A Study of LY3437943 in Participants Who Have Obesity or Are Overweight: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of LY3437943 in Participants Who Have Obesity or Are Overweight (NCT04881760), a randomized phase 2 study. The primary outcome is Mean Percent Change From Baseline in Body Weight.

2. Clinical Question

3. Trial Design

This was a randomized, double-masked, parallel-group Phase 2 study comparing once-weekly LY3437943 with matched placebo. The official title describes participants with obesity or overweight and weight-related comorbidities. The registry record lists 338 enrolled participants and a completed status. The listed study start date is 2021-05-20 and the primary completion date is 2022-05-16. The brief summary says the study would last about 18 months and may include up to 18 visits; this describes the planned study duration and visit schedule, not the primary endpoint follow-up period.

The posted treatment groups include placebo and six LY3437943 regimens: 1 mg; 4 mg without a listed escalation; 4 mg after a 2 mg starting dose; 8 mg after a 2 mg starting dose; 8 mg after a 4 mg starting dose; and 12 mg after a 2 mg starting dose with subsequent escalation. The different schedules matter when describing what was compared: the arm labels do not all represent the same titration approach. Each group was compared with placebo in the sponsor’s reported primary endpoint analyses.

The primary endpoint timeframe was baseline to Week 24. The record also lists a Week 48 body-weight outcome and several threshold-based outcomes at Week 24. These are distinct follow-up measures, not substitutes for the primary endpoint. The registry record does not report the original sample-size justification, the allocation ratio, or further operational details beyond the stated randomized, double-masked, parallel design and listed interventions. The record describes an analysis population and a repeated-measures model for the primary endpoint, but further details about conduct and analysis should not be inferred from the design labels alone.

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: Four maintenance doses of LY3437943 were evaluated in the trial: 1, 4, 8, and 12 milligrams (mg). Dose escalation to improve gastrointestinal (GI) tolerability occured in certain treatment groups up to Week 12 by increasing the volume of administered study drug (or placebo) during the 48-week double-blind, placebo-controlled treatment period.

Only the first 6 of 7 groups are shown.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: All randomized participants who had baseline and at least one post-baseline body weight value, excluding participants discontinuing study drug due to inadvertent enrollment and data after discontinuation of study drug.

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 participants.

Only the first 6 of 8 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Mean Percent Change From Baseline in Body Weight, measured over Baseline, Week 24.

The primary endpoint is mean percent change from baseline in body weight at Week 24. It expresses change relative to each participant’s baseline weight, then summarizes the modeled average within each treatment group. A negative value denotes a decrease from baseline. The posted arm estimates are least-squares means, rather than simple arithmetic averages, because the registry describes a mixed-effects model for repeated measures.

Percent change is useful in a study where participants may begin at different body weights: it puts change on a relative scale rather than reporting only a change in weight units. Comparing each LY3437943 group with placebo helps distinguish the pattern associated with assignment to a study regimen from change observed in the placebo group during the same period. The endpoint is a group-level summary, however; it does not describe every participant’s individual trajectory or establish what caused any particular participant’s change.

The registry defines the primary analysis population as randomized participants with a baseline and at least one post-baseline body-weight value, excluding participants who discontinued study drug due to inadvertent enrollment and data after study-drug discontinuation. The primary model includes treatment and time, baseline BMI category by time, sex by time, and baseline body weight by time. The record identifies the endpoint and model, but further details of the model specification and missing-data handling are not reported in the registry record. Interpretation should therefore remain anchored to the stated population, Week 24 timeframe, and adjusted mean comparison.

7. Results Posted in the Registry

• 1 mg LY3437943: mean -7.18 versus -1.55 on control; difference -5.63 (95% CI -7.32 to -3.94), standardized effect d = -1.12; z-test p = <0.001.
• 4 mg LY3437943 (2 mg): mean -12.00 versus -1.55 on control; difference -10.45 (95% CI -12.20 to -8.70), standardized effect d = -2.41; z-test p = <0.001.
• 4 mg LY3437943: mean -13.80 versus -1.55 on control; difference -12.25 (95% CI -14.43 to -10.07), standardized effect d = -2.53; z-test p = <0.001.
• 8 mg LY3437943 (2 mg): mean -16.64 versus -1.55 on control; difference -15.09 (95% CI -16.89 to -13.29), standardized effect d = -3.41; 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.

