patients (12-75 Years of Age) With Eosinophilic Asthma (NCT01270464), a randomized phase 3 study. The primary outcome is Change From Baseline In Forced Expiratory Volume In 1 Second (FEV1) Over 16 Weeks Using Mixed Model for Repeated Measures.

2. Clinical Question

The clinical question is framed around lung function, not around every possible benefit or risk of treatment. The primary measure was change from baseline in FEV1, analyzed repeatedly at scheduled visits during treatment. Positive changes from baseline indicate improvement in asthma control according to the registry’s endpoint description. The registry reports a placebo comparison for each dose, so the question concerns two treatment contrasts rather than a direct comparison between the doses. The record does not report a dose-to-dose statistical comparison.

3. Trial Design

This was a Phase 3, randomized, double-blind, placebo-controlled, parallel-group study with triple masking recorded in the registry. The study enrolled 315 participants and was listed as completed. The planned treatment period was 16 weeks. Participants were assigned to placebo, reslizumab 0.3 mg/kg, or reslizumab 3.0 mg/kg; each was administered intravenously once every 4 weeks for a total of 4 doses. The registry’s primary objective was to compare the reslizumab doses with placebo for improvement in lung function measured by change from baseline in FEV1.

The primary analysis used the full analysis set, defined in the record as randomly assigned participants who received at least one dose of study drug. The number analyzed includes participants who contributed at least once to the analysis. The reported analyzed group sizes were 103 for placebo, 101 for reslizumab 0.3 mg/kg, and 102 for reslizumab 3.0 mg/kg. These are analysis counts for the endpoint, not a description of every participant’s completion or follow-up.

Repeated FEV1 measurements were scheduled at baseline and Weeks 4, 8, 12, and 16. A mixed model for repeated measures was used to estimate the during-treatment average. The registry also lists secondary outcomes covering other pulmonary-function measures, asthma control and quality of life, symptom utility, short-acting beta-agonist use, and blood eosinophil count. The registry record does not report the original sample-size justification, detailed eligibility criteria, or a full protocol. The listed trial design therefore describes the recorded assignment, masking, treatment, analysis population, and outcome schedule without assuming details beyond the record.

4. Participant Flow and Accounting

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

Before assignment: Of the 1025 patients screened at 80 centers in 12 countries (Argentina, Belgium, Brazil, Canada, Colombia, Hungary, Israel, Mexico, Netherlands, Poland, Sweden, and the US), 315 patients met entry criteria at 68 centers and were considered to be eligible for enrollment.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full analysis set-all patients randomly assigned to treatment and treated with at least 1 dose of study drug. Number of participants analyzed includes those who contributed at least once to the analysis.

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: Randomized population

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline In Forced Expiratory Volume In 1 Second (FEV1) Over 16 Weeks Using Mixed Model for Repeated Measures, measured over Day 0 (baseline, pre-dose), Weeks 4, 8, 12 and 16.

The primary endpoint was change from baseline in forced expiratory volume in 1 second (FEV1), measured in liters. FEV1 is the volume of air a person can forcefully exhale in the first second of expiration, measured using a spirometer. It is used as a lung-function measure in asthma studies because it quantifies airflow during a standardized pulmonary function test. The registry defines a positive change from baseline as indicating improvement in asthma control.

Rather than relying on one follow-up measurement, the analysis used measurements at Weeks 4, 8, 12, and 16 to estimate the average during-treatment change. This repeated-measures approach uses the pattern of available measurements across visits, with the model accounting for the study factors and baseline information specified in the record. The reported endpoint is a model-based least-squares mean, not simply an arithmetic average of all participants’ observed changes.

FEV1 captures one aspect of asthma and should not be treated as a complete measure of symptoms, daily functioning, quality of life, or safety. Those topics appear among the listed secondary outcomes, but they are distinct from the primary lung-function question. The registry’s endpoint description does not state a threshold for a clinically meaningful difference in FEV1, so the numerical estimates alone do not establish how participants would experience a given change.

