Efficacy and Safety of Grass Sublingual Tablet in Children and Adolescents (P05239 AM3)(COMPLETED): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of Grass Sublingual Tablet in Children and Adolescents (P05239 AM3)(COMPLETED) (NCT00550550), a randomized phase 3 study. The primary outcome is Participant Total Combined Symptom (TCS) Score Over the Entire Grass Pollen Season (GPS).

2. Clinical Question

3. Trial Design

This was a Phase 3, randomized, quadruple-masked, parallel-group study comparing SCH 697243 with matching placebo. The registry lists enrollment of 345 and a completed status. The study start is listed as 2007-11 and primary completion as 2009-09. These dates describe the registry record and do not provide the duration of treatment or the timing of each participant’s follow-up.

The study concerned children and adolescents aged 5 to <18 years with a history of grass-pollen-induced rhinoconjunctivitis, with or without asthma. The stated purpose was to investigate efficacy and safety of a grass sublingual tablet in that population. Randomization and masking can reduce some forms of bias, but their presence alone does not establish that every aspect of trial conduct or analysis was free from bias. The registry record does not report the allocation ratio, sequence-generation method, concealment procedure, or the identities of the masked groups.

The primary outcome was assessed over the entire Grass Pollen Season (GPS), from its start to its end. The Full Analysis Set consisted of randomized participants with at least one post-treatment diary entry. The outcome groups include 149 participants for SCH 697243 and 158 for placebo. The registry record does not report why the analysis-set counts differ from enrollment, nor does it provide a full account of participant flow or missing diary data.

Rescue treatments were listed, including loratadine, olopatadine, mometasone, albuterol, and fluticasone formulations. The outcome combines symptom and medication scores, so rescue medication use contributes to the endpoint rather than serving only as a separate clinical detail. The registry record does not report the original sample-size justification, trial-specific power assumptions, interim analyses, or a complete statistical analysis plan.

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 Full Analysis Set (FAS) population was comprised of all participants randomized with at least one post-treatment diary data entry.

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 Participant Total Combined Symptom (TCS) Score Over the Entire Grass Pollen Season (GPS), measured over From the Start of the GPS to the End of the GPS.

The primary endpoint was the participant’s average Total Combined Symptom (TCS) score over the entire Grass Pollen Season. It was calculated as the sum of the rhinoconjunctivitis Daily Symptom Score (DSS) and Daily Medication Score (DMS), averaged across the season. The posted description gives a scale from 0, indicating no symptoms and no rescue medication use, to 54, indicating the most severe symptoms and maximum rescue medication use. A higher score represents greater symptom severity and medication use.

The DSS reflects six rhinoconjunctivitis symptoms, with a stated range from 0 (best) to 18 (worst). The DMS reflects the scores associated with rescue medication use per day, with a stated range from 0 (no rescue medication use) to 36 (maximum use). Combining symptoms and medication use offers a seasonal summary that incorporates both reported symptoms and the use of rescue treatments. It is therefore not a pure symptom measure, and a group difference in TCS cannot by itself show which component contributed more.

A season-wide average can describe overall burden across the pollen season rather than a single day. It also compresses variation over time into one value, so it does not reveal when symptoms occurred, how they changed during the season, or how individual participants’ scores were distributed. The registry record identifies a mean endpoint and reports its standard error; it does not describe further details of diary completeness or the exact handling of missing daily entries.

7. Results Posted in the Registry

• SCH 697243: mean 4.62 versus 6.25 on control; difference -1.63 (95% CI -3.06 to -0.20), standardized effect d = -0.26; z-test p = 0.025.

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.

Participant Average Rhinoconjunctivitis Daily Symptom Scores (DSS) Over the Entire GPS

• 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:
  • SCH 697243: mean 3.71 versus 4.91 on control; difference -1.20 (95% CI -2.32 to -0.08), standardized effect d = -0.24; z-test p = 0.036.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for SCH 697243 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Participant Average Rhinoconjunctivitis Daily Medication Score (DMS) Over the Entire GPS

• 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:
  • SCH 697243: mean 0.91 versus 1.33 on control; difference -0.42 (95% CI -1.09 to 0.25), standardized effect d = -0.14; z-test p = 0.216.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SCH 697243 and the control. The interval gives the range of effects that remain compatible with the data.