Mean Percent Change From Baseline in Body Weight

• 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:
  • 1 mg LY3437943: mean -8.67 versus -2.11 on control; difference -6.56 (95% CI -8.91 to -4.21), standardized effect d = -0.93; z-test p = <0.001.
  • 4 mg LY3437943 (2 mg): mean -16.32 versus -2.11 on control; difference -14.21 (95% CI -17.62 to -10.80), standardized effect d = -1.99; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for 1 mg LY3437943 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 mean is statistically lower for 4 mg LY3437943 (2 mg) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Participants Who Achieve ≥ 5% Body Weight Reduction

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • 1 mg LY3437943: 59.4% (41/69) versus 26.5% (18/68) on control; risk difference 32.9 percentage points (95% CI 17.3 to 48.6), risk ratio 2.24 (1.44–3.49); unadjusted two-proportion z-test p = <0.001.
  • 4 mg LY3437943 (2 mg): 87.9% (29/33) versus 26.5% (18/68) on control; risk difference 61.4 percentage points (95% CI 46.1 to 76.7), risk ratio 3.32 (2.19–5.03); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for 1 mg LY3437943 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 4 mg LY3437943 (2 mg) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Participants Who Achieve ≥ 10% Body Weight Reduction

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • 1 mg LY3437943: 24.6% (17/69) versus 2.9% (2/68) on control; risk difference 21.7 percentage points (95% CI 10.8 to 32.6), risk ratio 8.38 (2.01–34.88); unadjusted two-proportion z-test p = <0.001.
  • 4 mg LY3437943 (2 mg): 57.6% (19/33) versus 2.9% (2/68) on control; risk difference 54.6 percentage points (95% CI 37.3 to 72.0), risk ratio 19.58 (4.84–79.10); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for 1 mg LY3437943 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 4 mg LY3437943 (2 mg) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Across the posted secondary outcomes, the overall pattern is consistent with the primary endpoint: group-level body-weight changes and the proportions reaching specified reduction thresholds tend to be more pronounced in the LY3437943 groups than in placebo. The outcomes extend the description to a later body-weight assessment and to categorical thresholds, adding different views of the same broad domain. They should be considered complementary to, rather than replacements for, the Week 24 primary comparison.

Secondary endpoints answer additional questions and can help show whether the primary pattern is reflected across related measures. However, multiple outcomes and multiple group comparisons create more opportunities for apparently strong results to arise by chance. The registry record does not report a multiplicity adjustment strategy for the secondary outcomes. Unadjusted p-values and intervals therefore carry less confirmatory weight than would results from a clearly prespecified and controlled testing plan. They are best read as supportive or exploratory evidence, not as a set of independent confirmations.

The record lists 14 outcome measures and 84 analyses, while 13 secondary outcomes are posted. Not every listed outcome necessarily has a posted result or the same degree of detail. The registry record does not report why some results are absent from the posted secondary analyses, or whether they were omitted, not collected, or not reported. The available secondary findings should therefore be interpreted in light of that incomplete reporting context, without assuming that the posted results exhaust the study’s planned comparisons.

Correlated endpoints also should not be treated as independent replications. Percent change and threshold achievement both reflect body-weight outcomes, but they summarize those outcomes differently. Agreement across them can add context, while the shared underlying measure means the pattern is not equivalent to confirmation from unrelated outcomes. The central inferential result remains the sponsor-reported primary endpoint analysis, with secondary results offering additional but less certain context.

