Bupropion Hydrochloride in Improving Sexual Desire in Women With Breast or Gynecologic Cancer: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Bupropion Hydrochloride in Improving Sexual Desire in Women With Breast or Gynecologic Cancer (NCT03180294), a randomized phase 2 study. The primary outcome is Change From Baseline at 9 Weeks in the Desire Subscore of the Female Sexual Function Index ("Sexual Desire").

2. Clinical Question

3. Trial Design

This was a randomized, double-blind, parallel-group phase II trial sponsored by NRG Oncology. The registry lists enrollment as 230 and the study status as completed. The recorded start date is 2017-05-31, and primary completion is recorded as 2021-02-22. These registry dates describe the study record; they do not, by themselves, explain recruitment, follow-up, or timing of analyses.

The study compared bupropion 150 mg, bupropion 300 mg, and placebo. In the 150 mg arm, participants took one bupropion 150 mg XL capsule daily for one week, then one bupropion capsule and one placebo capsule daily for 8 weeks, followed by one week of placebo for titration off. In the 300 mg arm, participants took one bupropion capsule daily for one week, two bupropion capsules daily for 8 weeks, and one bupropion capsule daily for one week for titration off. The placebo arm received placebo capsules throughout the described schedule. The exact process used to maintain blinding across these regimens is not reported in the registry record.

The primary endpoint was change from baseline at 9 weeks in the desire subscore of the Female Sexual Function Index. The primary endpoint population is described as eligible participants with baseline and 9-week data. The posted analysis includes 66 participants in the 150 mg group, 59 in the 300 mg group, and 63 in the placebo group. Those endpoint-specific counts are not the same description as the overall enrollment figure; the registry does not explain the reasons for the difference.

The record also lists secondary outcomes concerning fatigue, desire at 5 weeks, sexual satisfaction and functioning, mood, perceived change, perceived risk versus benefit, and adverse events. The original sample-size justification and the trial’s prespecified statistical analysis plan 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: Registered patients who completed required baseline assessments were randomized. Of 238 registered patients, 230 were randomized.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Eligible participants with baseline and 9 week data

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: Eligible participants

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline at 9 Weeks in the Desire Subscore of the Female Sexual Function Index ("Sexual Desire"), measured over Baseline (prior to randomization) and 9 weeks from start of study treatment (within 21 days of randomization).

The primary endpoint is change from baseline at 9 weeks in the desire subscore of the Female Sexual Function Index (FSFI). This questionnaire subscore measures self-reported sexual desire. The stated possible scores range from 1.2 to 6, with higher scores indicating greater desire. The change score is calculated as the later score minus the baseline score, so a positive change represents an increase on the measure.

This outcome is used because the trial’s stated question concerns sexual desire, and the FSFI subscore gives that concept a defined, participant-reported measure. It is not a direct measure of every aspect of sexual experience or of clinical benefit. As a continuous outcome, it preserves the amount of change on the scale rather than reducing each participant’s result to a yes-or-no category. Group means summarize the average change, while standard deviations describe variation among participants.

The measurement was scheduled at baseline and 9 weeks from the start of study treatment, within 21 days of randomization. The primary analysis population is described as eligible participants with data at both time points. Consequently, the posted endpoint summaries concern participants with those measurements, rather than necessarily every randomized participant. The record does not report further detail about how missing baseline or follow-up measurements were handled, nor does it describe a threshold for what would count as an important individual change.