Participant Average Weekly Rhinoconjunctivitis Quality-of-Life Questionnaire (RQLQ) Total Score Over the Entire GPS

• 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:
  • SCH 697243: mean 1.45 versus 1.77 on control; difference -0.32 (95% CI -0.64 to -0.00), standardized effect d = -0.26; z-test p = 0.049.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for SCH 697243 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes cover symptom scores, medication scores, and quality of life over the Grass Pollen Season. Taken together, their posted point estimates are lower in the SCH 697243 group than in the placebo group. The uncertainty and inferential results are not uniform across outcomes, so the pattern should be read as a set of related but distinct findings rather than as one simple conclusion.

These measures help contextualize the primary combined score because DSS and DMS are its component measures, while RQLQ captures quality of life. Their results can describe whether the direction of the primary comparison is reflected in separate symptom, medication, or quality-of-life summaries. They do not independently confirm the primary finding: the outcomes concern the same trial population and are likely related in what they measure. The secondary outcomes should not be treated as separate replications.

The registry reports sponsor analyses for the secondary outcomes and also gives simple unadjusted recalculations. As with the primary result, reported sponsor estimates should be distinguished from recalculated summary-statistic comparisons. The record flags a discrepancy for the primary analysis; it does not provide a basis for assuming that every secondary comparison used identical analysis details or that the posted outcomes exhaust all analyses conducted.

Unadjusted secondary results carry less weight because testing several outcomes creates more opportunities for apparently notable results, even when no adjustment is made for multiplicity. Whether the trial prespecified an adjustment, a hierarchy, or another approach is not reported in the registry record. The secondary outcomes are therefore best regarded as supportive context for the primary endpoint, with caution about treating any one secondary p-value as definitive evidence.

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

• Participant Average Rhinoconjunctivitis Daily Symptom Scores (DSS) Over the Entire GPS
• Participant Average Rhinoconjunctivitis Daily Medication Score (DMS) Over the Entire GPS
• Participant Average Weekly Rhinoconjunctivitis Quality-of-Life Questionnaire (RQLQ) Total Score Over the Entire GPS

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous and reported as a mean. A mean summarizes the central value of a group’s scores, while the standard error describes the estimated sampling uncertainty in that mean. Standard error is not the same as the spread of individual participant scores: it concerns uncertainty in an estimated group mean, whereas a measure such as a standard deviation describes participant-to-participant variability. The posted arm summaries report standard errors of 0.52 for SCH 697243 and 0.51 for placebo.

What does a mean difference represent?

The primary comparison is expressed as the mean difference, with the placebo group serving as the comparator. The estimate of -1.63 is the difference in the direction SCH 697243 minus placebo. A negative estimate therefore indicates a lower group mean in the SCH 697243 arm. Because the scale assigns higher scores to greater symptom severity and medication use, the direction of the estimate is interpretable on the endpoint’s stated scale. The estimate remains a contrast between group averages; it does not describe the size or direction of every participant’s change.

What does the reported ANOVA do?

The sponsor reports an analysis of variance (ANOVA) for the final values, with a mean difference, confidence interval, and p-value. In general, ANOVA is a statistical approach for comparing group means. The registry record does not give enough detail to establish the full model specification, whether any covariates were included, or how assumptions were assessed. The label ANOVA alone does not identify all analytical choices that may affect an estimate or its uncertainty.

For a simple recalculation, posted group means and standard errors can be used to estimate an unadjusted mean difference and its uncertainty. Such a calculation does not reproduce any unreported adjustment, model specification, or participant-level analysis used by the sponsor. Here the record explicitly flags a discrepancy between the recalculated summary-statistic analysis and the sponsor’s reported analysis. The sponsor’s own analysis takes precedence; the recalculation is best treated as a transparent secondary check, not as the trial’s official inferential result.

How should a p-value be understood?

A p-value describes how compatible the observed data are with a specified statistical model in which there is no group difference, subject to the assumptions of the analysis. It is not the probability that the treatment has no effect, and it does not measure the size or importance of the observed difference. The sponsor reports p =0.001 for the primary endpoint. The unadjusted recalculation reports p =0.025. Because these analyses do not agree and the registry marks a discrepancy, the sponsor’s result is the appropriate one to use when describing the reported primary analysis.

Statistical testing also depends on which outcomes and analyses were planned and how many were examined. The registry lists a primary endpoint and three secondary outcomes, but whether and how the trial’s testing plan accounted for multiple comparisons is not reported in the registry record. Without that information, the p-values for additional outcomes should be viewed as exploratory or supportive rather than as stand-alone confirmation.

What does randomization contribute?

Random allocation is intended to make treatment groups comparable in expectation, including on factors that are measured and factors that are not measured. Masking can reduce the chance that expectations affect care, reporting, or assessment. These design features support causal interpretation when implemented and maintained appropriately, but the registry record does not describe the allocation procedure, masking implementation, or assessment of masking. Design labels cannot substitute for those details.

