Efficacy and Tolerability Study of Betahistine to Ameliorate Antipsychotic Associated Weight Gain: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Tolerability Study of Betahistine to Ameliorate Antipsychotic Associated Weight Gain (NCT00709202), a randomized phase 2 study. The primary outcome is Change in Weight.

2. Clinical Question

The trial asked whether adding betahistine to antipsychotic treatment was associated with a different change in weight than adding placebo. The registry describes participants as having gained a developmentally inappropriate amount of weight while taking antipsychotics. Its broader hypotheses also concerned BMI, appetite and caloric intake, body circumferences, and fasting metabolic laboratory values.

The primary question is narrower than the overall set of hypotheses. Weight change was designated as the primary outcome; BMI, waist and hip circumference, and metabolic measures were listed as secondary outcomes. Although the brief summary also mentions satiety and caloric intake, results for those measures are not reported in the registry record. The posted primary estimate therefore addresses the weight comparison, while the other proposed mechanisms and outcomes require separate evidence.

3. Trial Design

The registry classifies the study as randomized, quadruple-masked, parallel-group, and phase 2. It lists betahistine and placebo oral tablet as the two drug interventions. A parallel design assigns participants to a group whose intervention is compared with the other group over the study period; masking is intended to limit the influence of knowing treatment assignment. The registry does not specify which four parties were masked, so that detail is not reported in the registry record.

The recorded enrollment is 48. For the posted primary outcome, the betahistine group has an analysis count of 19 and the placebo group has an analysis count of 20. The endpoint description says the primary analysis used all subjects who had at least one post-baseline weight evaluation. The registry record does not explain the difference between the enrollment figure and the outcome analysis counts, nor does it describe the disposition of participants not represented in those counts.

Weight was measured at each visit from baseline to the end of the study over a 12 week period. The primary outcome is described as the least-squares estimated change from baseline to study end, analyzed using a mixed model. The registry lists BMI, waist circumference, hip circumference, glucose, cholesterol, LDL, HDL, and triglycerides among secondary outcomes; it also notes 10 secondary outcomes posted. Results are available for BMI and the two circumference measures in the posted results. Details of the measurement schedule beyond the stated visits, the specific mixed-model specification, and the trial's original design assumptions are not reported in the registry record.

The study is marked completed. The listed start is 2008-07 and the primary completion is 2016-05. The registry record does not describe changes to the protocol or explain the time between those recorded milestones. The sponsor listed is Nathan Kline Institute for Psychiatric Research.

4. Participant Flow and Accounting

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

Before assignment: 48 subjects signed consent for the study. 8 subjects withdrew consent before randomization and another subject withdrew before the first post-baseline measurement. Therefore, only 39 subjects were analyzed.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Least Squares estimated change in weight from end of study minus baseline for all subjects who had at least one post-baseline weight evaluation, using mixed model analysis.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: One subject randomized to placebo group discontinued participation before the first post-baseline measurement, and, therefore, eh was not considered as relevant in the analysis of data. Therefore, background data is presented on 39 of the 40 subjects who were analyzed for outcome variables.

6. Primary Endpoint

The registry lists the primary outcome as Change in Weight, measured over Measured at each visit from baseline to end of study over a 12 week period.

The primary endpoint is change in weight, measured in kg., defined as the end-of-study value minus baseline. The registry reports least-squares estimated changes for each group and a between-group mean difference. The analysis population is described as subjects with at least one post-baseline weight evaluation, using mixed model analysis. The reported measurement timeframe is each visit from baseline to the end of the study over a 12 week period.

Weight is a direct measure of the outcome named in the study's central hypothesis: whether betahistine augmentation was associated with a different weight trajectory than placebo augmentation among people taking antipsychotics. Comparing change from baseline helps focus the comparison on movement during the study rather than only on end-of-study weight. A between-group contrast is especially important: a change within one group alone does not establish that the intervention groups changed differently.

Least-squares means are model-based estimates rather than simple raw averages. They can express the estimated group changes under the fitted analysis, but their interpretation depends on the model and the data included. The registry identifies mixed model analysis but does not report the model specification, covariates, or assumptions in detail. Thus the endpoint definition and broad method are stated, while a full technical reproduction of the analysis is not possible from the registry record.

