A Study to Evaluate the Safety, Tolerability, and Weight Loss Efficacy of K-757 Alone and in Combination With K-833: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Evaluate the Safety, Tolerability, and Weight Loss Efficacy of K-757 Alone and in Combination With K-833 (NCT06019559), a randomized phase 2 study. The primary outcome is Percentage Change From Baseline in Body Weight (%) After 13 Weeks of Treatment.

2. Clinical Question

The trial also examined the proportion reaching at least 5% weight loss, absolute change in body weight, and treatment-emergent adverse events. Those outcomes provide additional views of weight change and tolerability, but they do not replace the prespecified primary endpoint. The registry describes a randomized, double-blind, placebo-controlled, parallel-group study with quadruple masking. Its brief summary states that safety and efficacy of K-757 alone and in combination with K-833 were evaluated against placebo.

The clinical question is therefore comparative: how did the recorded weight outcomes differ among the placebo, K-757-alone, and combination groups during the study period? The posted results describe group estimates and analyses, not an individual participant's likely outcome. Details such as eligibility criteria beyond obesity, baseline characteristics, and the clinical rationale for the tested doses are not reported in the registry record.

3. Trial Design

This was a randomized, placebo-controlled, double-blind, parallel-group phase 2 study with quadruple masking. The registry lists 155 participants and three groups: placebo to both K-757 and K-833, K-757 alone with matching placebo to K-833, and K-757 with K-833. The listed active regimens were K-757 120 mg BID and K-833 100 mg BID. The official title describes a 13-week study in participants who are obese.

The study is marked completed. Its registry start date is 2023-09-15, and its primary completion date is 2024-02-07. The primary outcome was percentage change from baseline in body weight after 13 weeks, analyzed in the Modified Intent-to-Treat Population. The posted primary arm counts were 52 for placebo, 51 for K-757 alone, and 52 for the combination group.

Randomization is intended to support balanced comparisons between groups, while masking is intended to limit the influence of treatment knowledge on care, measurement, and assessment. These are general explanations of trial-design concepts; the registry does not report the randomization procedure, allocation concealment details, or the identities of the masked parties. Arm descriptions beyond the named treatments are blank, and further operational details are not reported in the registry record.

The registry reports a 13-week timeframe for the primary endpoint and several secondary outcomes. One adverse-event outcome uses a 15-week timeframe. The registry record does not explain the reason for that different timeframe. Detailed visit schedules, treatment adherence, withdrawals, and the protocol's planned sample-size justification are not reported in the registry record.

4. Participant Flow and Accounting

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

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified Intent-to-Treat Population

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: All randomized all modified intent-to-treat

6. Primary Endpoint

The registry lists the primary outcome as Percentage Change From Baseline in Body Weight (%) After 13 Weeks of Treatment, measured over 13 weeks.

The primary endpoint is percentage change from baseline in body weight after 13 weeks of treatment. It expresses body-weight change relative to each participant's baseline weight, rather than as an absolute change in kilograms. In general, a negative percentage change represents a reduction from baseline, while a positive value represents an increase. The registry reports least-squares means and standard errors for this continuous outcome in the Modified Intent-to-Treat Population.

A percentage measure can help describe change on a common relative scale when participants may begin at different body weights. It is also distinct from the absolute-change secondary outcome, which is measured in kilograms. These measures answer related but not identical questions: one describes relative change and the other describes change in weight units. This is a general statistical distinction, not a claim that one measure is preferable for every study.

The posted least-squares mean percentage changes were -0.15 for placebo, -1.57 for K-757 alone, and -2.94 for K-757 with K-833. The registry also reports standard errors of 0.562, 0.566, and 0.587, respectively. A standard error describes uncertainty in an estimated group mean; it is not the spread of individual participants' weight changes. The registry does not provide a fuller endpoint definition or details of the model used to obtain the least-squares means, beyond identifying mixed models analysis for the reported comparisons.

7. Results Posted in the Registry

• K-757 Alone: mean -1.57 versus -0.15 on control; difference -1.42 (95% CI -2.98 to 0.14), standardized effect d = -0.35; z-test p = 0.075.
• K-757+K-833: mean -2.94 versus -0.15 on control; difference -2.79 (95% CI -4.38 to -1.20), standardized effect d = -0.67; z-test p = <0.001.

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.

