Clotrimazole Vaginal Tablet vs Fluconazole for Severe Vulvovaginal Candidiasis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Clotrimazole Vaginal Tablet vs Fluconazole for Severe Vulvovaginal Candidiasis (NCT02180828), a randomized phase 4 study. The primary outcome is Therapeutic Efficacy 1.

2. Clinical Question

The posted primary outcome counts are 102 of 114 in the clotrimazole group and 98 of 110 in the fluconazole group. The comparison is reported as a non-inferiority or equivalence analysis, but the registry record does not report the margin needed to interpret such a claim. The result therefore describes the observed outcome and the posted statistical test; it does not, by itself, establish a particular clinical conclusion.

3. Trial Design

The registry describes a Phase 4, randomized, parallel-group study sponsored by Peking University Shenzhen Hospital. Its title concerns clotrimazole vaginal tablet versus fluconazole for severe vulvovaginal candidiasis. The record lists an enrollment of 240 and a completed status. The study start is recorded as 2014-07, and primary completion as 2015-09.

One group received 2 doses of 500 mg clotrimazole intravaginally, at day1 and day4. The other received 2 doses of 150 mg oral fluconazole, also at day1 and day4. The registry states that masking was none. Allocation is recorded as randomized, and the model as parallel. Further details about sequence generation, allocation concealment, or how randomization was implemented are not reported in the registry record.

The primary outcome was assessed 7-14 days after treatment, identified as visit 2. The reported outcome population is PPS, or per protocol. The registry reports 114 participants in the clotrimazole outcome group and 110 in the fluconazole outcome group. These posted group counts are not the same as the enrollment figure; reasons for the difference and participant flow between enrollment, treatment, follow-up, and analysis are not reported in the registry record.

The record lists nine outcome measures and nine analyses. It identifies five posted secondary outcomes, all concerning adverse events: four separately labeled adverse-event outcomes and a total adverse-events outcome. Definitions and timeframes for these secondary outcomes are not reported in the registry record. The record does not report the trial’s original sample-size justification, planned analysis details beyond the posted test description, or whether any interim analyses were conducted.

4. Participant Flow and Accounting

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

Overall Study

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

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 Therapeutic Efficacy 1, measured over 7-14 days after treatment (=visit 2).

The primary endpoint is the clinical cure outcome assessed 7-14 days after treatment, at visit 2. It is recorded as a count of participants. Clinical cure was defined as resolution of symptoms present at baseline together with a total severity score of at most 2. The registry distinguishes cure from improvement: improvement required a considerable reduction in baseline signs and symptoms, with a decrease in total score of at least 50%. Participants who were neither clinically cured nor classified as improved were considered clinical failures.

This endpoint turns a clinical assessment into a binary outcome for each participant: the person either meets the stated cure definition or does not. A count can then be compared between treatment groups. In the posted results, 102 of 114 participants in the clotrimazole group and 98 of 110 in the fluconazole group were recorded as having the endpoint event. These counts describe the posted PPS analysis; they should not be treated as a complete account of all enrolled participants because the registry does not report the participant flow or the handling of missing outcome assessments.

General statistical explanation: a binary clinical endpoint can be useful when the study question concerns whether participants meet a prespecified clinical state at a defined assessment time. Its interpretation depends on the clarity and consistent application of the definition, the timing of assessment, and how participants without an observed assessment are handled. Details about assessor training, blinding of outcome assessment, and the handling of missing primary outcomes are not reported in the registry record.

7. Results Posted in the Registry

• Fluconazole: 89.1% (98/110) versus 89.5% (102/114) on control; risk difference -0.4 percentage points (95% CI -8.5 to 7.7), risk ratio 1.00 (0.91–1.09); unadjusted two-proportion z-test p = 0.926.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary result is a binary outcome: each participant in the analyzed population was classified according to whether the clinical cure definition was met. The posted counts are 102 of 114 for clotrimazole and 98 of 110 for fluconazole. A comparison of binary outcomes can be expressed on several scales, each answering the comparison in a different way. The posted recalculation focuses on the risk difference, which is the difference between the groups’ observed event proportions. The registry record also includes risk-ratio and odds-ratio summaries, but the central reported contrast is the risk difference.