The endpoint does not by itself establish why weight changed, whether any change was important to participants, or whether the same pattern would occur outside this study. Those questions require information beyond the reported endpoint and its statistical uncertainty.

7. Results Posted in the Registry

• Betahistine: mean -2.00 versus -1.55 on control; difference -0.45 (95% CI -2.62 to 1.71), standardized effect d = -0.13; z-test p = 0.682.

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 in Body Mass Index (BMI)

• 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:
  • Betahistine: mean -0.55 versus -0.56 on control; difference 0.01 (95% CI -0.74 to 0.76), standardized effect d = 0.01; z-test p = 0.976.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Betahistine and the control. The interval gives the range of effects that remain compatible with the data.

Change in Waist Circumference

• 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:
  • Betahistine: mean 4.09 versus 2.49 on control; difference 1.61 (95% CI -2.21 to 5.43), standardized effect d = 0.26; z-test p = 0.410.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Betahistine and the control. The interval gives the range of effects that remain compatible with the data.

Change in Hip Circumference

• 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:
  • Betahistine: mean 1.80 versus 1.37 on control; difference 0.43 (95% CI -3.31 to 4.17), standardized effect d = 0.07; z-test p = 0.822.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Betahistine and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes provide context around the primary weight result, but they do not form a separate confirmation of it. BMI is closely related to body weight, while waist and hip circumference describe different aspects of body size. These measures can move differently from weight, and their estimates should be read as separate outcomes rather than interchangeable versions of the primary endpoint.

Across the posted secondary results, the point estimates do not form a consistent pattern of clear separation between betahistine and placebo. Their intervals include zero, leaving uncertainty about the direction and size of the between-group differences. The secondary findings therefore do not materially resolve the imprecision in the primary weight comparison. They also do not establish whether the broader proposed metabolic effects occurred.

The brief summary mentions satiety and caloric intake, and the record lists metabolic laboratory outcomes. Results for all of those proposed measures are not reported in the registry record. Among the posted secondary outcomes, the registry includes BMI and waist and hip circumference results. The presence of an outcome in the study hypothesis or outcome list should not be confused with a posted result for that outcome.

Unadjusted secondary results carry less weight because multiple outcomes create multiple opportunities for chance findings. Without a reported multiplicity strategy, an isolated p-value should not be treated as confirmatory evidence. The registry lists no reported analyses for the secondary result entries. It does not report whether analyses were prespecified, how outcome selection was handled, or whether any adjustment was planned. These gaps reinforce the need to interpret the secondary pattern cautiously and in relation to the primary comparison, rather than treating each endpoint as independent proof.

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

• Change in Body Mass Index (BMI)
• Change in Waist Circumference
• Change in Hip Circumference
• Change in Glucose
• Change in Cholesterol
• Change in LDL
• Change in HDL
• Change in Triglycerides

9. Statistical Interpretation

10. Statistical Methods Explained

What is a least-squares mean?

General explanation: a least-squares mean is an estimate from a statistical model, rather than necessarily the arithmetic average of the observed measurements. It represents the group mean as estimated by the fitted model. In this trial, the registry describes least-squares estimated change from baseline to study end and identifies a mixed model analysis. It does not give enough detail to identify all model terms, the handling of repeated measurements, or any adjustment variables. The reported least-squares means should therefore be interpreted as model-based estimates, not as unadjusted raw changes.

Why compare changes between groups?

General explanation: a within-group change describes how an outcome moved in one group, while a between-group contrast asks whether movement differed between groups. The latter is the central randomized comparison. A decrease within both groups does not by itself indicate that one intervention performed differently from the other. The primary estimate compares the reported change with betahistine against the reported change with placebo. Its sign depends on the stated comparison order: a negative estimate means the betahistine change is lower than the placebo change on the weight-change scale.

What does the interval communicate?

General explanation: a confidence interval describes uncertainty around an estimated quantity under the statistical model and repeated-sampling framework. A narrower interval indicates greater precision; a wider interval indicates less precision. An interval spanning zero for a difference is compatible with no difference as well as with values on either side of zero. It does not assign a probability to the true value being inside the particular interval. The registry posts the estimate and its interval but does not identify a confidence level, so no confidence percentage should be attached to it based on this record.

How should the p-value be read?