7. Results Posted in the Registry

• Reslizumab - 0.3 mg/kg: mean 0.24 versus 0.13 on control; difference 0.12 (95% CI -0.04 to 0.27), standardized effect d = 0.21; z-test p = 0.138.
• Reslizumab - 3.0 mg/kg: mean 0.29 versus 0.13 on control; difference 0.16 (95% CI 0.01 to 0.31), standardized effect d = 0.29; z-test p = 0.039.

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 Forced Vital Capacity (FVC) Over 16 Weeks Using Mixed Model for Repeated Measures

• 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:
  • Reslizumab - 0.3 mg/kg: mean 0.22 versus 0.17 on control; difference 0.05 (95% CI -0.12 to 0.22), standardized effect d = 0.08; z-test p = 0.583.
  • Reslizumab - 3.0 mg/kg: mean 0.30 versus 0.17 on control; difference 0.13 (95% CI -0.04 to 0.30), standardized effect d = 0.21; z-test p = 0.137.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Reslizumab - 0.3 mg/kg and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Reslizumab - 3.0 mg/kg and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Forced Expiratory Flow at 25% to 75% Forced Vital Capacity (FEF 25%-75%) Over 16 Weeks Using Mixed Model for Repeated Measures

• 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:
  • Reslizumab - 0.3 mg/kg: mean -0.11 versus -0.14 on control; difference 0.03 (95% CI -0.34 to 0.41), standardized effect d = 0.02; z-test p = 0.871.
  • Reslizumab - 3.0 mg/kg: mean 0.09 versus -0.14 on control; difference 0.23 (95% CI -0.14 to 0.61), standardized effect d = 0.17; z-test p = 0.218.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Reslizumab - 0.3 mg/kg and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Reslizumab - 3.0 mg/kg and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Asthma Control Questionnaire (ACQ) Over 16 Weeks Using Mixed Model for Repeated Measures

• 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:
  • Reslizumab - 0.3 mg/kg: mean -0.73 versus -0.49 on control; difference -0.24 (95% CI -0.58 to 0.11), standardized effect d = -0.19; z-test p = 0.175.
  • Reslizumab - 3.0 mg/kg: mean -0.85 versus -0.49 on control; difference -0.36 (95% CI -0.70 to -0.02), standardized effect d = -0.29; z-test p = 0.039.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Reslizumab - 0.3 mg/kg and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Reslizumab - 3.0 mg/kg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry lists secondary outcomes spanning additional measures of lung function, asthma control, quality of life, symptom utility, short-acting beta-agonist use, and blood eosinophil count. The detailed secondary results recorded in the posted trial information cover forced vital capacity (FVC), forced expiratory flow (FEF 25%-75%), and the Asthma Control Questionnaire (ACQ). Their sponsor-reported comparisons do not form a uniform pattern: some dose comparisons have confidence intervals excluding zero, while others do not. The secondary outcomes therefore add context but do not provide one consistent numerical signal across all measures.

These outcomes relate to the primary FEV1 result by examining other aspects of pulmonary function and asthma control. They are not substitutes for the primary endpoint, and their scales and units differ. The registry lists additional secondary outcomes, but results for the other listed measures are not reported in the registry record. The absence of those results from the record means the full set of secondary findings cannot be assessed from the posted information.

In general, secondary analyses are often interpreted more cautiously when many outcomes or contrasts are examined. Unless multiplicity is addressed, the chance of finding at least one apparently unusual result can rise across a collection of tests. The registry record does not report a multiplicity adjustment or a testing hierarchy for these results. As a result, individual secondary p-values should carry less weight than the prespecified primary analysis, and should be viewed as supportive or exploratory rather than as independent confirmation. The registry does not report enough detail to determine whether or how secondary outcomes were prioritized in the analysis plan.

