A Short-Term Appetite Suppression Trial Using Appethyl™: The Pizza: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Short-Term Appetite Suppression Trial Using Appethyl™: The Pizza (NCT01919814), a randomized na study. The primary outcome is Difference in Pizza Consumed During Two Meals.

2. Clinical Question

This is a short-term appetite-related question about food consumption under the trial’s meal-testing conditions. It is not a direct measure of long-term appetite, usual eating behavior, or change in body weight. The registry also lists appetite and satiety as secondary outcomes, but the posted primary outcome concerns calories consumed during the two meals. The record does not report results for those secondary outcomes in the registry record for this analysis.

3. Trial Design

The registry classifies the study as randomized, double-masked, and crossover. In a crossover design, participants receive more than one study condition in sequence, so each participant may contribute observations under both conditions. Here, the two stated sequences were Appethyl™ followed by placebo and placebo followed by Appethyl™. The registry describes a washout period of at least one week between the two periods.

In both periods, the assigned liquid was taken once four hours after breakfast. The primary meal test involved a standard lunch followed by pizza five hours after lunch. Participants were asked to eat the pizza to their satisfaction over 30 minutes. This setup measures consumption during a specified test meal, rather than intake over a usual day or a longer follow-up period.

Enrollment was 60, and the record status is completed. The primary-outcome description states that one participant dropped because of an adverse event. The posted outcome summaries list 59.0 participants for Appethyl™ and 59.0 for placebo. The registry does not report a fuller account of participant flow, period-specific completion, or whether every participant contributed a paired observation.

The registry lists the study phase as NA. It gives the start as 2013-07 and primary completion as 2015-12. The planned design assumptions, including any original sample-size justification, are not reported in the registry record. The trial’s crossover structure is important when interpreting the analysis: a paired comparison can use within-participant information, while an independent-groups comparison does not use that pairing in the same way. The posted analysis information does not fully describe how the sequence and repeated observations were handled.

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: One participant dropped because of adverse event

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: One participant was dropped because of adverse event

6. Primary Endpoint

The registry lists the primary outcome as Difference in Pizza Consumed During Two Meals, measured over 5 hours after lunch (9 hours after administration of Appethyl from the morning).

The primary endpoint is the difference in calories consumed during the pizza meal following lunch. The registry describes participants as being offered more pizza than they could reasonably be expected to eat and asked to eat to satisfaction over 30 minutes. The reported measure is a mean, with standard deviation used to describe spread. The timeframe is five hours after lunch, stated also as nine hours after morning administration of Appethyl™.

This endpoint is used to quantify eating behavior under a controlled, short-term test. Counting calories consumed gives a continuous measure, which can show both the average intake in each condition and variation among participants. The outcome is narrower than a general measure of appetite: it records food consumed at a particular meal under a particular schedule. Appetite and satiety are separately listed as secondary outcomes, including evaluation by visual analogue scale, but their posted results are not included in the registry record.

The mean calorie consumption was 1020.0 with Appethyl™ and 1067.0 with placebo. These are condition-specific summaries. The endpoint should be interpreted in the context of the crossover design and the stated meal protocol, not as a measure of sustained dietary intake or a clinical outcome beyond the recorded meal consumption.

7. Results Posted in the Registry

• Appethyl™: mean 1,020 versus 1,067 on control; difference -47.25 (95% CI -246.80 to 152.30), standardized effect d = -0.09; z-test p = 0.643.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary measure is continuous: calories consumed at the pizza meal. For a continuous outcome, the mean describes the arithmetic average, while the standard deviation describes the spread of individual observations around that average. A large standard deviation relative to the difference between means indicates substantial variation in the measured outcome. Here, the reported standard deviations are 554.4 calories for Appethyl™ and 551.6 calories for placebo, compared with a recalculated mean difference of -47.25 calories.

What does a two-sided t-test ask?

The registry reports a two-sided t-test. In general, a t-test assesses whether the observed mean difference is compatible with a null hypothesis of no mean difference, given the assumptions of the test and the variation in the data. A two-sided test considers departures in either direction: lower or higher mean consumption. The registry reports p > 0.05, not an exact value. A p-value is a measure of how unusual the data, or more extreme data, would be under the null hypothesis and the model assumptions. It is not the probability that the null hypothesis is true, and it does not quantify the probability that a treatment works.

Why does the crossover design matter?

In general, a crossover comparison can account for the fact that the same participant receives both conditions. This allows a treatment contrast to use within-participant differences, which may be more informative than comparing two unrelated groups when individual baseline levels vary. However, analysis must address the repeated observations and the order in which conditions were received. Period effects, sequence effects, or carryover can affect interpretation if they are relevant and not handled appropriately. The registry describes randomized sequences and a washout of at least one week, but details of the analysis of paired observations, period, sequence, or carryover are not reported in the registry record.

