Study to Evaluate the Efficacy, Safety and Tolerability of Bupropion Hydrochloride Extended-release Tablet, and Escitalopram Oxalate Capsule in Subjects With Major Depressive Disorder: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Evaluate the Efficacy, Safety and Tolerability of Bupropion Hydrochloride Extended-release Tablet, and Escitalopram Oxalate Capsule in Subjects With Major Depressive Disorder (NCT02191397), a randomized phase 3 study. The primary outcome is Mean Change in Hamilton Depression Rating Scale - 17 (HAMD-17) Total Score From Baseline to End of Acute Treatment Phase (Week 8).

2. Clinical Question

3. Trial Design

This completed Phase 3 study used randomized allocation, double blinding, and a parallel-group, active-controlled design. The registry describes a total study duration of 11 weeks: screening for 0-14 days, an 8-week acute treatment phase, and a taper phase of up to 1 week. During acute treatment, participants were randomized in a 1:1 ratio to bupropion XL or escitalopram. The record describes three dose levels for each treatment and matching placebo to help maintain blinding.

The brief summary identifies the study population as inpatients and outpatients with major depressive disorder. It describes bupropion XL at 300 mg/day and escitalopram at 10-20 mg/day. The stated context was evaluation of bupropion XL for registration in China, where the summary says it had not yet been approved at the time described. GlaxoSmithKline is listed as the sponsor.

The primary endpoint was assessed at baseline and Week 8. Its analysis population was not everyone enrolled: the registry specifies a Per Protocol population drawn from the Intent-To-Treat population, subject to compliance, treatment-duration, assessment, and protocol-deviation criteria. The primary analysis method was mixed model repeated measures. The randomization sequence method, any stratification factors, and the original design’s sample-size assumptions 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.

Before assignment: The study had screening phase (up to 14 days), 8-week double blind treatment phase and taper phase (up to 1 week). A total of 655 participants were screened and 538 were randomized into the study. 4 participants were randomized but discontinued prior to receiving any study treatment. Hence, the Safety Population was comprised of 534 participants.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: PP 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.

6. Primary Endpoint

The registry lists the primary outcome as Mean Change in Hamilton Depression Rating Scale - 17 (HAMD-17) Total Score From Baseline to End of Acute Treatment Phase (Week 8), measured over Baseline (Week 0) and Week 8.

The primary endpoint is mean change in HAMD-17 total score from baseline to the end of acute treatment at Week 8. HAMD-17 is a 17-question rating measure used to assess depression severity and symptom change. The total is formed by summing item responses when none are missing; the stated scale ranges from 0, meaning not present, to 52, meaning severe. Change is calculated as the Week 8 score minus the baseline score, so a negative change represents a lower score at Week 8.

The endpoint focuses on average change over the acute treatment period, rather than only on whether a participant crossed a response or remission threshold. Comparing average changes can retain information across the score scale, while response and remission outcomes answer threshold-based questions. The registry reports least-squares means and standard errors for the primary endpoint, reflecting a model-based analysis rather than simply presenting unadjusted group averages.

The endpoint is clinically interpretable as a change in a symptom-rating score, but the score alone does not describe every aspect of a participant’s experience. The registry’s primary analysis population was Per Protocol, and only participants with data available at a specified time point were included in that time-point analysis.

7. Results Posted in the Registry

• Escitalopram: mean -15.40 versus -14.50 on control; difference -0.90 (95% CI -2.01 to 0.21), standardized effect d = -0.17; z-test p = 0.112.

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.

Response Rate Based on HAMD-17 Total Score

• 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:
  • Escitalopram: 72.9% (145/199) versus 69.6% (128/184) on control; risk difference 3.3 percentage points (95% CI -5.8 to 12.4), risk ratio 1.05 (0.92–1.19); unadjusted two-proportion z-test p = 0.476.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Escitalopram and the control. The interval gives the range of effects that remain compatible with the data.

Remission Rate Based on HAMD-17 Total Score

• 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:
  • Escitalopram: 47.2% (94/199) versus 39.7% (73/184) on control; risk difference 7.6 percentage points (95% CI -2.3 to 17.5), risk ratio 1.19 (0.95–1.50); unadjusted two-proportion z-test p = 0.136.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Escitalopram and the control. The interval gives the range of effects that remain compatible with the data.

