Efficacy and Safety of SUBLIVAC Phleum for Immunotherapy of Grass Pollen-Allergy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of SUBLIVAC Phleum for Immunotherapy of Grass Pollen-Allergy (NCT02556801), a randomized phase 2 study. The primary outcome is Mean Total Symptom Score (TSS) After 10 Months of Treatment (Visit 6) Compared to Placebo.

2. Clinical Question

The study asked whether sublingual immunotherapy with SUBLIVAC FIX Phleum was associated with different Total Symptom Scores (TSS) after 10 months than placebo in people with grass pollen allergy and IgE-mediated seasonal allergic rhinoconjunctivitis. Its broader stated purpose was to assess safety and tolerability, look for a dose-response signal using grass-pollen challenges in an Environmental Exposure Chamber (EEC), and estimate a minimum effective dose.

The randomized, parallel-group design compares participants assigned to different treatments. The clinical question is therefore about differences between group summaries at the specified assessment, not about whether every participant improved or how an individual would respond.

3. Trial Design

This was a phase 2, randomized, quadruple-masked, parallel-group, placebo-controlled study. The official title identifies it as a single-center study. The registry record reports enrollment of 168 participants and four treatment groups: placebo and three SUBLIVAC FIX Phleum concentrations. The record marks the study completed.

The arm descriptions report that 42 subjects received placebo, 42 received 10,000 AUN/ml, 40 received 40,000 AUN/ml, and 40 received 80,000 AUN/ml. Each group used sublingual drops, with a described gradual increase to 5 drops per day followed by maintenance treatment during 10 months. The primary endpoint was assessed after 10 months, at visit 6, using an EEC grass-pollen challenge.

The primary efficacy population is described as an intention-to-treat population comprising randomized subjects who received at least one dose and had at least one post-baseline primary-endpoint measurement. The posted primary results list 40 participants in the placebo group, 35 in the 10,000 AUN/ml group, 38 in the 40,000 AUN/ml group, and 37 in the 80,000 AUN/ml group. These are the counts associated with the posted primary endpoint summaries; the registry record does not explain the differences between those counts and the arm-description counts.

The registry lists eight secondary outcome measures among 11 outcome measures overall and 61 analyses. Secondary measures include symptom scores at different visits, a combined symptom and medication score during grass pollen season, and immunoglobulin measures. Details of the original sample-size justification, the full statistical analysis plan, and any interim analyses are not reported in the registry record.

4. Participant Flow and Accounting

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

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The Intention-to-Treat population (ITT) includes all randomized subjects who received at least one dose of the study drug and for whom at least one post-baseline measurement for the primary efficacy endpoint was available.

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 Mean Total Symptom Score (TSS) After 10 Months of Treatment (Visit 6) Compared to Placebo, measured over 10 months after treatment start (baseline - Visit 2).

The primary endpoint is the mean Total Symptom Score (TSS) after 10 months of treatment, at visit 6. For each participant, the score was calculated as the average of available TSS measurements taken from 1 to 6 hours after the start of the EEC challenge at that visit. The score adds ratings for eight nasal and non-nasal symptoms: rhinorrhea, congestion, sneezing, itchiness, itchy or gritty eyes, tearing or watery eyes, red or burning eyes, and ear or palate itching.

Each symptom is rated on a scale from 0 to 3, from none to severe, and the total score ranges from 0 to 24. A higher score indicates more severe symptoms. The registry description says a negative change from baseline was expected to reflect reduced symptoms, and a more negative change was considered a better outcome. The primary outcome summaries, however, are mean scores at visit 6; the registry also reports change-from-baseline TSS as a secondary outcome.

An EEC challenge provides a defined setting for recording symptoms following grass-pollen exposure. Using a prespecified symptom score gives the study a common numeric measure for comparing group averages. That makes it possible to describe both the direction and the uncertainty of observed between-group differences. It does not, by itself, establish how those score differences relate to day-to-day symptoms outside the challenge setting.