The reported primary summaries show 59.0 observations for each treatment condition. Those counts alone do not identify whether the same participants contributed to both summaries or establish how the reported test treated the observations. The sponsor’s reported test is described only as a two-sided t-test. Further specification of its variance assumptions or its handling of the crossover is not reported in the registry record. Consequently, the recalculation from posted summary statistics is best viewed as an unadjusted check, not as a replacement for the trial analysis.

What is the role of the mean difference?

The recalculated mean difference is -47.25 calories, with Appethyl™ as the first condition and placebo as the second. A negative value means the posted Appethyl™ mean is lower than the posted placebo mean. The difference is expressed in the endpoint’s original units, making it directly interpretable as a contrast in average calories consumed during the test meal. That direction is descriptive; it does not by itself demonstrate a reliable difference.

Standardized effect measures express a contrast relative to a measure of variability. They can help compare effects measured on different scales, but they do not replace the original-unit estimate or its uncertainty. The registry’s recalculated standardized effect is -0.085; it is not reproduced because the reporting limit is three decimal places. The standardized value is small in magnitude, but the analysis should still be read with its uncertainty and design limitations in mind.

How should uncertainty be understood?

In general, a confidence interval gives a range of estimates compatible with the data and a statistical procedure, under that procedure’s assumptions. The recalculated interval runs from -246.8 to 152.3 calories. It includes no difference and includes possible differences on either side of zero. The interval’s stated confidence level is not reported in the registry record. A broad interval means the estimate is imprecise; it does not prove that every value in the interval is equally likely or that values outside it are impossible.

Imprecision can arise when the observed contrast is modest relative to variability, when the available information is limited, or when design features are not fully represented in a summary-statistic calculation. General statistical interpretation should keep the estimate, interval, test result, and design in view together. A p-value above 0.05 does not convert an uncertain estimate into evidence of equivalence. Equivalence requires a prespecified margin and an analysis designed to assess whether the plausible difference is sufficiently small; those details are not reported in the registry record.

What does the recalculation add?

The recalculation uses the posted condition means and standard deviations to produce a simple unadjusted contrast and uncertainty summary. It is not an independent reconstruction of the participant-level crossover analysis, because participant-level data and the sponsor’s full statistical specification are not reported in the registry record. The recalculated p-value is 0.643, whereas the sponsor reports p > 0.05. Since the registry’s discrepancy flag is true, the sponsor’s own analysis takes precedence. The recalculation can be read as a transparency check on the posted summaries, not as the definitive trial result.

10. Confidence Intervals and Precision

The recalculated mean difference is -47.25 calories for Appethyl™ minus placebo. The interval accompanying this estimate ranges from -246.8 to 152.3 calories. The registry record does not report the confidence level for this interval. It is therefore appropriate to describe the bounds and their implication, but not to assign a particular confidence percentage.

The interval includes zero. It also includes negative values, corresponding to lower average consumption with Appethyl™, and positive values, corresponding to higher average consumption with Appethyl™. This range shows that the recalculation does not determine the direction of the difference with precision. Its width relative to the point estimate also indicates that substantially different contrasts remain compatible with the summary-based calculation.

In general, a confidence interval expresses uncertainty in an estimate under a statistical procedure and its assumptions. It is not a list of values that have equal probability, and it does not mean that the true value must fall within the interval. Its interpretation depends on the method used. Here, the crossover structure and the limited description of the sponsor’s analysis are relevant: a recalculation from summary statistics may not reproduce an analysis that uses participant-level paired data.

The sponsor’s analysis reports p > 0.05, while the recalculated p-value is 0.643. Both indicate that the result does not meet a conventional significance threshold, but the sponsor’s test is the analysis that takes precedence. Neither the reported p-value nor the recalculated interval establishes that the conditions are equivalent. The interval’s breadth leaves meaningful uncertainty about the magnitude and direction of the mean difference.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are illustrations based on fractions of the observed effect, not the original design assumptions for the trial. For 100% of the observed effect, the illustration gives 2,151 participants per arm for 80% power and 2,879 participants per arm for 90% power. For 75% of the observed effect, it gives 3,823 participants per arm for 80% power and 5,118 participants per arm for 90% power. For 50% of the observed effect, it gives 8,601 participants per arm for 80% power and 11,514 participants per arm for 90% power.

These figures are participants per arm, not total event counts. In general, power is the probability that a study will detect an effect of the specified size under the planning assumptions, if that effect is present. The 80% column describes a planning target with an 80% chance of detecting the specified effect; the 90% column uses a higher detection-probability target. The listed assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect.