General explanation: a p-value describes how unusual data at least as incompatible with a null hypothesis would be under that hypothesis and the analysis assumptions. It is not the probability that the null hypothesis is true, nor a measure of the size or clinical importance of an effect. The primary unadjusted p-value is 0.682. The registry record does not state a significance threshold or a multiplicity adjustment for the posted secondary comparisons. The estimate and interval are therefore important complements to the p-value, especially because they show the range of differences compatible with the analysis.

What does the mixed model add?

General explanation: mixed models can analyze measurements that are repeated over time and account for correlation among observations from the same participant, depending on the specification. They may also use available observations when follow-up is incomplete, under assumptions that depend on the model and missingness process. The registry says weight was assessed at each visit and that the primary endpoint used mixed model analysis for subjects with at least one post-baseline evaluation. It does not state the covariance structure, estimation method, missing-data assumptions, or sensitivity analyses. It is therefore not possible to determine from the record exactly how incomplete follow-up affected the estimate.

Why does over-dispersion matter generally?

General explanation: over-dispersion occurs when observed variability exceeds what a model's assumed distribution allows. If not accounted for, uncertainty can be understated and intervals may be too narrow. The posted primary endpoint is continuous and reports standard errors; the registry does not identify an over-dispersion issue or describe a diagnostic assessment. Over-dispersion is not established as a specific concern in this trial, but it illustrates why the model assumptions and uncertainty estimates matter when reading any fitted analysis.

What is the role of standard errors?

General explanation: a standard error describes the estimated variability of a statistic across repeated samples under the model. It is not the spread of individual participant measurements. The arm-level dispersion is labeled standard error, while the group contrast is accompanied by an interval. Keeping these quantities distinct avoids interpreting the reported standard errors as the range of participant outcomes. Since the endpoint is model-based, these standard errors reflect the model's estimate of uncertainty rather than the full distribution of individual changes.

Overall, the record gives the endpoint definition, a broad mixed-model description, group estimates, standard errors, an interval for the contrast, and unadjusted p-values. It does not report enough detail to reproduce the full analysis or evaluate every assumption. General statistical interpretation can explain what the measures mean, but cannot fill in those missing trial-specific methods.

11. Confidence Intervals and Precision

The primary between-group estimate is -0.453 kg., and its reported interval runs from -2.618 to 1.712. The interval is wide enough to include zero, so the posted result is compatible with no group difference. It also includes negative and positive differences. In the stated comparison order, that means the data are compatible with a greater decrease in the betahistine group, little or no difference, or a greater decrease in the placebo group. The point estimate alone does not capture this uncertainty.

General explanation: an interval is a range of estimates reasonably compatible with the observed data and the model at its stated confidence level. Greater precision is reflected by a narrower interval. The registry record does not state the confidence level for the posted intervals. The interval should therefore be quoted as reported without assigning it a confidence percentage that is absent from the record.

The group standard errors for weight change are 0.797 for betahistine and 0.765 for placebo. They describe uncertainty in the group estimates, not the spread of individual participants' weights. The contrast interval is the most direct summary of uncertainty about the randomized comparison. Reading the estimate, interval, and unadjusted p-value together is more informative than relying on any one statistic alone.

The interval's breadth limits precision; it does not prove that all values it spans are equally plausible or that values outside it are impossible. The registry does not report a threshold for a clinically important weight difference, so the record cannot identify which points in the interval would matter clinically. The result is therefore best described as an imprecise estimate rather than as a precise demonstration of either a difference or its absence.

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 illustrations based on the observed effect, not the trial's own original design assumptions. For these continuous outcomes, the figures are participants per arm, rather than total participants or total events. The calculation assumptions listed in the registry are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row asks what the planning estimate would be if the effect to detect were the stated fraction of the observed effect.

The 80% power column means the illustrated number of participants per arm for a design with 80% power under those assumptions and that effect size. The 90% power column gives the corresponding per-arm planning figure for 90% power. In general, power is the chance of detecting an effect of the specified size under the assumptions if that effect is the true one. Higher target power generally requires more participants under otherwise unchanged assumptions.

Rows based on 100%, 75%, and 50% of the observed effect use progressively smaller target effects. Smaller effects are harder to distinguish from random variation, so they require more participants per arm to reach the same stated power target. The illustrations are sensitive to the observed effect: an imprecise or unusually large observed estimate can produce planning figures that may not represent a reliable future target.