7. Results Posted in the Registry

• SP 10,000 AUN/ml: mean 8.06 versus 10.01 on control; difference -1.95 (95% CI -4.24 to 0.34), standardized effect d = -0.39; z-test p = 0.095.
• SP 40,000 AUN/ml: mean 8.19 versus 10.01 on control; difference -1.82 (95% CI -4.07 to 0.43), standardized effect d = -0.36; z-test p = 0.112.
• SP 80,000 AUN/ml: mean 7.69 versus 10.01 on control; difference -2.32 (95% CI -4.58 to -0.06), standardized effect d = -0.46; z-test p = 0.044.

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 Mean Total Symptom Score (TSS) After 10 Months of Treatment (Visit 6)

• 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:
  • SP 10,000 AUN/ml: mean -5.37 versus -3.45 on control; difference -1.92 (95% CI -4.21 to 0.37), standardized effect d = -0.38; z-test p = 0.100.
  • SP 40,000 AUN/ml: mean -5.24 versus -3.45 on control; difference -1.79 (95% CI -4.02 to 0.44), standardized effect d = -0.36; z-test p = 0.116.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SP 10,000 AUN/ml 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 SP 40,000 AUN/ml and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Mean Total Symptom Score (TSS) After 5 Months of Treatment (Visit 4)

• 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:
  • SP 10,000 AUN/ml: mean -3.00 versus -2.40 on control; difference -0.60 (95% CI -2.72 to 1.52), standardized effect d = -0.13; z-test p = 0.579.
  • SP 40,000 AUN/ml: mean -4.24 versus -2.40 on control; difference -1.84 (95% CI -3.92 to 0.24), standardized effect d = -0.39; z-test p = 0.083.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SP 10,000 AUN/ml 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 SP 40,000 AUN/ml and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Mean Total Nasal Symptom Score (TNSS) After 10 Months of Treatment (Visit 6)

• 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:
  • SP 10,000 AUN/ml: mean -2.76 versus -1.87 on control; difference -0.89 (95% CI -2.12 to 0.34), standardized effect d = -0.33; z-test p = 0.158.
  • SP 40,000 AUN/ml: mean -2.75 versus -1.87 on control; difference -0.88 (95% CI -2.09 to 0.33), standardized effect d = -0.32; z-test p = 0.153.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SP 10,000 AUN/ml 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 SP 40,000 AUN/ml and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes extend the primary symptom assessment to other visits and measures. They include TSS and Total Nasal Symptom Score at 5 and 10 months, combined symptom and medication scores during grass pollen season, and changes in serum specific IgE, IgG, and IgG4. The posted secondary results cover only some of the listed measures. Across the posted symptom-score summaries, mean changes are negative in the treatment and placebo groups, with the size of the change varying by outcome and visit.

This broad pattern is related to, but not independent of, the primary result. The primary endpoint is TSS after 10 months during an EEC challenge; secondary outcomes use other time points, symptom definitions, or biological measures. Agreement in direction across related symptom measures may provide context, but it does not amount to several independent replications. Secondary measures may also differ in how they were collected and analyzed.

Unadjusted secondary results carry less weight when many outcomes and comparisons are examined. The more hypotheses assessed, the greater the chance that some results may appear notable by chance, unless the analysis plan accounts for multiplicity. The registry record lists 11 outcome measures and 61 analyses, but does not report a complete multiplicity strategy or identify which secondary results were designated confirmatory. Therefore, individual secondary comparisons should be read as exploratory unless the sponsor’s analysis plan establishes otherwise. Their role is to add context and identify patterns for further study, not to replace the primary endpoint or settle the overall interpretation.

The registry record does not provide enough information to assess whether all planned secondary outcomes were reported, how missing values were handled for each outcome, or whether a hierarchy was used to control the overall error rate. Those omissions limit how strongly the secondary findings can be combined into a single conclusion.