Sustained Response Rate Based on HAMD-17 Total Score

• 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:
  • Escitalopram: 56.3% (112/199) versus 51.6% (95/184) on control; risk difference 4.7 percentage points (95% CI -5.3 to 14.6), risk ratio 1.09 (0.91–1.31); unadjusted two-proportion z-test p = 0.362.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Escitalopram and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcomes include HAMD-17 response, remission, and sustained response. Across these outcomes, the Escitalopram arm has higher reported percentages than the Bupropion XL arm, while the recalculated comparisons remain uncertain and their intervals span no difference. The sponsor’s corresponding generalized estimating equation analyses likewise do not report clear evidence of a between-group difference at conventional significance levels. These outcomes offer related views of symptom thresholds, but they are not interchangeable with the primary analysis of mean score change.

The secondary outcomes are consistent with a pattern in which the group estimates are not identical, but the uncertainty is substantial enough that the posted results do not establish a clear difference. Their interpretation also depends on how response, remission, and sustained status were defined; the complete operational definitions are not reported with the results summarized in the registry record.

Unadjusted secondary results carry less weight because many outcomes and analyses are reported. When many comparisons are examined, a nominally notable result can arise by chance even when no corresponding effect exists. The registry record does not report a multiplicity adjustment or a hierarchy assigning confirmatory status to particular secondary outcomes. These results are best viewed as supportive or exploratory context for the primary endpoint, not as independent confirmation of a treatment effect.

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

• Response Rate Based on HAMD-17 Total Score
• Remission Rate Based on HAMD-17 Total Score
• Sustained Response Rate Based on HAMD-17 Total Score
• Sustained Remission Rate Based on HAMD-17 Total Score
• Change From Baseline in Montgomery-Asberg Depression Rating Scale (MADRS) Total Score at Weeks 1, 2, 4, 6 and 8
• Change From Baseline in HAMD-17 Depressed Mood Subscale Score (Score of Item 1) at Weeks 1, 2, 4, 6 and 8
• Change From Baseline in HAMD-17 Anxiety/Somatization Subscale Score (Sum of Scores of Items 10, 11, 12, 13, 15 and 17) at Weeks 1, 2, 4, 6 and 8
• Change From Baseline in HAMD-17 Retardation Subscale Score (Sum of Scores of Items 1, 7, 8 and 14) at Weeks 1, 2, 4, 6 and 8

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: it is a score change measured on a numerical scale. The registry reports least-squares means, which are model-based group estimates, with standard errors that describe the estimated sampling uncertainty of those means. A standard error is not the same as the spread of individual participant scores. It describes the precision of an estimated mean under the analysis model.

What does mixed model repeated measures mean?

The sponsor’s primary method is mixed model repeated measures analysis. In general, this type of model can use repeated outcome measurements over time and account for the fact that measurements from the same participant are related. It estimates group patterns while using the available measurements included in the analysis. The registry says that participants in the Per Protocol population were included and that only participants with data available at the specified time point were analyzed. The model’s exact covariance structure, included covariates, and handling of missing observations are not reported in the registry record.

The primary outcome description defines the Per Protocol population as randomized participants in the Intent-To-Treat population who did not meet criteria for a major protocol deviation, had active-drug compliance in the range of 75%-125% during acute treatment, completed the first 6 weeks of treatment, and had a HAMD-17 assessment at or after week 6, meaning at least 35 days. Thus, the primary analysis does not represent an unrestricted analysis of every enrolled participant. The record does not give the specific counts excluded under each criterion.

How should the mean difference be read?

The recalculated contrast uses the posted arm-level means and standard errors to estimate an unadjusted difference, with Escitalopram minus Bupropion XL as the direction. It is a simple comparison of summary statistics, not a reconstruction of the sponsor’s repeated-measures model. The recalculated standard deviation is approximate because it is inferred from standard errors and group sizes, rather than obtained from participant-level data. The standardized effect size is also a summary of this unadjusted contrast and should not be treated as a model-based clinical conclusion.

The sponsor’s reported mean difference is labeled as a difference in final values and comes from mixed model repeated measures analysis. This is a different analysis from the recalculation. The registry record does not report the non-inferiority margin, so the estimate and confidence interval cannot be compared with that margin using the posted information. The sponsor’s non-inferiority designation should therefore be read as the reported analysis classification, not as a margin that can be independently checked from the record.