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

• Mean Percent Change From Baseline in Body Weight
• Percentage of Participants Who Achieve ≥ 5% Body Weight Reduction
• Percentage of Participants Who Achieve ≥ 5% Body Weight Reduction
• Percentage of Participants Who Achieve ≥ 10% Body Weight Reduction
• Percentage of Participants Who Achieve ≥ 10% Body Weight Reduction
• Percentage of Participants Who Achieve ≥ 15% Body Weight Reduction
• Percentage of Participants Who Achieve ≥ 15% Body Weight Reduction
• Mean Change From Baseline in Body Weight

9. Statistical Interpretation

10. Statistical Methods Explained

The primary analysis uses a mixed-effects model for repeated measures (MMRM). In general, repeated-measures methods use observations collected at multiple follow-up times while accounting for the fact that measurements from the same participant are related. Rather than treating each measurement as independent, the model estimates treatment and time patterns across the scheduled measurements. The record says that least-squares means were calculated from post-baseline measures. A least-squares mean is a model-based group estimate adjusted for the covariates and terms included in the model; it need not equal a plain average of the observations.

What does the model adjust for?

The registry description lists treatment by time, baseline BMI category by time, sex by time, and baseline body weight by time. In general, covariate adjustment can account for specified participant characteristics and can improve comparability of modeled estimates when those characteristics are associated with the outcome. The model uses BMI categories divided at 36 kg/m2, sex categories of female and male, and baseline body weight. The record does not report additional adjustment terms or enough detail to reconstruct all model assumptions from the description alone.

How should the mean difference be read?

The reported sponsor parameter is the least-squares mean difference in final values for each LY3437943 group versus placebo. A negative difference indicates a lower modeled percent change in the active-treatment group than in the placebo group. Because the outcome is percent change from baseline, the contrast is a difference on that percent-change scale, not a ratio of body weights. The sponsor’s estimate and confidence interval are the primary reported inferential results; simple recalculations from arm-level means and standard errors are approximate, unadjusted contrasts and do not replicate the full repeated-measures model.

What does a p-value convey?

In general, a p-value measures how incompatible the observed data are with a specified null hypothesis under the analysis assumptions. A small p-value is not the probability that the null hypothesis is true, and it does not describe the size or importance of an effect. The sponsor reports p < 0.001 for each primary comparison. These are the registry’s reported tests; the record does not report whether or how the primary comparisons were adjusted for multiple testing.

Why do standard errors matter?

A standard error describes uncertainty in an estimated mean, with smaller standard errors generally indicating more precise estimates under the model. The arm estimates list standard errors, not standard deviations. In general, a standard deviation describes variability among individual observations, while a standard error describes uncertainty around an estimate. Converting the posted standard errors into an approximate pooled standard deviation for a simple recalculation requires assumptions and does not recreate participant-level data or the MMRM. Those recalculations are therefore best treated as descriptive checks, not replacements for the sponsor’s model-based results.

What assumptions underlie the recalculations?

The unadjusted recalculated mean differences compare the posted arm-level means and use approximate variability derived from the reported standard errors. They do not incorporate the repeated-measures covariance structure, the covariate terms, or the specified primary analysis population in the same way as the sponsor model. Their confidence intervals and p-values may therefore differ slightly from the sponsor’s reported values. The sponsor’s own analysis remains the relevant primary analysis; the recalculations provide a transparent, simplified comparison rather than an alternative trial analysis.

What cannot be concluded from the method description?

The registry record does not report details of the covariance structure, estimation procedure, degrees-of-freedom method, or the assumptions used for missing observations. It also does not report the original design’s sample-size justification or whether interim analyses were planned or conducted. General descriptions of MMRM do not establish which specific technical choices were used. Where these details are absent, the result should be interpreted from the stated analysis population, endpoint, and sponsor-reported estimates rather than filling gaps with assumptions.

11. Confidence Intervals and Precision

Confidence intervals express uncertainty around an estimated contrast. In general, a 95% confidence interval is produced by a procedure that, under its assumptions, would cover the target parameter in 95% of repeated applications. It is not a range guaranteed to contain the true value in this particular study, and it does not describe the spread of individual participant outcomes.