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

• Change From Baseline in Mean Total Symptom Score (TSS) After 10 Months of Treatment (Visit 6)
• Change From Baseline in Mean Total Symptom Score (TSS) After 5 Months of Treatment (Visit 4)
• Change From Baseline in Mean Total Nasal Symptom Score (TNSS) After 10 Months of Treatment (Visit 6)
• Change From Baseline in Mean Total Nasal Symptom Score (TNSS) After 5 Months of Treatment (Visit 4)
• Mean Combined Symptom and Medication Scores (CSMS) During the Grass Pollen Season.
• Change From Baseline in Serum Specific Immunoglobulin (IgE) Levels After 5 Months (Visit 4) and 10 Months (Visit 6) of Treatment
• Change From Baseline in Serum Specific Immunoglobulin (IgG) Levels After 5 Months (Visit 4) and 10 Months (Visit 6) of Treatment
• Change From Baseline in Serum Specific Immunoglobulin (IgG4) Levels After 5 Months (Visit 4) and 10 Months (Visit 6) of Treatment

9. Statistical Interpretation

10. Statistical Methods Explained

Continuous outcome and group means. TSS is a continuous score, calculated by adding ratings across eight symptoms. The posted primary summaries are least-squares means with standard errors. A mean describes the central level of the score in a group; a standard error describes uncertainty in estimating that mean. It is not a measure of the range of individual participants’ scores. The registry record does not report the full model specification used to obtain the least-squares means.

Between-group contrasts. A treatment effect is expressed as a difference between an active-dose group and placebo. A negative estimate means the active-dose group’s reported mean was lower than placebo’s, consistent with the score’s direction: higher scores represent more severe symptoms. A contrast describes a difference between group averages, not a change that must have occurred for each participant. The sponsor reports treatment effects from its analyses. The recalculated contrasts are simple, unadjusted estimates based on posted summary statistics and approximate variability.

Uncertainty intervals. A confidence interval gives a range of values compatible with the data and the assumptions of the analysis. A wider interval indicates less precision than a narrower one. When an interval includes zero, the data are compatible with no mean difference as well as with differences in either direction at the interval’s stated confidence level. When it does not include zero, the range of values represented by that interval lies on one side of zero. This interpretation does not establish clinical importance. The sponsor reports 90% confidence intervals for the pairwise treatment effects. The recalculated intervals are approximate; the registry-derived summaries do not specify their confidence level, so they should not be treated as substitutes for the sponsor’s intervals.

Standard errors and approximate variability. The group summaries provide standard errors rather than standard deviations. The recalculations infer approximate pooled standard deviations from those standard errors and group sizes, then use them to make unadjusted comparisons. This is a simplification: it does not recreate a more complex model, covariate adjustment, repeated-measures structure, or any prespecified missing-data procedure that the sponsor may have used. The registry record does not report sufficient analysis details to verify those features. As a result, the recalculated p-values and intervals are useful as checks on the posted summaries but should not be elevated over the sponsor’s reported analyses.

p-values. A p-value measures how compatible the observed data are with a specified null hypothesis under the assumptions of the test. It is not the probability that the null hypothesis is true, nor does it measure the size or importance of an effect. The sponsor reports an overall MCP-Mod test with p = 0.057. It also reports pairwise treatment effects and 90% intervals, without pairwise p-values in the primary results. The recalculated comparisons include unadjusted p-values. Because they do not account for the full analysis plan or multiplicity across several comparisons, those recalculated values need cautious interpretation.

MCP-Mod and dose-response. MCP-Mod is the named method for the sponsor’s reported overall test across placebo and the three active-dose groups. In general, dose-response methods assess whether results across ordered dose groups are consistent with a modeled relationship between dose and outcome. A test statistic and p-value summarize evidence against the test’s null hypothesis under the selected model. The registry record does not report which candidate dose-response models, selection procedures, or multiplicity adjustments were used, so the details of this result cannot be independently reconstructed from the record.

Why over-dispersion can matter, in general. If observed variability is greater than assumed by a statistical model, standard errors may be too small and intervals too narrow; this is called over-dispersion in settings where it applies. TSS is analyzed as a continuous measure in these results, and the registry does not identify an over-dispersion issue or a particular correction. This general concept should not be read as a claim about the trial’s data.