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

• Change From Baseline in Forced Vital Capacity (FVC) Over 16 Weeks Using Mixed Model for Repeated Measures
• Change From Baseline in Forced Expiratory Flow at 25% to 75% Forced Vital Capacity (FEF 25%-75%) Over 16 Weeks Using Mixed Model for Repeated Measures
• Change From Baseline in % Predicted Expiratory Volume In 1 Second (FEV1) at Week 16 and at Endpoint
• Change From Baseline in Asthma Control Questionnaire (ACQ) Over 16 Weeks Using Mixed Model for Repeated Measures
• Change From Baseline in Asthma Quality of Life Questionnaire (AQLQ) at Week 16 or at Last Observed Value
• Change From Baseline in Asthma Symptom Utility Index (ASUI) Over 16 Weeks Using Mixed Model for Repeated Measures
• Change From Baseline in Short-Acting Beta-Agonist (SABA) Use Over 16 Weeks Using Mixed Model for Repeated Measures
• Change From Baseline in Blood Eosinophil Count Over 16 Weeks Using Mixed Model for Repeated Measures

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous: each participant has a measured FEV1 value, and the analysis estimates change from baseline. The registry reports least-squares means with standard errors for each group. A least-squares mean is a model-based group estimate adjusted for the factors included in the model; it need not equal the raw arithmetic mean. A standard error describes the estimated uncertainty of a mean estimate. It is not the same quantity as the spread of individual participant measurements.

Why use a repeated-measures model?

The primary outcome was measured repeatedly at Weeks 4, 8, 12, and 16. A mixed model for repeated measures (MMRM) analyzes the pattern of measurements across visits rather than selecting only one visit or treating all observations as independent. In general, measurements from the same participant tend to be related. A repeated-measures model represents that within-participant structure and can use available observations across visits under the model’s assumptions. The registry says patient was included as a random effect for repeated measurements.

The recorded fixed effects were treatment, stratification factors, sex, visit, and the treatment-by-visit interaction. Height and baseline value were included as covariates. In general, adjustment can account for prespecified characteristics and improve estimation of treatment differences, while the interaction allows the modeled treatment contrast to vary by visit. The registry identifies these model terms, but does not report all implementation details, such as the covariance structure used for repeated measurements or the method for handling missing outcome values.

What do the reported contrasts represent?

The registry reports mixed-model mean differences in final values for each reslizumab dose against placebo. For this continuous outcome, a mean difference expresses the estimated separation between groups in the outcome’s units, liters. The sponsor’s confidence intervals and p-values accompany those model-based contrasts. Because the registry reports a discrepancy between the sponsor’s own analysis and the simple recalculations, the sponsor’s mixed-model estimates are the appropriate results to foreground.

The simple recalculations use the posted group means and standard errors to produce unadjusted comparisons and approximate standard deviations. They do not reproduce the MMRM, its covariate adjustment, or the repeated-measures structure. Their intervals and unadjusted p-values are therefore useful as a separate, transparent check based on summary statistics, not as an alternative version of the sponsor’s adjusted analysis. The record marks the standard-deviation approximation, and these calculations should not be mistaken for participant-level analyses.

How should p-values and intervals be read?

In general, a p-value measures how unusual data at least as incompatible with a null hypothesis would be if the null model and analysis assumptions held. It does not state the probability that the null hypothesis is true, and it does not quantify the size or practical importance of a difference. A confidence interval gives a range of estimates compatible with the data and model at its stated confidence level. Its width reflects precision: wider intervals allow a broader range of plausible values than narrower ones. Neither measure removes uncertainty arising from model assumptions, outcome selection, or incomplete reporting.

The sponsor’s primary results include 95% confidence intervals and p-values. The recalculated comparisons are explicitly unadjusted; their p-values are not adjusted for testing multiple outcomes or comparisons. The registry record does not report whether a multiplicity procedure was used for the primary or secondary analyses. That absence matters because a collection of tests can increase the chance of at least one small p-value arising by chance when all null hypotheses hold. This is a general statistical concern, not evidence that any particular registry result is false.

What is the analysis population?