Why are secondary outcomes analyzed differently?

Response and remission are binary outcomes: each participant either meets the outcome definition or does not. Their percentages describe the proportion meeting the criterion among the analyzed participants. The registry reports sponsor analyses using a generalized estimating equation model for odds ratios. In general, odds ratios compare the odds of an outcome between groups; they are not the same quantity as a difference in percentages. The registry does not provide every definition detail for the response and remission criteria in the results information summarized for these outcomes.

The recalculated binary comparisons use unadjusted risk differences from posted event counts and denominators. A risk difference expresses the difference between group proportions in their original percentage-point scale. The sponsor’s odds-ratio analysis and the recalculated risk difference answer related but not identical statistical questions. Their estimates can differ because they use different measures and analysis approaches.

General statistical note: models for binary data and continuous scores make different assumptions about how outcomes vary. If binary outcomes exhibit more variation than the model expects, standard errors and tests can be affected; approaches that account for dependence or extra variation can help address this. The registry identifies a generalized estimating equation model for the sponsor’s binary outcome analyses, but details of its working correlation structure and other specifications are not reported.

The record lists 27 outcome measures and 40 analyses, and 26 secondary outcomes are posted. Multiple outcomes raise the chance that some comparisons may appear notable by chance alone. Whether the sponsor adjusted for multiplicity, and the specific statistical plan for doing so, are not reported in the registry record. The statistical significance of any single secondary comparison should therefore be interpreted in the context of the wider set of analyses.

11. Confidence Intervals and Precision

A confidence interval describes a range of estimates that are reasonably compatible with the observed data under the analysis assumptions. It is not a guarantee that the true effect lies in the interval, and its width communicates precision: narrower intervals indicate more precise estimates, while wider intervals indicate greater uncertainty.

For the recalculated primary comparison, the interval extends from -2.009 to an upper limit just above zero. Because it includes zero, the posted summary statistics are compatible with no mean difference as well as with differences in either direction within the interval. The unadjusted p-value of 0.112 is consistent with that uncertainty. The estimated contrast is therefore not precise enough to establish a clear difference between groups through this recalculation.

The sponsor-reported primary analysis has a 95% confidence interval from -0.27 to 1.94. It also spans zero. This interval belongs to the sponsor’s model-based estimate and should not be treated as though it were the interval for the recalculated contrast: the analyses differ in method and reported estimate. The non-inferiority margin is not reported in the registry record, so the interval cannot be evaluated against that criterion from the record alone.

Secondary outcome intervals also indicate uncertainty. The recalculated intervals for the posted binary comparisons span no difference, and the sponsor-reported odds-ratio intervals include the null odds ratio of 1. General interpretation: an interval that includes a null value does not prove that there is no effect; it means the data do not rule out that value under the analysis used. The registry does not report confidence intervals for every outcome or a multiplicity-adjusted interval procedure.

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 original sample-size design. For the continuous primary comparison and the binary comparisons shown, the figures are participants per arm, not total participants or total events. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The assumed effect to detect is the stated fraction of the observed effect. The original trial’s sample-size justification and design assumptions are not reported in the registry record.

The 80% power column describes a planning scenario in which a study of the stated size would have an 80% chance of detecting the assumed effect under the planning assumptions, if that effect were the true one. The 90% power column uses a higher chance of detecting that same assumed effect and therefore gives a larger participant requirement. These are hypothetical design calculations; this is not observed power.

Planning for 75% or 50% of the observed effect means asking how large a study would need to be to detect a smaller effect than the one estimated in this trial. Smaller effects are harder to distinguish from random variation, so they require more participants under the same assumptions. The sample-size figures are sensitive to the observed effect used as their starting point; they do not establish that a future study will reproduce that effect. They are useful for comparing planning scenarios, not for retrospectively judging whether the completed trial was adequately powered under its actual design.