Planning illustrations. The planning estimates use the observed effect as a reference and calculate participants per arm for 80% or 90% power under the stated assumptions. In general, power is the probability that a study would detect an effect of a specified size under a particular design and model if that effect were present. Planning numbers are prospective illustrations. They do not describe the power of the completed study, and the original design assumptions and sample-size justification are not reported in the registry record.

11. Confidence Intervals and Precision

The sponsor’s primary pairwise estimates are accompanied by 90% confidence intervals. For 10,000 AUN/ml, the treatment effect is -1.96, with a 90% interval from -3.89 to -0.03. For 40,000 AUN/ml, it is -1.83, with an interval from -3.72 to 0.06. For 80,000 AUN/ml, it is -2.33, with an interval from -4.23 to -0.43. Each interval includes a range of plausible treatment-effect values under the sponsor’s model, rather than identifying a single exact difference.

The interval for 40,000 AUN/ml includes zero, while the intervals for the other two dose comparisons do not. The endpoints of the 10,000 AUN/ml interval are close to zero, so the estimate’s direction is not separated from zero by a wide margin. These features help describe statistical precision, but the registry record does not report a threshold for a clinically meaningful TSS difference. Consequently, statistical separation from zero should not be equated with a judgment about clinical importance.

The recalculated estimates have different approximate intervals, reflecting the simplified method and reconstructed variability. Those calculations do not reproduce the sponsor’s reported model, and the sponsor’s own analysis takes precedence. More generally, an interval is informative only in light of its method, confidence level, assumptions, and endpoint definition. The sponsor’s 90% intervals are not directly interchangeable with intervals calculated under a different procedure or confidence level.

The group standard errors and the width of the reported intervals also indicate that the estimates remain uncertain. Point estimates can be compared in direction and magnitude, but small differences between dose-group estimates should not be overinterpreted. The overall MCP-Mod p-value of 0.057 adds a separate summary of the sponsor’s dose-response analysis; it does not remove the uncertainty around individual pairwise effects.

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 for these continuous-outcome comparisons, not total events. They use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The original trial’s sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm under which a study would have an 80% chance of detecting the chosen effect if that effect were present and the planning assumptions held. The 90% power column gives the corresponding illustration for a 90% chance. For example, for the 80,000 AUN/ml comparison, planning for 100% of the observed effect gives 75 participants per arm for 80% power and 100 for 90% power. Planning for 75% of that observed effect gives 133 and 178 participants per arm, respectively; planning for 50% gives 299 and 399.

Smaller effects require more participants to achieve the same target power, because they are harder to distinguish from the background variation. The illustration is based on the observed effect in this study, so it should not be treated as a guarantee that a future study would have the same effect or variability. These numbers are not observed power; they are planning illustrations under stated assumptions, not a retrospective measure of how likely the completed study was to detect an effect.

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 = -1.950; pooled standard deviation σ = 5.045.
2. n = 2 × (1.96 + 0.842)² × 5.045² / -1.950² = 105.1, rounded up to 106 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 <- -1.95                      # observed difference in means
sigma <- 5.04524053487983                     # 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(2556801)
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 = 106 (80% power), 141 (90% power)
 75% of observed effect: n per arm = 187 (80% power), 251 (90% power)
 50% of observed effect: n per arm = 421 (80% power), 563 (90% power)
power.t.test: 106.1 
Simulated power at n = 106 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 sponsor’s analysis is the primary reference for interpreting this endpoint. For the overall comparison across the groups, it reports an MCP-Mod test statistic of 1.823 and p = 0.057. For the pairwise comparisons, it reports treatment effects of -1.96, -1.83, and -2.33 for the 10,000, 40,000, and 80,000 AUN/ml doses, respectively, with 90% confidence intervals.

The recalculated comparisons are simple, unadjusted estimates derived from the posted group summaries and standard errors. They use approximate pooled variability and do not reproduce the sponsor’s analysis. The reported treatment effects are close in direction and magnitude to the recalculated contrasts, but some interval conclusions differ: the recalculated intervals include zero for 10,000 and 40,000 AUN/ml, whereas the sponsor’s 90% interval for 10,000 AUN/ml does not. Such differences can arise because the methods and interval constructions are not the same; the full sponsor model is not reported in enough detail to explain them precisely.