The registry defines the full analysis set as all randomly assigned participants who received at least one dose of study drug. The number analyzed includes people who contributed at least once to the endpoint analysis. This definition is important: it does not by itself establish that all randomized participants contributed measurements at every visit, nor does it state how missing measurements were handled. The record does not report the detailed missing-data assumptions or sensitivity analyses for the primary endpoint.

These methods explain what the reported estimates summarize and why the sponsor’s model-based analysis differs from the simple recalculation. They do not establish that model assumptions were met; diagnostics or further details needed to assess those assumptions are not reported in the registry record.

11. Confidence Intervals and Precision

The sponsor’s primary comparison for reslizumab 3.0 mg/kg was 0.160 liters, with a 95% confidence interval from 0.060 to 0.259. For 0.3 mg/kg, the reported difference was 0.115 liters, with a 95% confidence interval from 0.016 to 0.215. These intervals quantify uncertainty in the sponsor’s model-based contrasts under that analysis. Both intervals exclude zero, but the registry does not report a threshold that would define a clinically important difference.

The simple recalculations yield different intervals: -0.037 to 0.269 for 0.3 mg/kg, and 0.008 to 0.312 for 3.0 mg/kg. The interval for the lower dose includes zero, while the higher-dose recalculation interval is above zero. These recalculations are unadjusted and do not replicate the sponsor’s repeated-measures model. Since the record flags a discrepancy, the sponsor’s own analysis takes precedence; the recalculated intervals should be read as approximate comparisons from posted summary statistics, not as the principal trial inference.

In general, an interval’s width indicates precision, while its location indicates the direction and range of estimated differences. An interval that includes zero is compatible with no difference as well as with effects in either direction within its limits; it does not prove that there is no difference. An interval excluding zero does not by itself establish clinical importance or eliminate concerns about multiplicity and analysis assumptions. The observed estimates and intervals also do not show the distribution of individual responses. They summarize group-level uncertainty and should be interpreted for the population and time frame analyzed.

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 estimates are planning illustrations based on the observed effect, not the original trial’s design calculation. For these continuous-outcome comparisons, the figures are participants per arm, not total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning row uses the stated fraction of the observed effect as the effect to detect. The trial’s original sample-size assumptions and justification are not reported in the registry record.

The 80% power column means the estimated number of participants per arm under those assumptions for an analysis with an 80% chance of rejecting the null hypothesis if the specified effect were the true effect. The 90% power column uses a higher target chance of detecting that specified effect. These are prospective design calculations under assumptions, not guarantees about what a study will find. This is not observed power.

Rows that plan for 100%, 75%, or 50% of the observed effect illustrate how the target effect changes the planning estimate. Smaller effects require more participants to detect with the same target power and significance level. The estimates depend on the observed effect and the planning assumptions, so they should not be read as a recommendation for a future study without considering its design, outcome variability, analysis plan, and other requirements. They also do not alter the interpretation of the actual trial results or provide evidence that a particular effect is clinically meaningful.

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 = 0.116; pooled standard deviation σ = 0.558.
2. n = 2 × (1.96 + 0.842)² × 0.558² / 0.116² = 363.2, rounded up to 364 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 <- 0.116                      # observed difference in means
sigma <- 0.557966272890368                     # 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(1270464)
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 = 364 (80% power), 487 (90% power)
 75% of observed effect: n per arm = 646 (80% power), 865 (90% power)
 50% of observed effect: n per arm = 1,453 (80% power), 1,945 (90% power)
power.t.test: 364.2 
Simulated power at n = 364 per arm: 0.800 (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

The registry records sponsor analyses using mixed models for the primary endpoint. For reslizumab 3.0 mg/kg versus placebo, the reported mean difference in final values was 0.160 liters, with a 95% confidence interval from 0.060 to 0.259 and p = 0.002. For reslizumab 0.3 mg/kg versus placebo, it was 0.115 liters, with a 95% confidence interval from 0.016 to 0.215 and p = 0.024.