For the primary endpoint, the sponsor’s 95% confidence intervals for the mean differences were -7.34 to -3.94 for 1 mg LY3437943; -12.21 to -8.70 for 4 mg LY3437943 (2 mg); -14.42 to -10.08 for 4 mg LY3437943; -16.90 to -13.30 for 8 mg LY3437943 (2 mg); -18.86 to -14.58 for 8 mg LY3437943 (4 mg); and -17.57 to -14.13 for 12 mg LY3437943 (2 mg). Each interval lies below zero. The intervals also show that the estimated size of each contrast is not known exactly: plausible values span a range around its point estimate.

The sponsor’s reported estimates and intervals differ slightly from simple unadjusted recalculations using the posted arm summaries. This is expected when the underlying model-based analysis is compared with an approximation that does not reproduce its repeated-measures structure and covariate adjustment. The sponsor results are the primary reported inferential estimates. The registry record does not provide intervals for the individual arm-level means, and the standard errors listed for those means should not be mistaken for confidence limits.

Interval width reflects both the observed variability and the amount of information available under the analysis. A narrow interval indicates greater precision for the estimated contrast, not certainty about individual responses or all possible populations. Statistical precision also does not address unreported analysis choices, multiplicity, or missing-data assumptions. Those are separate considerations when judging how much weight to place on the results.

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 sample-size planning illustrations are expressed as participants per arm, not total participants, for the continuous and binary comparisons shown. The stated calculation assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect targeted is the stated fraction of the observed effect. For time-to-event outcomes, the convention would instead be total events, but the listed outcomes in this record are not time-to-event outcomes. The registry record does not report the assumptions used for the trial’s original design or its sample-size justification.

The 80% power column gives the illustrative number of participants per arm that would yield an 80% chance of detecting the chosen effect under the calculation assumptions, if that effect and the assumptions were correct. The 90% power column uses a higher probability of detection and generally calls for more participants per arm. These are planning calculations, not descriptions of the study’s observed statistical power. The calculations are based on the observed effects, so they do not independently establish what effect future research should expect.

Rows based on 100%, 75%, and 50% of the observed effect illustrate how planning changes when the effect to detect is smaller than the observed estimate. A smaller target effect is harder to distinguish from random variation, so more participants are needed under otherwise fixed assumptions. These illustrations do not account for every practical design feature, such as attrition or any multiplicity strategy. They should be read as conditional planning examples rather than recommendations or a reconstruction of the trial’s actual design decisions.

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 = -5.630; pooled standard deviation σ = 5.044.
2. n = 2 × (1.96 + 0.842)² × 5.044² / -5.630² = 12.6, rounded up to 13 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 <- -5.63                      # observed difference in means
sigma <- 5.04407859662088                     # 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(4881760)
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 = 13 (80% power), 17 (90% power)
 75% of observed effect: n per arm = 23 (80% power), 30 (90% power)
 50% of observed effect: n per arm = 51 (80% power), 68 (90% power)
power.t.test: 13.6 
Simulated power at n = 13 per arm: 0.781 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The sponsor’s primary analysis is a mixed-model comparison of each LY3437943 regimen with placebo. It reports least-squares mean differences, 95% confidence intervals, and p-values. For example, the sponsor estimate for 1 mg LY3437943 was -5.64, with a 95% confidence interval from -7.34 to -3.94 and p < 0.001. For 8 mg LY3437943 (4 mg), the reported estimate was -16.72, with a 95% confidence interval from -18.86 to -14.58 and p < 0.001. Each other reported primary contrast was also negative with p < 0.001.