As the effect being planned for becomes smaller, the required number of participants per arm increases. These estimates are based on the observed effect and are not observed power. The trial’s own original sample-size justification and design assumptions are not reported in the registry record. The planning illustration does not establish what the trial was designed to detect, and it should not be treated as a retrospective judgment of the trial’s success or failure.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -47.250; pooled standard deviation σ = 552.992.
2. n = 2 × (1.96 + 0.842)² × 552.992² / -47.250² = 2,150.2, rounded up to 2,151 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 <- -47.25                      # observed difference in means
sigma <- 552.991672360444                     # 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(1919814)
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 = 2,151 (80% power), 2,879 (90% power)
 75% of observed effect: n per arm = 3,823 (80% power), 5,118 (90% power)
 50% of observed effect: n per arm = 8,601 (80% power), 11,514 (90% power)
power.t.test: 2151.1 
Simulated power at n = 2,151 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.

13. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary analysis as a two-sided t-test, with p > 0.05. It does not give an exact p-value, test statistic, interval, or fuller description of the test. The posted condition means are 1020.0 calories for Appethyl™ and 1067.0 calories for placebo.

A simple unadjusted recalculation from the posted summary statistics gives a mean difference of -47.25 calories, an interval from -246.8 to 152.3 calories, and a p-value of 0.643. This recalculation is not necessarily the same analysis as the sponsor’s test. In particular, the study is a crossover trial, while the available summary statistics do not show how within-participant pairing was handled in the sponsor’s analysis.

The record flags a discrepancy between the sponsor-reported analysis and the recalculation. Under that circumstance, the sponsor’s own analysis takes precedence. The recalculation is useful as a separate check on the posted summaries, but it should not be presented as an alternative definitive result or used to override the registry-reported test. The sponsor’s exact estimate and uncertainty interval are not reported in the registry record.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists two secondary outcomes: evaluation of appetite and evaluation of satiety by means of a visual analogue scale. It also reports three outcome measures and one analysis, but the available information does not give results for the listed secondary outcomes. Those results, including estimates and uncertainty, are not reported in the registry record.

When a study examines multiple outcomes, time points, or comparisons, the chance of obtaining at least one apparently unusual result can increase. General approaches to this issue include defining a primary outcome in advance, controlling error rates across a family of tests, or treating additional analyses as exploratory. The registry record does not report a multiplicity adjustment, a testing hierarchy, or how secondary outcomes were handled. It is therefore not possible to determine whether multiplicity was addressed in the sponsor’s analysis.

The registry describes randomization, masking, and a crossover structure, but does not report a detailed analysis population definition. The primary outcome description notes that one participant dropped because of an adverse event, and the outcome summaries list 59.0 participants in each condition. The record does not explain how missing outcome data were handled, whether all randomized participants were analyzed, or whether any imputation or sensitivity analysis was used. These matters are important because missingness can affect an estimate if the available observations differ systematically from the observations that are missing.

In general, crossover trials also need clarity about participants who complete only one treatment period, because their available data may not support the same within-person contrast as complete paired observations. Period-specific completion and the handling of incomplete pairs are not reported in the registry record. The stated washout period does not, on its own, establish that carryover was assessed or absent.

The sponsor-reported result is a two-sided t-test with p > 0.05. Further information on prespecification, analysis populations, missing-data procedures, and multiplicity is not reported in the registry record. These gaps limit the ability to independently assess the analysis beyond the stated test and posted summary statistics.

15. 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 0% reporting threshold.

Most frequent serious adverse event terms

Serious events with the highest arm-level rate: severe headache (1.7%).

The registry reports serious adverse event figures separately for Appethyl™ and placebo. For each condition, 60 participants were listed as at risk, and 1 serious adverse event was reported. The most frequent serious-event term listed is Severe Headache, at 1.7%. The record reports 0 other adverse events in each condition.

These figures describe the entries in the registry record; they do not by themselves establish a causal relationship between a study liquid and an event. The registry lists one serious adverse event in each condition, but does not provide enough detail to compare event characteristics, timing, or participant-level exposure across periods in the crossover. Deaths are not reported in the registry record.

Adverse-event counts should be read alongside the trial’s size, duration, and recording context. This was a short-term meal-testing study, and the safety figures do not establish the frequency of events in other settings or over longer periods. The serious-event figures are descriptive registry results, not a basis for individual medical decisions.

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

The posted results show mean pizza-meal consumption of 1020.0 calories after Appethyl™ and 1067.0 calories after placebo. The sponsor-reported two-sided test gives p > 0.05. A recalculation from the posted summaries gives a mean difference of -47.25 calories, with an interval from -246.8 to 152.3 calories and a p-value of 0.643. Because the record flags a discrepancy, the sponsor’s own analysis takes precedence.

These results do not establish that the two conditions produce the same mean consumption. A non-significant test does not prove there is no difference, and the recalculated interval spans both lower and higher consumption with Appethyl™. The interval is broad enough that the magnitude and direction of a difference remain uncertain. The confidence level for that recalculated interval is not reported in the registry record.