The primary analysis population is defined as randomized participants with at least one post-treatment diary entry. That definition makes clear that participants without any such entry were not included in the stated Full Analysis Set, but it does not explain how incomplete diaries among included participants were handled. The missing-data method, sensitivity analyses, and reasons for missing outcome entries are not reported in the registry record. If missingness differs between groups or relates to symptom burden, estimates based on available records may be affected.

Why do the component outcomes matter?

The TCS is constructed from DSS and DMS. The secondary DSS outcome focuses on daily symptom scores, while DMS focuses on daily medication scores. These component measures can help describe what contributes to the combined endpoint, but they are related outcomes rather than independent replications. The weekly RQLQ provides a quality-of-life measure with a distinct interpretation. Together, the outcomes broaden description of the seasonal experience, while also increasing the importance of knowing the analysis plan and multiplicity approach.

In general, confidence intervals show a range of effect estimates that are compatible with the data and the statistical assumptions at the stated confidence level. They convey uncertainty about the group contrast and are often more informative about precision than a p-value alone. A confidence interval does not account for all possible bias, errors in measurement, or limitations in generalizability. For this trial, the sponsor-reported interval should be distinguished from recalculated intervals because the record documents that the analyses differ.

11. Confidence Intervals and Precision

The sponsor reports a 95% confidence interval for the primary mean difference from -2.60 to -0.66. The interval lies on the negative side of zero, consistent with the sponsor’s reported estimate of a lower mean TCS for SCH 697243 than for placebo. Its endpoints indicate that the data are compatible, under the analysis assumptions, with a range of group differences rather than a single exact value. The interval does not mean that a specific proportion of participants experienced a benefit, and it does not account for uncertainty arising from all possible biases.

The posted arm means are 4.62 for SCH 697243 and 6.25 for placebo, with standard errors of 0.52 and 0.51, respectively. Standard errors describe uncertainty in the estimated means, not the range of scores among participants. The registry does not provide standard deviations for these arm results in the primary outcome display. As a result, the displayed standard errors should not be read as describing individual score variability.

The simple unadjusted recalculation gives a different interval and p-value from the sponsor’s reported analysis. The registry flags this discrepancy, so the sponsor’s interval is the one to prioritize when discussing the trial’s reported finding. This difference is also a reminder that calculations based only on group summaries may not reproduce the sponsor’s analysis. The registry record does not report enough analytical detail to explain why the estimates of uncertainty differ.

Precision is separate from clinical importance. The interval quantifies statistical uncertainty under the model, but the registry record does not state a threshold for a clinically important difference in TCS. It therefore cannot establish from the interval alone whether the difference is large enough to be important to patients or caregivers. Nor does the interval describe how effects may vary across ages, symptom patterns, or other subgroups.

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 participants and not total events. The outcome is continuous, so the planning illustration gives participant counts per arm. It is a planning calculation based on the observed effect, not the trial’s original design justification. The trial’s own sample-size assumptions are not reported in the registry record.

The listed planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at the stated fraction of the observed effect. The 80% power column describes the planning count per arm for a design with an 80% chance of detecting the specified effect under those assumptions if that effect is truly present. The 90% power column describes the count per arm for a design with a 90% chance under the same assumptions. These are design probabilities, not guarantees for a particular study.

For the primary endpoint, the illustration lists 241 participants per arm for 80% power and 322 for 90% power when planning for 100% of the observed effect. For 75% of the observed effect, the listed figures are 428 and 573; for 50%, they are 962 and 1,288. The pattern illustrates that planning to detect a smaller effect requires more participants, because smaller group differences are harder to distinguish from sampling variability.

These values are not observed power. They are hypothetical planning illustrations that use the observed effect as an input and the stated simplifying assumptions. They do not show the trial’s achieved probability of detecting an effect, do not validate the original study design, and should not be interpreted as a recommendation for a future study without a separate design assessment.

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 = -1.630; pooled standard deviation σ = 6.380.
2. n = 2 × (1.96 + 0.842)² × 6.380² / -1.630² = 240.5, rounded up to 241 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 <- -1.63                      # observed difference in means
sigma <- 6.38001526284212                     # 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(550550)
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 = 241 (80% power), 322 (90% power)
 75% of observed effect: n per arm = 428 (80% power), 573 (90% power)
 50% of observed effect: n per arm = 962 (80% power), 1,288 (90% power)
power.t.test: 241.5 
Simulated power at n = 241 per arm: 0.803 (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 posted primary analysis reports an ANOVA mean difference of -1.63, a 95% confidence interval from -2.60 to -0.66, and p =0.001. The simple unadjusted recalculation from posted summary statistics gives the same point estimate but different uncertainty and a different p-value. The registry record explicitly flags this discrepancy.