What does a risk difference describe?

General statistical explanation: a risk difference is an absolute contrast between the proportions experiencing an event in two groups. A value of zero corresponds to equal observed proportions; values on opposite sides of zero indicate which group has the larger observed proportion, according to the comparison’s direction. The recalculated contrast is defined as fluconazole relative to clotrimazole. Its estimate is slightly below zero, so the observed proportion is slightly lower in the fluconazole group under that direction of comparison. This descriptive direction does not establish a meaningful treatment difference.

What does the confidence interval add?

General statistical explanation: a confidence interval shows the range of effect values compatible with the data and the calculation method at the stated confidence level. The posted interval crosses zero. This means the interval includes both a zero risk difference and values on either side of zero. The interval is also broad enough to leave uncertainty about the size and direction of the contrast. A confidence interval is not a guarantee that the true effect lies within its endpoints, and it does not resolve design or measurement limitations.

How should the p values be read?

General statistical explanation: a p value describes how unusual data at least as incompatible with a null hypothesis would be under that hypothesis and the assumptions of the test. It is not the probability that the null hypothesis is true, nor is it a measure of clinical importance. The recalculated unadjusted p value is 0.926. The registry’s reported chi-squared p value is 0.925. These values are close, but the analyses are not interchangeable simply because the values are similar. The registry identifies its analysis type as non-inferiority or equivalence. The non-inferiority or equivalence margin, and the details needed to evaluate that framework, are not reported in the registry record.

What is meant by unadjusted?

General statistical explanation: an unadjusted comparison uses the posted group summaries without accounting for additional covariates or a more complex model. The recalculated estimate and p value are simple unadjusted re-calculations from the posted summary statistics. They do not account for participant-level information, stratification, or covariate adjustment. The registry does not report whether other adjusted analyses were conducted. The posted comparison should not be interpreted as evidence that such analyses were or were not part of the complete study analysis.

Why does the analysis population matter?

The primary outcome is identified as PPS, meaning the posted primary analysis concerns a per-protocol population. General statistical explanation: a per-protocol analysis usually focuses on participants meeting specified protocol requirements, while an intention-to-treat analysis generally follows randomized assignment regardless of treatment adherence. The exact PPS definition is not reported in the registry record, and no intention-to-treat result is included in the registry entries. Without the population definition and participant flow, it is not possible to assess how exclusions or protocol deviations may have affected this comparison.

What can be inferred from the event counts?

The count of participants meeting the endpoint is an observed summary, not an estimate adjusted for factors such as baseline severity. The registry supplies the event counts and analysis denominators but does not report the distribution of baseline severity, the scoring instrument’s measurement properties, or participant-level outcome data. General statistical explanation: counts and proportions can summarize a binary endpoint, but confidence intervals and tests are needed to express uncertainty about the group contrast. Even then, the result remains dependent on the design, outcome definition, and completeness of observation.

What is not reported about the statistical plan?

The registry record does not report the original sample-size justification, the non-inferiority or equivalence margin, a detailed statistical analysis plan, adjustment procedures, interim analyses, or missing-data methods. The record does list nine outcome measures and nine analyses, with five secondary outcomes posted concerning adverse events. This does not reveal how other outcomes were defined or whether multiplicity was addressed. General statistical explanation: when multiple outcomes or analyses are considered, the chance of at least one apparently notable finding can increase unless the analysis plan accounts for those comparisons. Whether and how that issue was handled in this study is not reported in the registry record.

10. Confidence Intervals and Precision

The primary comparison’s recalculated risk difference is slightly below zero, and its confidence interval crosses zero. That interval therefore includes no risk difference as well as estimates favoring either group. Its breadth indicates uncertainty around both the magnitude and direction of the effect. The unadjusted recalculated p value is 0.926. These results describe limited precision for distinguishing the group outcomes through the risk-difference comparison; they do not show that the true difference is exactly zero.