7. Results Posted in the Registry

• Bupropion 150 mg: mean 0.64 versus 0.62 on control; difference 0.02 (95% CI -0.35 to 0.39), standardized effect d = 0.02; z-test p = 0.916.
• Bupropion 300 mg: mean 0.60 versus 0.62 on control; difference -0.02 (95% CI -0.39 to 0.35), standardized effect d = -0.02; z-test p = 0.915.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Change From Baseline at 5 Weeks in Desire Subscore of the FSFI ("Sexual Desire")

• 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 deviations.
• Result:
  • Bupropion 150 mg: mean 0.70 versus 0.58 on control; difference 0.12 (95% CI -0.21 to 0.45), standardized effect d = 0.13; z-test p = 0.472.
  • Bupropion 300 mg: mean 0.48 versus 0.58 on control; difference -0.10 (95% CI -0.40 to 0.20), standardized effect d = -0.12; z-test p = 0.513.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Bupropion 150 mg 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 Bupropion 300 mg and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists 9 secondary outcomes, covering fatigue, desire at 5 weeks, sexual satisfaction and functioning, depressive mood, perceived change, perceived risk versus benefit, and adverse events. Those outcomes span different constructs and time points, so they do not all measure the same aspect of participants’ experience as the primary 9-week desire subscore.

For the secondary 5-week desire measure, the posted mean changes are 0.7 units for bupropion 150 mg, 0.48 units for bupropion 300 mg, and 0.58 units for placebo. The recalculated comparisons have intervals that include zero, and their unadjusted p-values are 0.472 and 0.513. These results do not supply a clear, precise contrast that changes the broad reading of the primary result. The 5-week endpoint is related to the primary measure, but it is a different assessment time and should not be treated as a substitute for the 9-week outcome.

The record identifies 9 secondary outcomes, but numerical group results and comparisons are not detailed for all of them. As a result, an overall direction across every secondary measure cannot be established from the registry information available in this summary. It would be inappropriate to infer a consistent or inconsistent pattern for outcomes whose results are not reported.

General statistical explanation: multiple outcomes create multiple opportunities to observe a seemingly notable result by chance. Unless analyses account for that multiplicity, unadjusted secondary p-values are usually less persuasive than a prespecified primary comparison, especially when many outcomes or time points are examined. The registry does not report whether multiplicity adjustments were planned or used. Secondary findings can help describe the range of measured outcomes, but they warrant cautious interpretation and should be considered alongside their estimates, uncertainty, and the trial’s primary question.

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

• Change From Baseline in the Patient Reported Outcomes Measurement Information System (PROMIS) Fatigue Score
• Change From Baseline at 5 Weeks in Desire Subscore of the FSFI ("Sexual Desire")
• Change From Baseline in the PROMIS Global Satisfaction With Sex Life Subscore of Sexual Function and Satisfaction Measure ("Sexual Desire and Satisfaction")
• Change From Baseline in FSFI Total Score ("Sexual Functioning")
• Change From Baseline in the Patient Health Questionnaire (PHQ)-4 Score ("Depressive Mood")
• Global Impression of Change at 9 Weeks ("Perception of Change")
• Perception of Risk vs. Benefit at 9 Weeks
• Number of Participants With a Grade 3 or Higher Adverse Event Over the Course of the Study

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: a change score on the FSFI desire subscore. The registry reports the mean and standard deviation for each group. A mean describes the group’s average change; a standard deviation describes how dispersed individual observed changes are around that average. These summaries answer different questions. A group can have a particular average while participants’ changes vary substantially.

What does the between-group estimate represent?

The recalculated comparison subtracts the placebo group mean change from the mean change in an active-treatment group. For bupropion 150 mg, the estimate is 0.02 units; for bupropion 300 mg, it is -0.02 units. These estimates are unadjusted comparisons based on the posted group summaries. They are not estimates adjusted for baseline characteristics or other covariates. No such adjusted estimate is reported.

Randomization is intended to support a fair comparison of assigned groups, while blinding is intended to reduce the influence of knowledge of assignment on conduct or measurement. These features describe the design; they do not remove uncertainty from the estimates or answer questions about missing outcome measurements. The record describes the trial as randomized and double-blind, but detailed implementation information is not reported in the registry record.

What does a confidence interval add?