The trial addresses consumption at a particular pizza meal under a short-term testing schedule. It does not answer whether appetite changes persist, whether food intake differs in everyday settings, or whether there are longer-term effects. The registry lists appetite and satiety as secondary outcomes, but their results are not reported in the registry record. No conclusions about those outcomes can be drawn from the primary meal-consumption summaries alone.

The randomized, double-masked crossover design provides a structured comparison of Appethyl™ and placebo. However, interpretation of its analysis is limited because the registry does not give full details of the paired-data analysis, participant flow, or missing-data handling. The posted summaries and sponsor test should therefore be interpreted as evidence about the recorded short-term endpoint, not as a complete account of all possible effects or outcomes.

In general, statistical significance and practical importance are different questions. The primary results do not demonstrate a clear difference under the sponsor’s reported test, while the uncertainty around the recalculated estimate remains substantial. The registry record does not report a threshold for a clinically or behaviorally important calorie difference, so the importance of any possible difference cannot be judged against a stated benchmark.

17. Why This Trial Matters Statistically

This trial is statistically instructive because its randomized, double-masked crossover design puts the analysis structure in focus. In a crossover study, the same participant may receive both conditions. A comparison can therefore use within-person contrasts, but the analysis needs to reflect repeated observations and the order of treatment. The registry identifies the design and treatment sequences, yet its brief description of the t-test does not fully show how those features entered the sponsor’s analysis.

The outcome also illustrates why estimates and uncertainty should be read together. The condition means are close relative to the reported standard deviations, and the recalculated interval extends in both directions around zero. A p-value above 0.05 is not proof of no effect; it is one part of an analysis whose precision and assumptions matter. The interval makes the range of uncertainty more visible than a test result alone.

A further lesson is the distinction between the sponsor’s analysis and a recalculation from summary data. Summary-based calculations can provide a transparent check, but they may not reproduce a participant-level analysis, particularly for a crossover trial. The registry flags a discrepancy, so the sponsor’s analysis takes precedence rather than the recalculation being treated as a correction.

Finally, the endpoint is deliberately specific: calories consumed at one meal at a defined time after breakfast and lunch. That specificity makes the measure interpretable within the protocol, while limiting what can be inferred about longer-term eating behavior or other appetite measures. The record’s missing detail on secondary results, missing data, and analysis populations shows why a statistical result is best understood together with the design and reporting context.

18. Limitations

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

The primary endpoint concerns a single test meal after a specified schedule. It does not describe usual food intake, sustained appetite, or longer-term outcomes. The registry lists appetite and satiety as secondary outcomes, but those results are not reported in the registry record. The available primary summaries therefore provide a narrow view of the study question.

Although the study is described as a crossover trial, the sponsor’s analysis is reported only as a two-sided t-test. The registry record does not explain whether the test used paired participant-level data, how treatment sequence or period was handled, or whether carryover was assessed. The recalculation uses summary statistics and cannot independently recover those details.

The primary description notes one participant dropped because of an adverse event. The outcome summaries list 59.0 participants for each condition, but detailed participant flow and the handling of missing observations are not reported in the registry record. The analysis population, any imputation, and sensitivity analyses are also not reported.

The reported standard deviations are large in relation to the recalculated mean difference, and the recalculated interval spans both directions. The interval’s confidence level is not reported in the registry record. The sponsor’s exact estimate and uncertainty are also not reported, and the sponsor’s p-value is stated only as p > 0.05. The record flags a discrepancy between the sponsor’s analysis and the summary-based recalculation, so the sponsor’s result takes precedence.

The original sample-size rationale and trial-specific design assumptions are not reported in the registry record. The available planning illustration is based on fractions of the observed effect and should not be mistaken for the original trial plan. These reporting limits make it difficult to assess the study’s intended precision or fully reproduce its primary analysis.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Short-Term Appetite Suppression Trial Using Appethyl™: The Pizza — NCT01919814.
• Registry record last updated 2019-08-28; status last verified 2019-08.
• Results first posted 2019-08-28.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry describes a completed, randomized, double-masked crossover study of Appethyl™ and placebo in participants with overweight or obesity. Participants received both conditions in opposite sequences, separated by a washout period of at least one week. The primary outcome was calories consumed at a pizza meal scheduled after lunch.

The posted means were 1020.0 calories with Appethyl™ and 1067.0 calories with placebo. The sponsor reported a two-sided t-test with p > 0.05. A recalculation from the posted summaries gives a mean difference of -47.25 calories and an interval from -246.8 to 152.3 calories; because a discrepancy is flagged, the sponsor’s own analysis takes precedence.

The record notes one participant dropped because of an adverse event. It lists one serious adverse event in each condition and 0 other adverse events in each condition. Secondary appetite and satiety results, fuller analysis details, and the original sample-size justification are not reported in the registry record.