The simple recalculations from the posted means and standard errors are not identical. They use unadjusted summary-statistic comparisons and do not reproduce the model’s repeated measurements or covariate adjustment. The record explicitly flags a discrepancy. Accordingly, the sponsor’s own analysis takes precedence for interpreting the trial’s reported primary comparisons; the recalculations are approximate checks and should not be presented as competing primary findings. The registry does not explain the source of the differences or provide further detail that would resolve them.

This distinction applies to secondary results as well: where sponsor model results are recorded, they are not interchangeable with the simple recalculated comparisons. Neither analysis alone addresses every uncertainty, including multiplicity and missing-data handling, which are not fully described in the registry record.

15. Multiplicity, Missing Data and Analysis Populations

The study reports one primary outcome and multiple secondary outcomes, with comparisons of each reslizumab dose against placebo. When several hypotheses are tested, the overall chance of a false positive can increase if each test is interpreted independently at the same significance level. In general, multiplicity procedures can control that risk by adjusting thresholds, confidence intervals, or the testing sequence. The registry record does not report whether a multiplicity adjustment, hierarchical testing strategy, or other control was used for the primary comparisons or secondary outcomes. The posted p-values should therefore be read with that reporting gap in mind; it cannot be assumed that they are adjusted.

The endpoint analysis population is described as randomly assigned participants who received at least one dose, with analyzed counts including those who contributed at least once. The record does not say that every participant had complete measurements at every visit. It also does not report the detailed method for handling missing repeated measurements, the assumptions made about why measurements were missing, or sensitivity analyses assessing the effect of those assumptions. MMRM can use available repeated observations under specified assumptions, but the registry record does not establish which assumptions were used or whether they were examined.

The trial’s original sample-size justification, intended power, and detailed statistical analysis plan are not reported in the registry record. The planning illustrations based on observed effects are not a substitute for those original design details. The record also does not report whether interim analyses were planned or conducted. These omissions limit assessment of how the analyses were selected and how robust the results are to alternative assumptions. They do not by themselves show that the analyses were inappropriate; they identify information that is not available in the registry record.

16. 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: asthma (2.9%), pneumonia (1.0%), sinusitis (1.0%), rib fracture (1.0%), road traffic accident (1.0%).

The registry reports serious adverse events in 1 participant at risk of 105 in the placebo group, 0 at risk of 103 in the reslizumab 0.3 mg/kg group, and 4 at risk of 103 in the reslizumab 3.0 mg/kg group. These are participant counts for the reported serious adverse event category. The record lists asthma at 2.9% and pneumonia, sinusitis, rib fracture, road traffic accident, and acute myocardial infarction at 1.0% each among the top serious adverse event terms.

These counts describe events recorded during the study; they do not by themselves establish that treatment caused an event or that the groups differ statistically. The registry does not report deaths for these groups, so death counts are not reported in the registry record. Other adverse events were reported in 28 participants at risk of 105 with placebo, 20 at risk of 103 with reslizumab 0.3 mg/kg, and 28 at risk of 103 with reslizumab 3.0 mg/kg. The record does not provide a formal comparative safety analysis here, and the counts should be interpreted alongside the limited study period and the full safety reporting.

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

The primary result is an estimate of the average difference in FEV1 over the study’s treatment period between each reslizumab dose and placebo among participants included in the endpoint analysis. The sponsor’s mixed-model analysis reported positive mean differences for both dose comparisons, with 95% confidence intervals above zero. Those estimates describe the observed data under the recorded analysis model. They are not a direct comparison between the two reslizumab doses, and the registry does not report such a test.

The endpoint is a measure of lung function, not a complete account of asthma control or a participant’s overall experience. It does not establish what happened after the 16-week period, and the registry record does not report longer-term outcomes. A group average also does not indicate that every participant experienced a similar change. The record does not specify a clinically meaningful FEV1 threshold, so statistical evidence of a difference should not be equated with a judgment about the importance of that difference to patients.

The secondary results address other outcomes, but multiple testing and incomplete reporting complicate their interpretation. The registry does not report a multiplicity plan, and results for all listed secondary outcomes are not recorded. Safety counts provide descriptive information rather than proof of causation or a definitive comparison of risk. Missing-data methods, sensitivity analyses, and other protocol details are not reported in the registry record.