General statistical explanation: a confidence interval gives a range of values compatible with the observed data under the calculation’s assumptions. It is not a guarantee that the true effect lies inside the particular interval, and it is not a range of individual participant responses. Here, each recalculated interval includes zero, the value representing no mean difference. Each interval also extends to differences on both sides of zero. That pattern indicates uncertainty about both the direction and size of the comparative effect. The 95% confidence level describes the long-run behavior of the interval procedure under its assumptions, not a 95% probability assigned to the effect in this particular trial.

How should the p-values be read?

A p-value describes how surprising data at least as incompatible with a null comparison would be if the null model and test assumptions held. It is not the probability that the null hypothesis is true, nor a measure of the size or importance of an effect. The recalculated unadjusted p-values are 0.916 and 0.915. The registry separately reports one-sided sponsor t-tests with p-values 0.46 and 0.54. Because one-sided and two-sided tests answer different directional questions, those p-values should not be treated as directly interchangeable. The registry’s sponsor results do not include a confidence interval or comparison estimate.

General statistical explanation: a two-sided analysis allows for a difference in either direction, whereas a one-sided test evaluates a difference in a specified direction. A test’s sidedness should be chosen in advance and interpreted in light of the study question. The registry record does not provide enough information to evaluate the rationale for the sponsor’s one-sided tests or whether other testing choices were prespecified.

What does the standard deviation tell us?

In the primary outcome summaries, the standard deviations are 0.95 for bupropion 150 mg, 0.89 for bupropion 300 mg, and 1.18 for placebo. They describe the spread of observed change scores within each group. General statistical explanation: variability matters because greater participant-to-participant spread can make a group mean less precise when group sizes are fixed. The standard deviation is not the standard error of the mean, and it should not be read as uncertainty in the treatment contrast alone.

The recalculated mean differences and intervals use the posted group means, standard deviations, and endpoint sample sizes. They are simple unadjusted recalculations. The record does not report an adjustment for covariates or multiplicity in the sponsor’s analysis. The method used for the sponsor’s reported one-sided t-tests is named, but test statistics, effect estimates, and confidence intervals are not posted for those tests.

These methods describe how the posted summaries relate to one another; they do not establish that a particular analysis was the only suitable approach. The registry does not report a complete statistical analysis plan, the original sample-size justification, or detailed missing-data procedures. Those details would help evaluate choices such as analysis population, model specification, handling of incomplete observations, and control of false-positive findings across outcomes.

11. Confidence Intervals and Precision

The two recalculated primary comparisons are close to zero, but their confidence intervals are appreciably wider than the point estimates. For bupropion 150 mg versus placebo, the interval runs from -0.351 to 0.391 units. For bupropion 300 mg versus placebo, it runs from -0.389 to 0.349 units. Both include zero and encompass possible differences in either direction. The intervals therefore do not locate the comparative effects precisely.

Precision is about how narrowly the data constrain an estimate, not simply whether a p-value crosses a chosen threshold. A point estimate near zero can coexist with an interval that includes effects of either sign. Here, the estimates do not show a clear separation in average change, but the intervals also do not establish equivalence or rule out every potentially relevant difference. The registry does not report an equivalence margin or a threshold for a clinically important difference, so those interpretations cannot be assessed from the posted record.

The arm-specific standard deviations are 0.95, 0.89, and 1.18 units for bupropion 150 mg, bupropion 300 mg, and placebo, respectively. These show that individual change scores varied within each arm. The confidence intervals for the mean differences are more directly useful for judging precision of the comparisons than the arm-level standard deviations alone.

The primary summaries use 66 participants in the 150 mg group, 59 in the 300 mg group, and 63 in the placebo group. The stated primary population requires both baseline and 9-week data. Because the registry does not explain the difference between overall enrollment and these endpoint counts, or detail missing-data handling, precision should be understood as applying to the posted analysis and its observed endpoint data. The intervals quantify sampling uncertainty under the recalculation; they do not account for every possible source of uncertainty, such as departures from the analysis assumptions or missing-data mechanisms.