The registry record flags a discrepancy between the sponsor results and the recalculations. Accordingly, the sponsor’s own analysis takes precedence. The recalculations serve only as approximate checks on the displayed summaries and should not be used to override the reported sponsor analysis or to imply a separate definitive conclusion.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study assesses several endpoints, doses, time points, or treatment comparisons. In general, repeated testing increases the chance of obtaining at least one apparently notable result by chance. Approaches such as prespecified testing hierarchies or adjusted significance thresholds can address that issue, but the registry record does not report the sponsor’s full multiplicity strategy for the primary and secondary analyses. The presence of a named overall MCP-Mod test does not, by itself, establish how the sponsor handled every pairwise or secondary comparison.

The registry lists 11 outcome measures and 61 analyses. That number of analyses makes it particularly important to know which hypotheses were primary, which were secondary or exploratory, and whether adjustments were planned. Those details are not reported in the registry record. As a result, unadjusted p-values, especially among secondary analyses, should not be treated as if they represent a single isolated test.

The primary efficacy population is described as randomized participants who received at least one dose and had at least one post-baseline primary-endpoint measurement. This definition is narrower than all randomized participants because it requires both treatment exposure and a measured post-baseline outcome. The registry does not report how many randomized participants lacked a post-baseline measurement, why measurements were missing, or which imputation or modeling procedures were used to address missing data. The listed primary group counts therefore identify participants contributing to the posted endpoint summaries, but do not fully explain exclusions or missingness.

Nor does the registry record report enough detail to verify whether the primary model used all available repeated measurements, how it handled departures from model assumptions, or what sensitivity analyses were conducted. Without those details, readers cannot assess how robust the findings are to alternative missing-data assumptions or analysis specifications. The full statistical plan, including any interim analyses and stopping rules, is not reported in the registry record.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: cholecystitis (2.4%), spontaneous abortion (2.4%).

The registry reports serious adverse event counts by safety group. Among 42 participants at risk in the placebo group, 0 were reported with a serious adverse event; the same count was 1 among 42 at risk in the 10,000 AUN/ml group, 0 among 42 in the 40,000 AUN/ml group, and 1 among 42 in the 80,000 AUN/ml group. Deaths are reported as 0 in each group.

The registry also lists cholecystitis and spontaneous abortion among the top serious adverse event terms, each at 2.4%. The posted summary does not identify further group attribution for these terms. Serious adverse events are a specific category and should not be conflated with all adverse events. The record also reports other adverse events affecting 26 participants in the placebo group, 36 in the 10,000 AUN/ml group, 33 in the 40,000 AUN/ml group, and 36 in the 80,000 AUN/ml group.

These counts describe events recorded during the study; they do not establish that an event was caused by a treatment. The registry summary does not provide event-level narratives, exposure-adjusted rates, or enough detail to evaluate differences in event timing or severity. Safety counts should therefore be read descriptively and alongside the study’s limited size and duration.

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

The posted data describe average symptom scores in four randomized groups after 10 months of treatment and report a sponsor analysis of those comparisons. The active-dose group means at the primary assessment are lower than the placebo mean, and the sponsor’s pairwise estimates are negative. The sponsor’s overall MCP-Mod result is p = 0.057, and its pairwise confidence intervals vary in whether they include zero. These findings describe the observed endpoint and its statistical uncertainty; they do not justify a broad claim about what will happen for an individual participant.

The endpoint was measured during an Environmental Exposure Chamber challenge, using a score that combines eight nasal and non-nasal symptoms. It is not a direct measure of every aspect of allergic disease or of symptoms in all everyday settings. The record does not report a threshold for interpreting a TSS difference as clinically meaningful, so the size of the observed contrasts cannot be assigned a clinical importance category from these results alone.

The study also does not establish that every dose has a distinct effect or that the dose-response relationship follows a particular shape. The reported overall test and the pairwise comparisons are related analyses, and their interpretation depends on the statistical model and multiplicity approach. The registry record does not report enough detail to fully reconstruct those choices.