Overall, the posted data support a description of the sponsor-reported model estimates and their uncertainty for the primary endpoint. They do not, on their own, settle questions about individual response, longer-term outcomes, clinical importance, generalizability beyond the analyzed population, or the completeness of the analysis assumptions. Interpretation should distinguish the trial’s recorded model-based results from the simpler recalculations and recognize that the sponsor analysis takes precedence where the two differ.

18. Why This Trial Matters Statistically

This study illustrates why statistical interpretation depends on more than a group mean or a p-value. The endpoint was measured repeatedly, and the sponsor used a mixed model that incorporated treatment, visit, their interaction, stratification factors, sex, height, baseline value, and participant-level repeated measurements. A simple comparison reconstructed from summary statistics does not reproduce that analysis. The registry’s explicit discrepancy flag makes the distinction especially important: the model-based results are the sponsor’s reported analyses, while recalculations are approximate and unadjusted.

The study also shows why precision and analysis scope matter. Confidence intervals communicate a range of estimates compatible with the model and data, while the endpoint itself covers one dimension of asthma-related health. Statistical differences in a lung-function measure do not automatically establish clinical importance, patient-level benefit, durability, or a favorable overall benefit-risk balance. The registry does not report a threshold for clinical importance or longer-term results.

Finally, the record lists numerous secondary outcomes but does not report multiplicity handling, missing-data details, or all secondary results. Those gaps limit how strongly multiple findings can be combined into a broad narrative. Keeping the primary model results, approximate recalculations, secondary evidence, and descriptive safety counts distinct is a useful statistical practice when reading a randomized trial registry.

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.

Several trial-specific limitations of interpretation arise from the registry record. The sponsor’s reported primary contrasts differ from the simple recalculations based on posted group summary statistics, and the record does not explain the discrepancy. The sponsor’s model-based results take precedence, but the lack of a reconciliation means the recalculated values should not be used to replace or independently validate the official analysis.

The registry describes the repeated-measures model terms but does not report the covariance structure, model diagnostics, detailed missing-data method, or sensitivity analyses. The analysis population requires at least one dose and at least one contribution to the endpoint analysis; the record does not clarify the extent of missing measurements across visits. The original sample-size justification, interim analysis information, and detailed statistical analysis plan are also not reported in the registry record.

Interpretation is further limited by the absence of a reported multiplicity strategy for the primary contrasts and multiple secondary outcomes. Results for all listed secondary outcomes are not reported in the registry record. The record also does not provide a clinically meaningful threshold for the primary FEV1 measure or longer-term outcomes beyond the 16-week treatment period. Safety reporting is descriptive in the registry record recorded here, without formal comparative analyses or death counts. These limitations identify boundaries of the available record; they do not establish that the underlying analyses were invalid.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study to Evaluate the Efficacy and Safety of Reslizumab (0.3 or 3.0 mg/kg) as Treatment for Patients (12-75 Years of Age) With Eosinophilic Asthma — NCT01270464.
• Registry record last updated 2016-06-06; status last verified 2016-04.
• Results first posted 2016-06-06.
• 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

This completed Phase 3 study randomized 315 participants with eosinophilic asthma to placebo or intravenous reslizumab at 0.3 mg/kg or 3.0 mg/kg, administered once every 4 weeks for a total of 4 doses. The primary endpoint was change from baseline in FEV1 over 16 weeks, analyzed with a mixed model for repeated measures.

The sponsor’s reported mean differences versus placebo were 0.115 liters for 0.3 mg/kg and 0.160 liters for 3.0 mg/kg, with 95% confidence intervals above zero. Simple unadjusted recalculations differ from those sponsor analyses, and the registry flags the discrepancy; the sponsor’s analysis takes precedence. Secondary outcomes cover additional pulmonary-function and asthma-related measures, but the registry does not report results for all listed outcomes or a multiplicity strategy. Serious adverse event counts are recorded descriptively, while deaths are not reported in the registry record.