Simple recalculations from the posted arm summaries are close to the sponsor estimates but are not identical. For instance, the recalculated difference for 1 mg is -5.63, and for 8 mg LY3437943 (4 mg) it is -16.71. These recalculations use an approximate unadjusted method and do not reproduce the sponsor’s full repeated-measures model. The registry record does not flag a discrepancy. The sponsor’s own model-based analysis takes precedence for interpreting the primary comparisons; the recalculations serve only as approximate checks on the direction and scale of the posted results.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when many hypotheses are tested. In general, as the number of comparisons grows, the chance of at least one apparently significant result can increase if no adjustment or prespecified testing hierarchy is used. This concern is relevant to a trial with multiple LY3437943 groups, several secondary outcomes, and many analyses. The registry record lists 14 outcome measures and 84 analyses, and 13 secondary outcomes are posted. Those counts indicate a broad analysis set, but do not reveal which outcomes were formally designated confirmatory or how testing was organized.

The sponsor reports p < 0.001 for each primary placebo comparison, but the registry record does not report whether adjustment for multiple primary comparisons was applied. A formal correction, a hierarchical strategy, or another control of family-wise error cannot be assumed. Likewise, the record does not report a multiplicity procedure for the secondary outcomes. This absence does not change the numerical estimates, but it limits interpretation of p-values as confirmatory evidence across the full set of comparisons.

The registry describes the primary analysis population: randomized participants with a baseline and at least one post-baseline body-weight value, excluding participants who discontinued study drug because of inadvertent enrollment and excluding data after study-drug discontinuation. This is important because results pertain to that defined population and analysis approach, not automatically to every randomized participant at every follow-up. The record does not report enough detail to establish how missing body-weight observations were handled in the model or what assumptions were made about missingness.

MMRM is commonly used to analyze repeated measurements, and in general it can use available post-baseline observations under specified modeling and missing-data assumptions. That general property does not establish the assumptions or sensitivity analyses used in this study. The registry record does not report sensitivity analyses for missing data, a detailed disposition of missing observations for the primary endpoint, or the original sample-size rationale. It also does not report interim analyses. These gaps should be treated as limits on what can be assessed from the registry, not as evidence that a particular procedure was or was not used.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: drowning (3.0%), clear cell renal cell carcinoma (3.0%), cerebrovascular accident (2.9%), cardiac failure (2.9%), vomiting (2.9%).

The posted adverse-event summaries distinguish serious adverse events from other adverse events. For serious events, the registry lists 3 participants in the placebo group, 3 in the 1 mg group, 0 in the 4 mg group with a 2 mg starting dose, 2 in the 4 mg group, 1 in the 8 mg group with a 2 mg starting dose, 2 in the 8 mg group with a 4 mg starting dose, and 2 in the 12 mg group with a 2 mg starting dose. The record lists 1 death in the 4 mg LY3437943 group; the other groups list 0 deaths.

These counts describe what was recorded in the safety summaries; they do not establish that an event was caused by a study treatment. The listed serious-event terms include Drowning and Clear cell renal cell carcinoma at 3.0% each, and Cerebrovascular accident, Cardiac failure, Vomiting, and Cholecystitis acute at 2.9% each. The record does not provide enough context in these summaries to determine the circumstances or treatment relationship for each event.

Safety counts should be read alongside the group-specific numbers at risk, which differ among treatment arms, and should not be converted into an overall total across arms. They are not a substitute for detailed clinical review or a complete benefit-risk assessment. The registry record gives these aggregate counts but does not report further case-level detail in the information summarized for these outcomes.

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

The results show that, in the primary analysis population, the sponsor’s modeled mean percent change in body weight at Week 24 was lower in each LY3437943 group than in placebo. The sponsor-reported mean differences were negative, their 95% confidence intervals were below zero, and each reported p-value was <0.001. These statements describe the posted estimates and statistical comparisons for this trial.

They do not show that every participant experienced a decrease, nor do group averages predict an individual participant’s outcome. The primary endpoint is one measure at one follow-up timeframe, and its model-based estimate reflects the defined analysis population and the stated repeated-measures model. The record also includes different dose and escalation schedules; the placebo comparisons do not establish a direct ranking of active regimens.