These estimates are not observed power. They are planning illustrations derived from the posted effect and stated calculation assumptions. The registry record does not report the trial's original design assumptions or its sample-size justification. The illustrations should not be treated as evidence that the completed trial had a particular power, nor as a substitute for a prospective design calculation based on a justified target 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 = -0.453; pooled standard deviation σ = 3.447.
2. n = 2 × (1.96 + 0.842)² × 3.447² / -0.453² = 908.5, rounded up to 909 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -0.4531                      # observed difference in means
sigma <- 3.44700017641662                     # 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(709202)
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 = 909 (80% power), 1,217 (90% power)
 75% of observed effect: n per arm = 1,616 (80% power), 2,163 (90% power)
 50% of observed effect: n per arm = 3,635 (80% power), 4,865 (90% power)
power.t.test: 909.5 
Simulated power at n = 909 per arm: 0.798 (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. Multiplicity, Missing Data and Analysis Populations

The registry lists 10 secondary outcomes and 11 outcome measures. Multiple outcomes can increase the chance of at least one apparently notable result arising by chance, even when no clear underlying difference exists. A prespecified multiplicity strategy can address that issue through methods such as adjusting the testing threshold or organizing outcomes into a hierarchy. The registry record does not report such a strategy for the posted results. The reported secondary p-values are unadjusted, so they should be interpreted as exploratory rather than as a collection of independent confirmatory tests.

The primary endpoint is identified as change in weight, and its population is described as subjects with at least one post-baseline weight evaluation. That definition indicates that the posted primary analysis does not include every enrolled participant by virtue of enrollment alone. The registry does not explain why outcome analysis counts differ from recorded enrollment, how participants without a post-baseline measure were handled, or whether any imputation or sensitivity analysis was used. Missing-data assumptions and their potential effect on the estimate are therefore not reported in the registry record.

The registry identifies mixed model analysis for the primary endpoint, but does not report the model formula, covariance structure, covariate adjustment, or diagnostic checks. It also does not state whether the primary analysis followed an intention-to-treat principle or describe another analysis population beyond the stated post-baseline requirement. These details matter because model specification and analysis-population choices can affect estimates and uncertainty.

Interim analyses, stopping rules, and the trial's original statistical plan are not reported in the registry record. The record also does not provide a sample-size justification. These omissions do not establish that a procedure was or was not used; they mean that the information is unavailable in the registry record. Consequently, interpretation should focus on the posted estimates and their uncertainty while recognizing that the analysis plan and missing-data handling cannot be fully assessed.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports serious adverse events for 0 participants in the betahistine group and 0 participants in the placebo group. The listed group counts at risk are 19 for betahistine and 20 for placebo. Deaths are reported as 0 in each group. For other adverse events, the registry reports 2 affected participants in the betahistine group and 4 in the placebo group.

These are descriptive counts in the registry record. They do not establish that an event was caused by the assigned intervention, and they do not show the full nature, timing, severity, or duration of the other adverse events. The record lists no serious adverse event terms. Zero reported serious events in these groups should not be interpreted as proof that serious harms are impossible or that the interventions have equivalent safety. The trial's recorded enrollment and outcome analysis counts also differ, and the registry does not explain the disposition of every participant for safety reporting. These figures are best read as the adverse-event counts posted for this study, not as a complete assessment of comparative safety.

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

The result is an estimate of the difference in weight change between the betahistine and placebo groups during a 12 week period, for the primary analysis population described in the registry. The point estimate is -0.453 kg. In the betahistine-minus-placebo comparison. Its reported interval spans zero and extends in both directions, so the estimate is not precise enough to establish a clear difference from these data alone.

This does not mean the groups were proven equivalent. A finding of equivalence would require a prespecified margin and an analysis designed to assess whether the uncertainty lies within that margin; neither is reported in the registry record. Nor does the result prove that there is no effect. The interval remains compatible with differences in either direction. The unadjusted p-value of 0.682 likewise should not be interpreted as the probability that the treatment has no effect.