When the sponsor’s analysis and a recalculation disagree, the sponsor’s own analysis takes precedence for describing the trial’s reported result. A summary-statistic recalculation cannot account for analysis details that are not present in the registry record, such as any adjustments or other model specifications. It is useful as a check on the direction and approximate group contrast, but it is not a substitute for the sponsor’s analysis.

The record does not report the detailed model specification or an explanation for the difference between analyses. It is therefore not possible to identify from the registry information alone why the confidence intervals and p-values differ. The clear reporting distinction is between the sponsor’s inferential result and the separately recalculated unadjusted result; they should not be blended into a single estimate of uncertainty.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies one primary endpoint and three secondary outcomes. Testing multiple outcomes can increase the chance of a false-positive result if each is interpreted as a separate confirmatory test without an appropriate strategy for multiplicity. A prespecified hierarchy or adjustment can address that issue, but the registry record does not report whether either was used, how the primary and secondary tests were ordered, or whether the reported p-values were adjusted.

The primary comparison is accompanied by a sponsor-reported ANOVA result and a simple unadjusted recalculation. The registry flags a discrepancy between them. This is distinct from multiplicity: the discrepancy concerns differences between analyses of the same endpoint, while multiplicity concerns interpretation across multiple outcomes or tests. Neither issue can be resolved by treating all posted p-values as interchangeable.

The Full Analysis Set included randomized participants with at least one post-treatment diary entry. This definition is reported for the primary outcome, but the registry does not provide a complete account of participants excluded from that set, reasons for missing entries, or the method used to handle partially completed diaries. The outcome counts differ from the enrollment figure, but the record does not explain the flow or the reasons for the differences. Missing-data methods and sensitivity analyses are not reported in the registry record.

Missing outcome data can affect interpretation if availability is related to treatment assignment or to the outcome itself. General statistical methods can make assumptions about the unobserved data, but those assumptions cannot be checked from group means alone. The registry record does not report the assumptions used, imputation methods, or robustness analyses.

The displayed population is therefore identifiable by its stated definition, but the available record does not provide enough detail to reconstruct the analysis population fully or assess the consequences of missingness. The original sample-size rationale, interim-analysis plan, detailed statistical analysis plan, and multiplicity procedures are not reported in the registry record. These omissions limit independent assessment of whether the posted analyses followed a prespecified confirmatory plan.

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: idiopathic thromnocytopenic purpura (0.6%), lymphadenitis (0.6%), pyelonephritis (0.6%), anaesthetic complications (0.6%).

The serious adverse event summary lists 176 participants at risk in the SCH 697243 group, with 0 affected, and 169 at risk in the placebo group, with 4 affected. These are registry counts of participants with serious adverse events, not counts of all individual events. The record lists idiopathic thromnocytopenic purpura, lymphadenitis, pyelonephritis, and anaesthetic complications among the top serious-event terms, each reported as 0.6%.

The record also lists other adverse events affecting 141 participants at risk in the SCH 697243 group and 121 in the placebo group. Those figures refer to the registry’s other-adverse-event summary and should not be combined with the serious-event counts. Deaths are not reported in the registry record. The listed serious-event terms are not enough to establish causation, comparative risk, or the full clinical context of an event.

These safety figures are descriptive. They do not by themselves establish whether differences between groups are meaningful, and the record does not provide a detailed event-by-event narrative, exposure-adjusted analysis, or a complete account of how events were assessed. The counts should be read alongside the trial’s size, duration, and reporting limitations rather than as a comprehensive safety evaluation.

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

The primary result describes a lower average seasonal combined symptom and medication score in the SCH 697243 group than in the placebo group. The sponsor’s reported mean difference is -1.63, with a 95% confidence interval from -2.60 to -0.66 and p =0.001. Because higher TCS values indicate greater symptom severity and rescue medication use, the direction of the reported contrast favors a lower score in the active-treatment group. This is a statistical description of the posted data, not medical advice or a conclusion about what any individual should use.

The endpoint combines symptom experience and rescue medication use. It does not isolate either component, and the average over the full pollen season does not show daily fluctuations or individual responses. The secondary outcomes provide related information, but they do not remove the limitations of an aggregate average or establish that the same pattern applies to every participant.