The Proportion of Participants Achieving ≥5% Weight Loss After 13 Weeks of Treatment

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • K-757 Alone: 17.6% (9/51) versus 11.5% (6/52) on control; risk difference 6.1 percentage points (95% CI -7.5 to 19.7), risk ratio 1.53 (0.59–3.99); unadjusted two-proportion z-test p = 0.380.
  • K-757+K-833: 21.2% (11/52) versus 11.5% (6/52) on control; risk difference 9.6 percentage points (95% CI -4.5 to 23.7), risk ratio 1.83 (0.73–4.59); unadjusted two-proportion z-test p = 0.185.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between K-757 Alone and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between K-757+K-833 and the control. The interval gives the range of effects that remain compatible with the data.

Absolute Change From Baseline in Body Weight (kg) After 13 Weeks of Treatment

• 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:
  • K-757 Alone: mean -1.64 versus -0.09 on control; difference -1.55 (95% CI -3.17 to 0.07), standardized effect d = -0.37; z-test p = 0.061.
  • K-757+K-833: mean -3.11 versus -0.09 on control; difference -3.02 (95% CI -4.67 to -1.37), standardized effect d = -0.70; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between K-757 Alone and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for K-757+K-833 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Proportion of Participants Who Experienced 1 or More Treatment-emergent AEs

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • K-757 Alone: 80.4% (41/51) versus 59.6% (31/52) on control; risk difference 20.8 percentage points (95% CI 3.6 to 38.0), risk ratio 1.35 (1.04–1.75); unadjusted two-proportion z-test p = 0.022.
  • K-757+K-833: 80.8% (42/52) versus 59.6% (31/52) on control; risk difference 21.2 percentage points (95% CI 4.0 to 38.3), risk ratio 1.35 (1.04–1.76); unadjusted two-proportion z-test p = 0.018.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for K-757 Alone than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for K-757+K-833 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes extend the primary question in two directions: they describe weight change using an absolute kilogram scale and a threshold for achieving at least 5% weight loss, and they include a treatment-emergent adverse-event measure. Their overall pattern is broadly consistent with the primary estimates in that the active groups have more favorable weight-change estimates than placebo, while the posted event counts for treatment-emergent adverse events are higher in each active group than in placebo. These measures are related to, but distinct from, the primary percentage-change endpoint.

The secondary analyses should not be treated as interchangeable confirmations of the primary result. A continuous mean, a threshold count, and an adverse-event count answer different questions and may have different statistical precision. The posted registry analyses for the weight-loss threshold use logistic regression, while the absolute body-weight change is reported with mixed models analysis. No sponsor analysis is listed for the treatment-emergent adverse-event outcome.

In general, interpreting several outcomes and comparisons creates multiplicity: the more tests considered, the greater the possibility of apparently notable results arising by chance. The registry does not report a multiplicity adjustment or a hierarchy specifying which secondary outcomes were confirmatory. Therefore, unadjusted secondary results carry less weight than a result supported by a prespecified primary analysis, especially when effect estimates, intervals, or analysis details are not fully posted. Secondary findings can help describe the pattern of results, but should be understood as supportive or exploratory unless the analysis plan establishes otherwise. That plan is not reported in the registry record.

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

• The Proportion of Participants Achieving ≥5% Weight Loss After 13 Weeks of Treatment
• Absolute Change From Baseline in Body Weight (kg) After 13 Weeks of Treatment
• Proportion of Participants Who Experienced 1 or More Treatment-emergent AEs
• Proportion of Participants Who Discontinued Study Medication Due to an AE

9. Statistical Interpretation

10. Statistical Methods Explained

The registry identifies the primary outcome as a continuous measure: percentage change from baseline in body weight after 13 weeks. It reports a least-squares mean and standard error for each group. In general, a mean describes the central value of a continuous measurement. A least-squares mean is a model-based estimate; its exact interpretation depends on the model and covariates. The detailed model specification and covariates are not reported in the registry record.

What does the standard error describe?

In general, the standard error describes the sampling uncertainty of an estimated mean. It is not the same as a standard deviation, which describes variation among individual observations. The primary endpoint standard errors were 0.562, 0.566, and 0.587 for placebo, K-757 alone, and the combination group, respectively. The registry does not report a direct standard deviation for the endpoint. The recalculated comparisons approximate a pooled standard deviation from the posted standard errors and group sizes; that approximation is not the sponsor's model-based estimate of variability.

How are the comparisons expressed?

The recalculated continuous-outcome comparisons express each active group's estimated mean minus the placebo group's estimated mean. A negative difference means the active-group estimate is more negative than the placebo estimate on this endpoint scale. For K-757 alone, the recalculated difference was -1.42; for K-757 with K-833, it was -2.79. These are unadjusted comparisons derived from posted summary statistics. They do not adjust for other variables or account for any unreported features of the sponsor's model.