The result also does not demonstrate a clinically meaningful benefit or harm. The registry does not give a threshold for what size of weight change would matter to participants. The posted estimate cannot establish long-term effects, effects in other populations, or effects under treatment conditions not described in the record. It addresses the recorded group comparison in this study, not every outcome in the broader hypotheses.

Because the analysis counts are smaller than the recorded enrollment, and because the record does not explain the difference or report detailed missing-data procedures, the representativeness of the analyzed data cannot be fully assessed. The mixed model description is too brief to reconstruct all analytic choices. Secondary outcomes and adverse-event counts offer additional context but do not overcome those limits.

The appropriate reading is cautious: the observed estimate points toward a greater decrease in the betahistine group, but the uncertainty includes no difference and a difference in the opposite direction. It is an imprecise result from a phase 2 trial, not a final determination of efficacy, absence of efficacy, or safety.

17. Why This Trial Matters Statistically

This trial illustrates why a between-group estimate and its uncertainty are more informative than looking only at change within each arm. Both groups had negative reported weight-change estimates, yet the primary scientific question concerns whether their changes differed. The contrast addresses that question directly; its interval shows why the point estimate should not be treated as a settled conclusion.

It also demonstrates the role of endpoint hierarchy. Weight was designated as the primary outcome, while BMI and other body-size and metabolic measures were secondary. Related endpoints can add context, but they do not automatically provide independent confirmation. Considering multiple outcomes without a reported adjustment strategy increases the risk of overinterpreting isolated patterns or p-values.

The record provides an opportunity to distinguish outcome reporting from design planning. The posted sample-size illustrations use the observed effect and stated planning assumptions, whereas the trial's original sample-size rationale is not reported. Retrospective planning illustrations are not observed power and cannot establish whether the design was adequate for a particular target difference.

Finally, the endpoint is model-based and the primary analysis population requires at least one post-baseline weight evaluation. The record gives a broad mixed-model description but does not document the full model, missing-data strategy, or analysis-plan details. This makes the study useful for teaching how to interpret estimates and identify reporting limits: numerical results must be read alongside the definition of the population, methods, multiplicity, and precision.

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 recorded enrollment is 48, while the primary outcome analysis counts are 19 for betahistine and 20 for placebo. The registry record does not explain the difference, provide a participant flow, or report reasons for missing post-baseline measurements. Since the primary analysis population requires at least one post-baseline weight evaluation, the scope of the result is narrower than simply all enrolled participants. The effect of missing observations cannot be assessed from the posted information.

The analysis description is brief. It identifies a mixed model and least-squares mean change, but does not give the model specification, covariates, covariance structure, or sensitivity analyses. The record does not state the confidence level attached to the intervals, the original sample-size justification, or a complete statistical analysis plan. These omissions limit independent evaluation and reproduction of the primary analysis.

The follow-up described for the primary endpoint is over a 12 week period. The registry does not report longer-term weight outcomes. The population spans several listed psychiatric and developmental conditions, but the posted result is not broken down by condition, age group, or antipsychotic treatment. It is therefore not possible to assess whether estimates differ across those groups from this record.

Results for some outcomes mentioned in the hypotheses, including satiety and caloric intake, are not reported in the registry record. The secondary p-values are unadjusted, and no multiplicity plan is reported. Finally, the adverse-event counts are descriptive and do not provide detailed event terms or establish causality. These limits do not negate the posted estimates, but they constrain what can be concluded from them.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Efficacy and Tolerability Study of Betahistine to Ameliorate Antipsychotic Associated Weight Gain — NCT00709202.
• Registry record last updated 2019-01-25; status last verified 2019-01.
• Results first posted 2019-01-25.
• 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 record describes a completed, randomized, quadruple-masked, parallel-group phase 2 trial of betahistine versus placebo for antipsychotic-associated weight gain. Recorded enrollment is 48. The primary endpoint is least-squares estimated change in weight from baseline to study end over a 12 week period, using mixed model analysis for participants with at least one post-baseline weight evaluation.

The primary between-group estimate was -0.453 kg., with a reported interval from -2.618 to 1.712 and an unadjusted p-value of 0.682. The interval includes zero and values in both directions, indicating substantial uncertainty about the size and direction of the difference. Secondary results and adverse-event counts are also posted, but the record does not report all outcomes described in the hypotheses, a full statistical analysis plan, the original sample-size justification, or detailed missing-data methods.