A confidence interval communicates uncertainty around the estimated group contrast under the analysis assumptions. It does not account for every possible source of error, including missing data, deviations from planned methods, or limits in reporting. The registry record flags a discrepancy between the sponsor’s analysis and an unadjusted recalculation, so the sponsor’s analysis is the primary inferential result to cite. Details needed to independently resolve the difference are not reported in the registry record.

The study’s randomized, masked design supports a comparative interpretation, but a registry summary is not a complete account of conduct, analysis, or applicability. The record does not provide the full protocol, trial-specific sample-size rationale, multiplicity strategy, or detailed missing-data methods. It also does not establish a threshold for a clinically important TCS difference. The posted result therefore describes the reported group-level statistical contrast and its stated precision, without settling every question about practical importance, subgroup effects, long-term outcomes, or safety.

18. Why This Trial Matters Statistically

This trial is statistically informative because it uses a season-wide endpoint that combines symptom reporting with rescue medication use. That construction makes the primary measure relevant to both symptom burden and medication-taking within the study, while also requiring care in interpretation: a difference in the combined score does not reveal which component drives the contrast.

The randomized, quadruple-masked, parallel-group design provides a framework for comparing assigned groups. The primary result is presented as a mean difference with an interval and a p-value, allowing readers to consider both direction and uncertainty rather than relying only on whether a test crosses a threshold. The posted secondary outcomes add context across symptoms, medication use, and quality of life, but their multiplicity and relationship to the primary endpoint matter when weighing the overall evidence.

The record also illustrates why analysis provenance matters. The recalculated summary-statistic result differs from the sponsor’s reported uncertainty and test result, and the registry flags that discrepancy. A transparent distinction between the sponsor’s analysis and an unadjusted recalculation avoids implying that a simple reconstruction is identical to the trial’s formal analysis.

Finally, the trial record makes clear which information is not available for independent statistical assessment, including the original sample-size rationale, multiplicity procedures, and missing-data handling. These details are important for judging how robustly the reported results answer the research question. The findings can be described precisely as posted while recognizing that registry-level results do not resolve every methodological or clinical question.

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 design the trial. The separate planning illustration is based on the observed effect and specified planning assumptions; it is not evidence of the trial’s original rationale. The record also does not report the trial’s interim-analysis plan or complete statistical analysis plan.

The sponsor’s primary ANOVA result differs from a simple unadjusted recalculation of the posted summaries. Although the registry flags this discrepancy and the sponsor’s analysis takes precedence, the information needed to explain the difference is not reported. This limits independent reproduction of the sponsor’s uncertainty estimates.

The primary population is defined as randomized participants with at least one post-treatment diary entry, but participant flow, reasons for missing diary data, and the approach to incomplete diaries are not reported in the registry record. These gaps limit assessment of whether the analysis could be affected by missingness. The record also does not report a multiplicity strategy for the primary and secondary outcomes, so secondary p-values should be interpreted cautiously.

The primary endpoint is a combined seasonal average of symptom and rescue medication scores. It does not show the component contribution, timing of symptoms, or distribution of effects among participants. The record does not state a clinically important difference threshold, which limits interpretation of practical importance. Further details on eligibility, treatment adherence, exposure, subgroup analyses, and the conduct of masking are not reported in the registry record.

Safety reporting is also limited to the posted summary counts and terms. The record does not provide a detailed event narrative or a full account of event assessment, and deaths are not reported in the registry record. These limitations mean the registry summary should not be treated as a complete account of trial methods, clinical experience, or safety.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety of Grass Sublingual Tablet in Children and Adolescents (P05239 AM3)(COMPLETED) — NCT00550550.
• Registry record last updated 2017-03-03; status last verified 2017-01.
• Results first posted 2012-09-07.
• 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

NCT00550550 is a completed Phase 3 randomized, quadruple-masked, parallel-group study of SCH 697243, a grass sublingual tablet, compared with matching placebo in children and adolescents aged 5 to <18 years with a history of grass-pollen-induced rhinoconjunctivitis, with or without asthma. The registry lists enrollment of 345.

The primary endpoint was average Total Combined Symptom score over the Grass Pollen Season, combining symptom and rescue medication scores. The sponsor reported a mean difference of -1.63, a 95% confidence interval from -2.60 to -0.66, and p =0.001. The registry flags a discrepancy between the sponsor analysis and a simple unadjusted recalculation; the sponsor’s analysis takes precedence.

Three secondary outcomes cover daily symptoms, daily medication use, and quality of life. The registry record does not report the original sample-size justification, multiplicity strategy, detailed missing-data methods, or complete statistical analysis plan. Safety summaries list serious adverse events in both groups and do not report deaths in the registry record.