General statistical explanation: precision concerns how narrowly an estimate is determined by the data under the analysis method. A confidence interval gives more information than a point estimate alone because it displays a range of compatible estimates. A wide interval can include effects that would be interpreted differently in practice. Whether the interval is sufficiently narrow for a non-inferiority or equivalence conclusion depends on the prespecified margin and analysis framework. Neither the margin nor a corresponding confidence-interval criterion is reported in the registry record.

Precision also depends on the number of observed outcomes and the analysis population, but the enrollment figure does not by itself establish the precision of the primary comparison. The posted PPS group denominators are 114 and 110. The registry does not explain the difference between those analysis counts and its enrollment figure of 240, or report how missing assessments and exclusions were handled. The posted interval consequently needs to be interpreted alongside those reporting limitations.

Finally, lack of a statistically clear difference is not proof of equivalence. Equivalence requires a prespecified range of differences considered acceptably small, alongside results that support remaining within that range. Non-inferiority similarly depends on a prespecified margin and appropriate analysis. With those details not reported in the registry record, precision can be described from the posted interval, but a formal non-inferiority or equivalence conclusion cannot be assessed from the p value alone.

11. 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 expressed as participants per arm, not as a combined total. The columns for 80% power and 90% power indicate the number of participants per arm in an illustrative design intended to have the corresponding probability of detecting the specified effect under the stated assumptions. They are planning quantities, not counts observed in this study.

The planning illustration assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Its target effect is set to a stated fraction of the observed effect: 100%, 75%, or 50%. The rows therefore represent planning for the full observed effect, planning for 75% of the observed effect, and planning for 50% of the observed effect. The associated sample-size values are those calculated under these assumptions, rather than an account of the study’s original design.

For either power column, a smaller effect requires more participants per arm to detect under the same assumptions. The planning values become larger as the assumed fraction of the observed effect becomes smaller. A 90% power target also entails more participants per arm than an 80% target for the same assumed effect. These comparisons illustrate how effect size and desired power influence planning; they do not establish what enrollment was needed under the trial’s actual design assumptions.

This is not observed power. The trial’s own original sample-size assumptions and justification are not reported in the registry record. The illustrative calculations use the observed effect, so they are not evidence that the completed trial had any particular probability of detecting an effect before it began.

12. 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.895; treatment proportion p₁ = 0.891; average p̄ = 0.893.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4375 = 0.8574.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4375 = 0.3682.
4. n = (0.8574 + 0.3682)² / (-0.0038)² = 102,520.9, rounded up to 102,521 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
p0 <- 0.894736842105263                          # control proportion
p1 <- 0.890909090909091                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(2180828)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 102,521 (80% power), 137,246 (90% power)
 75% of observed effect: n per arm = 181,544 (80% power), 243,036 (90% power)
 50% of observed effect: n per arm = 406,862 (80% power), 544,672 (90% power)
power.prop.test: 102520.9 
Simulated power at n = 102,521 per arm: 0.796 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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.

13. Analyses Reported by the Sponsor

The registry’s own primary analysis is identified as a chi-squared test and as a non-inferiority or equivalence analysis. Its reported p value is 0.925. The unadjusted recalculation from the posted summary statistics gives a p value of 0.926 and a risk-difference estimate with an interval that crosses zero. The small difference between the two p values is recorded without a discrepancy flag.

The recalculation is not a replacement for the sponsor’s analysis. It is an unadjusted analysis of the posted counts and denominators, whereas the registry reports its own test and analysis classification. The registry record does not provide the non-inferiority or equivalence margin or further details needed to assess that framework. The sponsor’s reported analysis should therefore be read according to the information the record gives, without treating the recalculation as confirmation of a non-inferiority or equivalence conclusion.