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 = -0.900; pooled standard deviation σ = 5.392.
2. n = 2 × (1.96 + 0.842)² × 5.392² / -0.900² = 563.4, rounded up to 564 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 <- -0.9                      # observed difference in means
sigma <- 5.39201056198451                     # 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(2191397)
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 = 564 (80% power), 755 (90% power)
 75% of observed effect: n per arm = 1,002 (80% power), 1,341 (90% power)
 50% of observed effect: n per arm = 2,254 (80% power), 3,018 (90% power)
power.t.test: 564.4 
Simulated power at n = 564 per arm: 0.802 (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-reported primary analysis is a mixed model repeated measures comparison of final values and is labeled non-inferiority. It reports a mean difference of 0.8, a 95% confidence interval from -0.27 to 1.94, and p = 0.139. The registry does not report the non-inferiority margin or enough detail to independently reconstruct the sponsor’s decision rule.

The recalculated result is an unadjusted mean difference of -0.9, with an interval that includes zero and an unadjusted p-value of 0.112. It is derived from the posted arm-level means and standard errors, with an approximate standard deviation, rather than participant-level data or the sponsor’s full model. The sponsor’s estimate and the recalculation therefore should not be expected to match exactly or be interpreted as identical tests. The registry record reports no discrepancy flag, but the distinction in methods and estimands remains important.

The sponsor analysis is the trial’s reported formal analysis; the recalculation is a transparent, simple comparison of posted summaries. Neither a non-significant p-value nor an interval spanning zero proves equivalence. Without the margin and analysis details, the non-inferiority designation cannot be independently assessed from the registry record alone.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists multiple outcome measures and analyses, including a primary continuous endpoint and several secondary outcomes. Each additional comparison creates another opportunity for a chance finding. In general, multiplicity procedures control the overall chance of false-positive conclusions across a defined family of tests, but they can also affect the precision or power of individual comparisons. Whether such procedures were used, which outcomes formed any testing families, and whether testing followed a hierarchy are not reported in the registry record.

Missing-data handling is also relevant. The primary outcome description says that only participants with data available at the specified time point were analyzed, within the Per Protocol population. The record does not specify the amount or reasons for missing outcome data, whether values were imputed, or the assumptions used about missingness. General statistical note: analyses can be affected when the chance of missing data is related to participant characteristics or outcomes. The posted description does not allow that possibility to be evaluated.

The primary analysis population has additional eligibility criteria beyond randomization, including the stated compliance range, treatment duration, assessment timing, and absence of a major protocol deviation. Those criteria define the population whose primary result is reported, but the registry does not provide counts or outcome information for participants excluded from that analysis. The secondary outcome counts differ from the primary analysis counts, and the reason for each difference is not reported in the registry record.

The randomization method, allocation concealment details, interim analyses, protocol deviations by group, original sample-size rationale, and complete statistical analysis plan are not reported in the registry record. Their absence limits independent assessment of design and analysis choices; it does not by itself show that a particular method 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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: depression (1.5%), depression suicidal (0.4%), lacrimal structure injury (0.4%), overdose (0.4%), somatic symptom disorder (0.4%).

The registry reports serious adverse events for 10 of 266 participants at risk in the Bupropion XL group and 11 of 268 at risk in the Escitalopram group. It separately reports other adverse events for 151 of 266 and 150 of 268 participants at risk, respectively. Deaths are recorded as 1 in the Bupropion XL group and 0 in the Escitalopram group.

These are descriptive counts with their stated at-risk denominators. They do not by themselves establish that an event was caused by a treatment, and the registry summary does not provide the timing, duration, severity details, or participant-level overlap among event categories. The listed serious-event terms include Depression at 1.5%, and Depression suicidal, Lacrimal structure injury, Overdose, Somatic symptom disorder, and Tinnitus at 0.4% each. Those terms describe reported categories, not necessarily unique participants.

Safety counts should be read in the context of the trial’s duration, population, and event reporting. The registry does not provide enough information in these summaries to compare the full safety profiles or infer uncommon risks.

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

The posted primary data show mean HAMD-17 score decreases in both treatment groups from baseline to Week 8. The recalculated between-group estimate is small and uncertain, with an interval spanning no difference. The sponsor’s model-based result is also reported with a confidence interval spanning zero and is designated as a non-inferiority analysis. These findings describe the registry results; they do not establish that the treatments are identical or that either treatment does or does not work.