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 table and curve are planning illustrations based on the observed comparison, not a reconstruction of the trial’s original design. For these continuous outcomes, the displayed figures are participants per arm, not a total across both arms and not total events. The stated 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 set to the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the estimated participants per arm for a planned study to have an 80% chance of detecting the selected effect under the listed assumptions, if that effect and the assumptions are correct. The 90% power column gives the corresponding per-arm planning figure for a 90% chance. These are design targets for a future study, not descriptions of how often the present result would be significant. This is not observed power.

The table shows planning for 100%, 75%, and 50% of the observed effect. The rows illustrate an important general relationship: smaller effects are harder to distinguish from random variation, so the planning figures rise as the effect to detect is reduced. For example, in the primary 150 mg comparison, The table shows 44,804 participants per arm for 80% power when planning for 100% of the observed effect, and 179,216 participants per arm when planning for 50% of it. These very large figures reflect the small observed difference used as the planning basis; they should not be interpreted as the trial’s actual enrollment target.

The curve is another way to view how the planning requirement varies with the effect assumption. It does not add an independent trial result. Because the calculations use the observed effect, they are sensitive to the uncertainty and possible instability of that estimate. The illustrations should therefore be read as conditional planning information rather than as definitive recommendations about a future study.

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 = 0.020; pooled standard deviation σ = 1.068.
2. n = 2 × (1.96 + 0.842)² × 1.068² / 0.020² = 44,803.9, rounded up to 44,804 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 <- 0.02                      # observed difference in means
sigma <- 1.06848667728127                     # 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(3180294)
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 = 44,804 (80% power), 59,980 (90% power)
 75% of observed effect: n per arm = 79,652 (80% power), 106,631 (90% power)
 50% of observed effect: n per arm = 179,216 (80% power), 239,919 (90% power)
power.t.test: 44804.9 
Simulated power at n = 44,804 per arm: 0.800 (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 sponsor analyses comparing each bupropion group with placebo using a one-sided t-test for superiority. The posted p-value is 0.46 for bupropion 150 mg versus placebo and 0.54 for bupropion 300 mg versus placebo. The record does not provide an effect estimate, confidence interval, or test statistic alongside these sponsor results.

The recalculations shown alongside the results use the posted means, standard deviations, and endpoint counts to estimate unadjusted mean differences and confidence intervals. They give mean differences of 0.02 units for 150 mg versus placebo and -0.02 units for 300 mg versus placebo, with unadjusted p-values of 0.916 and 0.915. These are not identical statistical summaries: the sponsor reports one-sided tests, whereas the recalculated comparisons include two-sided confidence intervals and unadjusted p-values. A difference in sidedness and reporting format means the p-values should not be compared as if they came from the same test.

The registry does not report enough detail to reconcile the analyses further or assess whether the sponsor’s test direction and analysis choices were prespecified. The discrepancy flag is false, so there is no identified numerical discrepancy requiring the sponsor result to take precedence over a conflicting recalculation. The sponsor’s analysis remains the trial’s own reported test; the recalculation is a transparent, unadjusted summary derived from the posted group statistics. Both should be identified as such rather than merged into a single result.

15. Multiplicity, Missing Data and Analysis Populations

The registry record reports a primary endpoint and lists multiple secondary outcomes. The posted results also include multiple analyses. The statistical plan for handling multiplicity is not reported in the registry record. In particular, the record does not say whether the sponsor adjusted for testing across secondary outcomes, across dose comparisons, or across assessment times, or whether any sequence of hypothesis tests was specified in advance.

General statistical explanation: when investigators test many hypotheses, the chance of at least one apparently unusual result can increase even if no underlying effects are present. Methods for addressing this include adjusting the significance threshold, controlling a family-wise error rate, or treating secondary analyses as exploratory. Without the planned approach, isolated secondary p-values should not be interpreted as if they were the sole confirmatory test. This does not make secondary data useless; it changes how much weight a single finding can carry.