The sponsor reports mixed models analysis for both primary comparisons. A mixed model is a general statistical approach that can account for structured or repeated measurements, depending on how it is specified. The registry does not report enough detail to establish which repeated-measure structure, covariates, missing-data assumptions, or estimation method was used. Consequently, the label “Mixed Models Analysis” should not be taken as a complete description of the model.

What does a p-value say?

In general, a p-value measures how unusual the data would be under a stated null hypothesis and a particular statistical model. It does not measure the size or importance of a difference, and it is not the probability that the null hypothesis is true. The sponsor's reported primary p-values were 0.076 and 0.001. The unadjusted recalculated p-values were 0.075 and <0.001. Since the reported analyses and recalculations differ, the sponsor's own analysis takes precedence.

The registry lists a superiority analysis type for the sponsor's comparisons. It does not report the detailed hypotheses, a prespecified decision threshold, or a multiplicity adjustment. In general, multiplicity arises when several outcomes or comparisons are tested: the chance of at least one apparently unusual result can increase as the number of tests grows. Without a reported adjustment plan, unadjusted secondary p-values should be treated as exploratory rather than as a set of independent confirmatory conclusions.

Why can over-dispersion matter?

Over-dispersion is a general concern for count or binary data when observed variability exceeds what a chosen statistical model assumes. It can affect standard errors and p-values if the model does not accommodate that extra variability. The registry identifies logistic regression for the posted binary weight-loss comparisons, but does not report model diagnostics or whether over-dispersion was assessed. The primary endpoint is continuous, so this issue is not the same as interpreting its reported standard error.

For binary outcomes, a risk difference expresses the difference between group proportions on an absolute scale. A risk ratio compares those proportions as a ratio, while an odds ratio compares odds. These are general definitions. The registry lists participant counts and sponsor logistic-regression p-values for the threshold weight-loss outcome, but does not post the sponsor's effect estimates or confidence intervals for that outcome. For adverse events, participant counts are posted, while no sponsor analysis is listed for the treatment-emergent adverse-event outcome.

Finally, a confidence interval represents uncertainty under the calculation's assumptions; it is not a prediction interval for individual participants. The registry record does not report a full statistical analysis plan, missing-data method, interim analyses, or the trial's original sample-size justification. Those omissions limit how specifically the statistical procedures can be reconstructed from the registry results.

11. Confidence Intervals and Precision

The primary endpoint estimates are accompanied by standard errors, and the recalculated comparisons include confidence intervals. The K-757-alone mean difference versus placebo was -1.42; its recalculated interval includes zero. This indicates that the posted summary statistics do not establish a clearly separated difference at the interval's stated level. The K-757-plus-K-833 mean difference was -2.79, with a recalculated interval from -4.383 to -1.197. That interval lies below zero under the recalculation assumptions.

In general, a confidence interval conveys both an estimated effect and its uncertainty. A narrower interval indicates greater precision under the same method; a wider interval indicates less precision. Precision depends on factors such as sample size and variability, but an interval does not account for biases or model assumptions that are not represented in the calculation. The confidence level for the recalculated intervals is not stated in the registry record, and the registry does not post sponsor confidence intervals for the primary comparisons.

The sponsor's primary analyses report p-values but no estimated differences or intervals. Therefore, those p-values cannot alone show how precisely the sponsor estimated the effects. The discrepancy between the sponsor's analysis and the unadjusted recalculation also matters: the sponsor's analysis takes precedence, while the recalculation provides a transparent but approximate view based on the posted summaries. The listed standard errors are not participant-level variability measures and cannot show the range of responses among individuals.

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 illustrative calculations based on the observed effects, not the trial's original design justification. For these non-time-to-event outcomes, the displayed figures are participants per arm, not total events. The 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 the stated fraction of the observed effect. The original trial's sample-size assumptions are not reported in the registry record.

The 80% power column gives the estimated number of participants per arm for a design that would have an 80% chance of detecting the specified effect under those planning assumptions, if that effect and assumptions were correct. The 90% power column gives the corresponding number for a higher chance of detecting that effect. These are design-planning probabilities, not guarantees about a study's result. This is not observed power.

Each row changes the assumed effect size relative to the effect observed in the trial. Planning for 75% of the observed effect or 50% of the observed effect means targeting a smaller difference than the observed one. Smaller effects generally require more participants to detect with the same power and significance level, which is why those planning rows have larger sample-size requirements. The observed effect can itself be unstable, especially in a small study, so these illustrations should not be treated as reliable forecasts of a future study's results.

The calculations are pairwise illustrations and assume equal allocation between two arms. They do not represent the complete three-group trial design or account for unreported choices such as attrition assumptions, covariate adjustment, multiple comparisons, or the sponsor's model. The trial's actual primary endpoint group sizes were 52, 51, and 52. A planning figure should not be compared with those observed sizes as evidence that the trial was or was not adequately designed; the original planning rationale is not reported in the registry record.