Safety counts are descriptive, and event counts alone do not establish causation. Secondary results provide additional context but are less decisive when many outcomes and analyses are reported without a stated multiplicity strategy. The results should therefore be understood as evidence about the posted study population, endpoint, and analysis—not as medical advice or a universal prediction.

18. Why This Trial Matters Statistically

This trial raises several useful statistical questions for clinical researchers. First, it compares three active doses with placebo while also testing for a dose-response signal. These are connected but not identical aims: an overall dose-response test and dose-specific placebo comparisons summarize different features of the data. Reporting both makes it important to understand the analysis plan and the role assigned to each test.

Second, the study uses a symptom score measured under a controlled pollen challenge. The score is built from multiple symptom ratings and then analyzed as a continuous outcome. Researchers must consider how the score is defined, when it is measured, and whether the resulting average is a useful summary of individual experiences. The registry gives a clear scoring range and direction, but not a clinical-importance threshold.

Third, the sponsor’s pairwise estimates and the simple recalculations are not identical in their uncertainty conclusions. This illustrates why summary-statistic checks can be informative without replacing a full analysis: model specification, variance estimation, and handling of repeated or missing measurements can affect estimates and intervals. The discrepancy makes it especially important to distinguish the sponsor’s reported results from unadjusted recalculations.

Finally, the registry lists many outcomes and analyses but does not report the full multiplicity plan or missing-data procedures. Those omissions constrain interpretation even when individual estimates are presented precisely. Transparent reporting of the statistical plan, analysis population, and sensitivity analyses would help readers evaluate how much confidence to place in the overall pattern.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record does not report the original sample-size justification or the assumptions used to plan the trial. The planning illustrations based on observed effects are not a substitute for those original design details. The record also does not report the full statistical analysis plan, including the model specification behind the least-squares means, the selected MCP-Mod models, or the procedure for handling multiplicity across outcomes and analyses.

The primary population definition requires treatment exposure and a post-baseline primary endpoint measurement. The primary results list fewer participants in some active groups than the arm descriptions report as having received treatment. The reasons for those differences and the amount or pattern of missing outcome data are not reported in the registry record. Without those details, the impact of missingness and exclusions cannot be assessed.

The recalculated comparisons rely on approximate variability reconstructed from standard errors and are unadjusted. They do not reproduce the sponsor’s model or its assumptions. The discrepancy between the sponsor’s reported analyses and the recalculations means the recalculations should remain secondary to the sponsor’s own results.

The posted primary endpoint is an EEC-based symptom score at one specified visit, and the record does not report a threshold for clinical importance. The registry describes the study as single-center, which limits what can be inferred about consistency across other settings. The record also does not provide detailed event-level safety information, and its secondary results do not establish how all planned measures or multiplicity were handled.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety of SUBLIVAC Phleum for Immunotherapy of Grass Pollen-Allergy — NCT02556801.
• Registry record last updated 2019-09-13; status last verified 2019-08.
• Results first posted 2019-09-13.
• 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

NCT02556801 is a completed phase 2 randomized, quadruple-masked, parallel-group study of SUBLIVAC FIX Phleum versus placebo in grass pollen-allergic participants. The registry reports enrollment of 168 and four groups: placebo and doses of 10,000, 40,000, and 80,000 AUN/ml.

The primary endpoint was mean TSS after 10 months, measured during an Environmental Exposure Chamber challenge. The sponsor reported an overall MCP-Mod result with p = 0.057 and pairwise treatment effects with 90% confidence intervals. Active-dose group means were lower than the placebo mean in the posted primary summaries, but the estimates remain uncertain and the sponsor’s results take precedence over approximate recalculations.

The registry does not report the full statistical analysis plan, original sample-size justification, multiplicity strategy, or missing-data procedures. Safety summaries report serious adverse events in 0 participants in placebo and 40,000 AUN/ml groups, and 1 participant in each other dose group; deaths are reported as 0 in all groups.