A non-significant comparison is not proof of equivalence. A non-inferiority conclusion depends on a prespecified margin and analysis conditions, and the margin is not reported in the registry record. The sponsor’s label is therefore reportable, but the posted material does not allow independent verification of the criterion used to reach it.

The secondary outcomes address threshold-based response and remission measures, in addition to sustained outcomes. Their group estimates are not conclusive, and the unadjusted results should be interpreted cautiously because multiple outcomes were examined. Safety summaries provide event counts but do not establish causality or capture every detail needed for a comprehensive safety assessment.

These results apply to the participants and analysis populations included in this study. The primary result is specifically based on the registry-defined Per Protocol population, and the record does not provide enough information to evaluate all consequences of missing data or exclusions. Statistical estimates are not individualized predictions and do not determine what treatment is appropriate for a particular person.

18. Why This Trial Matters Statistically

This trial illustrates why the analysis population and estimand matter when interpreting a randomized comparison. Although enrollment was 534, the primary result is reported for a Per Protocol population with additional criteria. A randomized design supports a structured comparison, but the analysis population and missing-data approach still shape what the estimate represents.

It also highlights the difference between a sponsor’s model-based analysis and a recalculation from summary statistics. The reported mixed model repeated measures analysis and the unadjusted contrast use different methods and should not be treated as duplicate calculations of the same quantity. Seeing both can clarify the role of model specifications and the limits of reconstructing an analysis without participant-level data or a full statistical plan.

The non-inferiority designation makes the margin especially important. A point estimate and confidence interval cannot establish non-inferiority without comparison with a prespecified margin. Because that margin is not reported in the registry record, readers can identify the sponsor’s stated analysis type but cannot verify its central decision criterion.

Finally, the trial includes multiple secondary outcomes and safety summaries. Their interpretation depends on uncertainty, multiplicity, and event definitions, not just on the direction of group estimates. This is a useful example of why statistical significance, clinical interpretation, and the strength of a trial’s formal claim are related but distinct questions.

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 trial-specific details needed for a full independent assessment are not reported in the registry record. These include the non-inferiority margin, the original sample-size justification, randomization and allocation-concealment procedures, the detailed statistical analysis plan, and whether interim analyses or multiplicity adjustments were used. Without the non-inferiority margin, the sponsor’s formal non-inferiority designation cannot be checked against its criterion.

The primary outcome is analyzed in a Per Protocol population, with criteria involving protocol deviations, treatment compliance, treatment completion, and assessment timing. The record does not give the number or reasons for exclusions under those criteria. It also does not specify the extent of missing data or the methods and assumptions used to address it. This limits assessment of how the analyzed population relates to all randomized participants.

The recalculated primary contrast relies on posted arm-level summary statistics, not individual participant data. Its inferred standard deviation is approximate, and it does not reproduce the sponsor’s mixed model repeated measures analysis. The sponsor’s reported final-value contrast and the recalculated change-score contrast also have different analysis descriptions.

The registry summaries do not provide all definitions and model details needed to assess the secondary outcomes, including full binary endpoint criteria and generalized estimating equation specifications. Safety summaries give event counts and selected terms, but not comprehensive event timing, duration, or causal assessment. These limitations constrain interpretation of the posted registry results; they do not establish that unreported methods were absent.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study to Evaluate the Efficacy, Safety and Tolerability of Bupropion Hydrochloride Extended-release Tablet, and Escitalopram Oxalate Capsule in Subjects With Major Depressive Disorder — NCT02191397.
• Registry record last updated 2020-02-25; status last verified 2020-02.
• Results first posted 2019-02-18.
• 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

NCT02191397 is a completed, randomized, double-blind, parallel active-controlled Phase 3 study sponsored by GlaxoSmithKline. It enrolled 534 participants with major depressive disorder and compared bupropion XL with escitalopram during an 8-week acute treatment phase within a study duration described as 11 weeks.

The primary endpoint was change in HAMD-17 total score from baseline to Week 8 in the Per Protocol population. The sponsor reported a mixed model repeated measures analysis designated as non-inferiority; an unadjusted recalculation from posted summaries gives a separate, uncertain comparison. The registry also reports response, remission, sustained outcomes, and adverse-event counts. Important details for independently checking the non-inferiority criterion, multiplicity handling, and missing-data assumptions are not reported in the registry record.