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 = -1.420; pooled standard deviation σ = 4.047.
2. n = 2 × (1.96 + 0.842)² × 4.047² / -1.420² = 127.5, rounded up to 128 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 <- -1.42                      # observed difference in means
sigma <- 4.04739995748401                     # 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(6019559)
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 = 128 (80% power), 171 (90% power)
 75% of observed effect: n per arm = 227 (80% power), 304 (90% power)
 50% of observed effect: n per arm = 511 (80% power), 683 (90% power)
power.t.test: 128.5 
Simulated power at n = 128 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. Analyses Reported by the Sponsor

The registry reports the sponsor's primary comparisons using mixed models analysis. For placebo versus K-757 alone, the reported p-value is 0.076; for placebo versus K-757 with K-833, it is 0.001. The registry does not post the sponsor's primary estimated differences or confidence intervals, so the reported p-values do not provide those details about effect size and precision.

The unadjusted recalculations use the posted group means, standard errors, and group sizes. They estimate a mean difference of -1.42 for K-757 alone versus placebo and -2.79 for the combination versus placebo. Their unadjusted p-values are 0.075 and <0.001, respectively. These simple calculations may not match the sponsor's mixed model, which can incorporate features not available in the posted summaries.

The registry record flags a discrepancy between the recalculations and the sponsor's analysis. The sponsor's own analysis takes precedence. The recalculated results are best read as an independent, approximate check on the direction and rough scale of the posted summaries, not as a replacement for the sponsor's model or as evidence that the sponsor's analysis is incorrect. The registry does not provide the model specification needed to resolve the difference.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies the primary endpoint population as the Modified Intent-to-Treat Population and reports secondary outcome counts and comparisons. It does not fully define the Modified Intent-to-Treat Population, explain how participants were included or excluded from each analysis, or provide a flow of participants through the trial. The registry record also does not report the handling of missing measurements, withdrawals, or incomplete follow-up. No imputation method or sensitivity analysis for missing data is reported in the registry record.

These omissions matter because estimates can depend on which participants contribute data and how missing measurements are treated. In general, a treatment-policy analysis, a per-protocol analysis, and an analysis using imputation can answer different questions. Those are general methodological distinctions; the registry does not specify which missing-data assumptions or sensitivity analyses were used for the posted primary endpoint.

The sponsor reports two primary pairwise comparisons and several secondary outcomes. The registry labels the primary comparisons as superiority analyses and reports p-values, but a multiplicity strategy, prespecified testing hierarchy, or adjustment method is not reported in the registry record. Without those details, the nominal p-values should not be read as adjusted for the full set of outcomes and comparisons. This is particularly relevant for secondary outcomes, whose unadjusted results carry less evidential weight when many analyses are considered.

The registry identifies mixed models analysis for the continuous primary endpoint and absolute body-weight change, and logistic regression for the threshold weight-loss outcome. Detailed model specifications, covariates, diagnostics, interim analyses, and the full statistical analysis plan are not reported in the registry record. Nor is the original sample-size justification reported. As a result, the posted outcomes offer useful descriptive and comparative information, but they do not allow a complete reconstruction of every planned analytic decision.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent non-serious adverse event terms

The posted serious adverse-event counts are zero in each group: 0 of 52 in the placebo group, 0 of 51 in the K-757-alone group, and 0 of 52 in the combination group. The registry also reports 0 deaths in each group. These counts describe what was recorded during the reported observation period; they do not establish that serious events could not occur or that the groups have identical safety profiles.

In general, the absence of observed serious events in a relatively small group leaves uncertainty about the frequency of uncommon events. The registry's serious adverse-event summary does not list serious event terms, and the number of serious events reported is zero in all groups. The registry does not provide further detail about event definitions, adjudication, or the relationship of events to treatment. The treatment-emergent adverse-event outcome is a separate measure and uses a 15-week timeframe; these serious-event counts should not be conflated with that broader outcome.

These figures are a description of the posted safety data, not a basis for medical advice or a conclusion that a regimen is safe or unsafe. The registry record does not report detailed event narratives or additional safety analyses.

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

The posted results describe estimated group-level changes in body weight over the trial's 13-week primary endpoint period. The primary percentage-change estimates were more negative in both active-treatment groups than in the placebo group. The sponsor's reported analysis gives a p-value of 0.076 for K-757 alone versus placebo and 0.001 for the combination versus placebo. The sponsor's own analysis takes precedence over the simple unadjusted recalculations, which differ from the sponsor's reported results.