The primary analysis population is described as eligible participants with baseline and 9-week data. The endpoint counts are 66 for bupropion 150 mg, 59 for bupropion 300 mg, and 63 for placebo. The registry does not report the number missing at each measurement, reasons for missingness, whether participants were excluded for other reasons, or the methods used to handle incomplete outcome data. It also does not report whether the main analysis followed an intention-to-treat principle or another named analysis population.

General statistical explanation: analyses limited to participants with observed measurements can be affected if missingness is related to outcome or treatment experience. Alternative approaches can make different assumptions about missing values, but no particular method can be attributed to this trial from the posted record. Without details on missingness and sensitivity analyses, readers cannot assess how robust the primary comparison is to incomplete follow-up.

The registry names a one-sided t-test for the sponsor’s primary comparisons, but it does not report the full statistical analysis plan, the original sample-size justification, or whether interim analyses were conducted. These items are not reported in the registry record; no protocol details should be inferred from their absence. The available record supports interpretation of the posted summaries, while leaving these aspects of analysis conduct unresolved.

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: insomnia (1.3%).

The adverse-event summary reports serious events and other adverse events by randomized group. For serious events, 1 participant was affected among 77 at risk in the bupropion 150 mg group, none among 73 at risk in the bupropion 300 mg group, and none among 76 at risk in the placebo group. The registry lists insomnia at 1.3% among the leading serious-event terms. It does not identify an arm for that term in the summary, so the term should not be assigned to a particular group.

For other adverse events, the affected counts are 53 among 77 at risk in the 150 mg group, 55 among 73 at risk in the 300 mg group, and 57 among 76 at risk in the placebo group. The death count is 0 in each group. These counts describe participants recorded as affected; they do not establish cause or comparative risk on their own. No inferential comparison or confidence interval for adverse events is reported.

Safety summaries should be read as descriptive registry data, with attention to the at-risk counts and the event category. The record does not provide event timing, duration, recurrence, or detailed attribution information in this summary. The figures do not support medical advice or a conclusion beyond what was recorded.

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

The primary endpoint summaries show similar average changes in desire score across the bupropion and placebo groups. The recalculated mean differences are close to zero, and their confidence intervals include zero while extending to differences in either direction. The posted results therefore describe little separation in the observed group averages, but they do not establish that the true comparative effects are exactly zero.

The result is about a specific self-reported measure, at a particular follow-up time, among eligible participants with baseline and 9-week data. It is not a direct assessment of every component of sexual wellbeing, and the registry record does not define a threshold for a meaningful change on this scale. The result should not be generalized automatically to people outside the study population, to other treatment schedules, or to other time points.

A positive within-group average change is not by itself evidence that a treatment caused improvement. The placebo group also had a positive average change, and changes over time can occur for reasons not isolated by a within-group comparison. The randomized between-group comparisons are more informative about differences associated with assignment, but the estimates remain imprecise.

The available summaries do not establish equivalence between the groups, rule out all differences that might matter, or demonstrate a clinical benefit or lack of benefit. Those conclusions would require additional prespecified criteria and fuller information than the registry reports. Nor do the posted results settle the interpretation of every secondary outcome: numerical details are not available for all listed secondary measures, and multiplicity handling is not reported.

In short, the registry supports a bounded statistical statement: the observed primary mean changes were close across groups, and the recalculated comparisons are uncertain. Readers should distinguish that description from a definitive statement about treatment efficacy, individual outcomes, or medical decisions.

18. Why This Trial Matters Statistically

This trial illustrates why a randomized comparison should be interpreted using both an effect estimate and its uncertainty. The three primary group means are positive, yet the placebo group’s mean change is close to the active-treatment means. Looking only at whether each group changed from baseline would miss the central comparative question. The between-group estimates and intervals make that contrast explicit.