The findings do not establish results beyond the study population and follow-up represented in the record. They do not, by themselves, answer questions about durability beyond the posted timeframes, other outcomes not reported, or people who differ from participants described in the eligibility context. The registry record does not report the original sample-size justification, detailed missing-data sensitivity analyses, or a multiplicity strategy, all of which limit how fully the strength and scope of inference can be assessed.

Statistical significance is not equivalent to clinical importance, and the posted estimates alone do not determine whether a particular change is meaningful for a person. The information presented is a statistical account of a clinical trial, not medical advice. Interpretation should distinguish the observed group-level pattern from causal claims or conclusions not directly tested by the reported comparisons.

18. Why This Trial Matters Statistically

This trial is statistically informative because it reports several randomized comparisons against a placebo group using a defined continuous primary endpoint and a repeated-measures model. The sponsor’s least-squares mean contrasts provide an adjusted comparison over the primary follow-up, while arm-level estimates and standard errors allow readers to understand the scale and uncertainty of the group summaries. The consistency in direction across the reported primary comparisons is a notable feature of the posted results.

At the same time, the design creates important interpretation questions. Each active regimen is compared with placebo, rather than being presented as a direct randomized comparison with another active regimen. The dose arms also include different starting and escalation schedules. Thus, an apparent ordering of group estimates should not be treated as a formal test of differences between active strategies.

The registry record is also a useful example of why an estimate, confidence interval, p-value, analysis population, and model specification belong together. A small p-value indicates evidence against a null contrast under the analysis assumptions, while the confidence interval conveys uncertainty in the magnitude. Neither resolves missing-data assumptions or multiplicity. Here, those details are not fully reported in the registry record, even though the primary model and analysis population are described.

Finally, planning illustrations based on observed effects emphasize that sample-size needs depend on the effect a future study aims to detect. They are conditional calculations, not a reconstruction of the original design. Keeping planning assumptions distinct from the trial’s actual design rationale helps prevent post hoc estimates from being mistaken for prospective justification or observed power.

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.

Several limitations specific to this trial affect interpretation of the posted results. The primary endpoint is a modeled mean at Week 24, and the analysis population excludes certain participants and post-discontinuation data as described in the registry. The available information does not give a full account of participant-level missingness or sensitivity analyses, so the robustness of the result to alternative missing-data assumptions cannot be assessed from the registry record.

The sponsor reports separate primary comparisons of each LY3437943 regimen with placebo. The posted primary analysis does not establish a direct comparison between active regimens. Different starting doses and escalation schedules further complicate any simple interpretation of the arm estimates as a dose-response sequence. Group estimates can describe a pattern, but do not substitute for a prespecified active-arm contrast.

The study has multiple outcome measures and analyses. The registry record does not report a multiplicity adjustment strategy, so secondary p-values and the full collection of comparisons warrant caution. Not all listed secondary outcomes have posted results in the record. The reason for the gap is not reported in the registry record.

The original sample-size justification, interim analysis plan, and detailed model implementation are not reported in the registry record. The calculations based on observed effects are planning illustrations and cannot fill those gaps. Finally, the registry summaries do not provide enough detail to assess the clinical context of individual serious adverse events or their relationship to treatment. These limitations narrow what can be concluded from the posted aggregate data; they do not negate the reported estimates.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study of LY3437943 in Participants Who Have Obesity or Are Overweight — NCT04881760.
• Registry record last updated 2023-09-13; status last verified 2023-08.
• Results first posted 2023-09-13.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The registry record describes a completed randomized, double-masked, parallel-group Phase 2 study of once-weekly LY3437943 versus matched placebo in participants with obesity or overweight and weight-related comorbidities. Enrollment was 338. The primary endpoint was mean percent change from baseline in body weight at Week 24, analyzed using a mixed-effects model for repeated measures in a defined analysis population.

The sponsor reported negative mean differences for each LY3437943 group versus placebo, with 95% confidence intervals below zero and p < 0.001 for each comparison. Secondary measures provide additional body-weight context, but multiplicity and missing-data details are not fully reported in the registry record. Simple recalculations are approximate and do not replace the sponsor’s model-based analysis.