These findings do not establish what any individual participant experienced, nor do they describe weight change beyond the reported study period. An average or model-based group estimate does not reveal the full distribution of responses. The registry does not report a threshold for clinical importance, so the statistical estimates alone do not say whether a difference would be meaningful to participants. The study also does not compare these regimens with other active treatments.

The posted secondary outcomes provide additional descriptions of threshold weight loss, absolute body-weight change, and adverse events. They address related but different questions, and unadjusted secondary results carry less weight when a multiplicity plan is not reported. The serious adverse-event counts were zero in all three groups, but these observations do not rule out uncommon events or establish safety for other populations or longer use.

In general, a trial result is conditional on its participants, procedures, follow-up, measurements, and analysis assumptions. The registry record does not report enough detail to assess all of those elements, including missing-data handling, the full statistical analysis plan, and the original sample-size rationale. The results should therefore be read as estimates from this completed trial, with the reported uncertainty and limitations, rather than as a definitive answer for every setting.

18. Why This Trial Matters Statistically

This trial offers a useful example of why a reported treatment comparison should be read through several statistical lenses. The primary outcome is continuous, the secondary threshold outcome is binary, and the adverse-event outcomes are counts of participants. Each outcome type has a different scale and requires a different interpretation. A mean difference in percentage change is not the same quantity as a risk difference for a binary outcome or an adverse-event count.

The registry also illustrates the distinction between a sponsor's model-based analysis and a simple recalculation from posted group summaries. The recalculation can make the scale and uncertainty of an estimate easier to inspect, but it cannot reproduce an analysis whose full model is not reported. When the two differ, the sponsor's own analysis takes precedence, while the difference itself is a reason to be cautious about treating approximate calculations as definitive.

Finally, precision and multiplicity matter alongside the direction of an estimate. The primary groups were modest in size, and the registry does not report a multiplicity adjustment, missing-data methods, or a detailed analysis plan. These limits affect how strongly secondary findings can be interpreted and how completely the analysis can be audited. Understanding those distinctions is central to reading clinical trial results without turning a statistical signal into a broader claim than the data support.

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 leaves several trial-specific details unavailable. Arm descriptions are blank, and eligibility criteria beyond the description of participants as obese are not reported. Baseline characteristics, participant flow, adherence, withdrawals, and reasons for discontinuation are not reported in the registry record. Those details would help readers assess how the analyzed groups and follow-up relate to the randomized population.

The sponsor's primary p-values are posted, but its estimated treatment differences and confidence intervals are not. The mixed-model specification, covariates, missing-data approach, diagnostics, and sensitivity analyses are not reported in the registry record. The recalculated comparisons are based on summary statistics and are approximate; the registry flags a discrepancy, so the sponsor's own analysis takes precedence.

The original sample-size justification, assumptions for the planned analysis, and any interim analyses are not reported in the registry record. A multiplicity strategy for the several outcomes and comparisons is also not reported. Consequently, the secondary p-values cannot be assumed to account for all testing. The posted planning illustrations use observed effects and specified assumptions, not the trial's original design rationale.

The study's primary endpoint timeframe is 13 weeks, and one adverse-event outcome uses a 15-week timeframe. The registry does not explain that difference. The results therefore provide limited information about longer-term outcomes. The listed serious adverse-event counts are zero, but small group sizes and limited follow-up cannot establish the absence of uncommon or later events. Finally, the registry does not report a clinical-importance threshold for the primary outcome, leaving the practical significance of the estimated differences unspecified.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study to Evaluate the Safety, Tolerability, and Weight Loss Efficacy of K-757 Alone and in Combination With K-833 — NCT06019559.
• Registry record last updated 2025-02-26; status last verified 2025-02.
• Results first posted 2025-02-26.
• 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

NCT06019559 is a completed randomized, placebo-controlled, double-blind, parallel-group phase 2 study sponsored by TriGemX Bio, Inc. It enrolled 155 participants described as obese and compared placebo, K-757 alone, and K-757 with K-833. The registry lists quadruple masking and a 13-week primary endpoint period.

The primary endpoint was percentage change from baseline in body weight, analyzed in the Modified Intent-to-Treat Population. The posted group estimates were -0.15 for placebo, -1.57 for K-757 alone, and -2.94 for the combination. The sponsor reported mixed-model p-values of 0.076 and 0.001 for the two active-versus-placebo comparisons. Because the posted unadjusted recalculations differ, the sponsor's own analysis takes precedence.

The registry also reports secondary weight and adverse-event outcomes. Important analytic details, including the original sample-size rationale, missing-data handling, and multiplicity plan, are not reported in the registry record.