It also shows why a small point estimate is not the same as proof of no effect. The two recalculated estimates sit near zero, but their confidence intervals cross zero and extend in both directions. The data are compatible with more than one comparative interpretation. Precision, rather than a binary significant/not-significant label alone, is therefore central to understanding what the posted results can support.

The record offers two distinct statistical perspectives: sponsor-reported one-sided superiority tests and simple unadjusted recalculations using the posted summaries. Keeping those analyses distinct helps avoid treating unlike p-values as interchangeable. It also makes clear what is available for independent interpretation and what the registry does not report, such as sponsor effect estimates and confidence intervals.

The trial is also a useful example of how registry completeness affects statistical interpretation. The record identifies the primary endpoint population and several secondary outcomes, but does not report the original sample-size justification, the complete analysis plan, multiplicity handling, or detailed missing-data methods. Those gaps matter when judging intended precision and the robustness of results, even when the main outcome summaries are present.

Finally, the planning illustrations demonstrate how sample-size calculations depend on the effect selected for detection. Smaller assumed effects require more participants per arm under the listed assumptions. These figures are not evidence about the trial’s power or its original design; they are conditional planning information anchored to the observed estimate. Taken together, the page emphasizes transparent estimation, uncertainty, and limits of inference.

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 primary analysis is described for eligible participants with both baseline and 9-week data, and the group counts are smaller than the overall enrollment figure. The registry does not explain this difference, list reasons for missing measurements, or describe how incomplete outcomes were handled. The posted estimates may therefore not represent every randomized participant in the same way an explicitly described full analysis population would.

The sponsor’s reported comparisons are one-sided t-tests, but the record does not provide their effect estimates, confidence intervals, test statistics, or rationale for the testing direction. The recalculated comparisons are unadjusted and based on summary statistics. They help quantify the posted group contrast, but they cannot reproduce all details of a model or analysis that the registry does not describe.

The original sample-size justification and full statistical analysis plan are not reported. The record does not state whether a multiplicity procedure was applied across secondary outcomes or analyses. That limits evaluation of confirmatory claims beyond the primary endpoint. Although the registry lists 9 secondary outcomes, detailed numerical results are not available for every one, preventing a complete assessment of their overall pattern.

The primary outcome is self-reported, and the registry defines its scale and direction but does not report a threshold for a clinically important change. The endpoint is specific to desire and the stated 9-week assessment; it does not cover every aspect of sexual function or longer-term outcomes. The reported adverse-event counts are also descriptive and lack detail about timing, attribution, or comparative uncertainty.

Finally, the registry record does not report enough information to assess implementation details of blinding, adherence, protocol deviations, or interim analyses. These are not evidence of a flaw; they are limits on what can be concluded from the posted record. Interpretation should stay with the reported measures and analyses.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Bupropion Hydrochloride in Improving Sexual Desire in Women With Breast or Gynecologic Cancer — NCT03180294.
• Registry record last updated 2026-07-10; status last verified 2026-06.
• Results first posted 2022-03-08.
• 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

This completed randomized, double-blind, parallel-group phase II study compared bupropion 150 mg, bupropion 300 mg, and placebo in women with breast or gynecologic cancer. Overall enrollment was 230. The primary endpoint was change from baseline at 9 weeks in the FSFI desire subscore, analyzed among eligible participants with measurements at both time points.

Mean changes were 0.64 units, 0.6 units, and 0.62 units in the 150 mg, 300 mg, and placebo groups, respectively. The recalculated unadjusted mean differences versus placebo were 0.02 and -0.02 units, and both 95% confidence intervals included zero. The registry reports sponsor one-sided t-test p-values of 0.46 and 0.54.

The record lists secondary outcomes and adverse events, but does not report the original sample-size justification, full statistical plan, multiplicity handling, or detailed missing-data methods. The posted primary comparisons are close to zero but imprecise; they do not establish equivalence or settle every question about the listed outcomes.