General statistical explanation: different tests can produce slightly different p values because their assumptions and calculation details may differ. A p value should be interpreted together with the method, outcome, analysis population, effect estimate, and uncertainty interval. Here, the registry’s reported p value and the recalculated p value are both high, but neither number alone establishes that the groups are equivalent or that any difference is clinically negligible.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists nine outcome measures and nine analyses, and identifies five posted secondary outcomes concerning adverse events. The primary outcome is clinical cure at 7-14 days after treatment. The record does not provide full definitions or timeframes for the secondary adverse-event outcomes beyond their labels. It also does not explain how the nine outcome measures relate to the nine analyses.

General statistical explanation: multiplicity arises when several outcomes, timepoints, or statistical comparisons are examined. The more comparisons made, the greater the chance that at least one result may appear notable by chance, depending on the analysis plan. Common approaches include designating a primary outcome, adjusting inference for multiple comparisons, or treating secondary analyses as exploratory. Whether such an approach was prespecified or used in this study is not reported in the registry record. The registry’s listing of outcomes alone does not show how multiplicity was handled.

The primary analysis population is PPS. The registry does not define the per-protocol criteria or report a parallel intention-to-treat analysis. It does not describe participant flow, protocol deviations, withdrawals, missing assessments, or methods for handling missing primary outcomes. These omissions limit assessment of how the analyzed participants relate to the randomized groups and whether missingness could have affected the result.

General statistical explanation: missing outcome data can affect a comparison when the probability of an outcome being observed is related to treatment, participant characteristics, or the outcome itself. Different assumptions and methods for handling missing data can produce different estimates. Without the missing-data counts and method, the extent and potential direction of any influence cannot be evaluated from the registry record.

The record also does not report details of random sequence generation, allocation concealment, baseline comparability, or a detailed statistical analysis plan. It reports no masking. These are reporting limitations, not proof that a particular procedure was or was not used beyond what the record states. They matter when interpreting an outcome that depends on symptom assessment and when assessing whether the posted analysis answers the planned primary question.

15. Safety Results

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

Other (non-serious) adverse events

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

Most frequent non-serious adverse event terms

The registry reports serious adverse events affecting 0 participants in the clotrimazole group, among 115 at risk, and 0 participants in the fluconazole group, among 113 at risk. The record does not list serious adverse-event terms. Death counts are not reported in the registry record.

For other adverse events, the registry reports 13 participants affected among 115 at risk in the clotrimazole group and 10 among 113 at risk in the fluconazole group. These are participant counts as posted, not a complete description of event frequency or clinical severity. The record does not report definitions for the numbered adverse-event outcomes, event timing, duration of follow-up for safety, attribution to treatment, or whether participants could contribute more than one event.

General statistical explanation: zero recorded serious adverse events does not establish that the underlying risk is zero. Rare outcomes may not occur in a study even when some risk exists, and interpretation depends on the amount and duration of observation and the completeness of reporting. These safety counts describe what the registry posts; they do not support a broader conclusion about comparative safety beyond the recorded outcomes.

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

The posted primary outcome counts show that clinical cure was recorded for 102 of 114 participants in the clotrimazole PPS group and 98 of 110 in the fluconazole PPS group. The unadjusted recalculated risk-difference estimate is slightly below zero for fluconazole relative to clotrimazole, and its confidence interval crosses zero. The recalculated p value is 0.926. The registry’s own chi-squared analysis reports a p value of 0.925 and labels the analysis non-inferiority or equivalence.

These results do not establish that the treatments have the same effect. A test that does not distinguish a difference from zero is not proof of equivalence. A formal non-inferiority or equivalence interpretation requires a prespecified margin and an appropriate analysis; the margin is not reported in the registry record. The confidence interval’s inclusion of zero also means the posted comparison is compatible with effects in either direction under the recalculated analysis.

The finding is limited to the defined clinical cure outcome, the follow-up at 7-14 days after treatment, and the PPS analysis population reported in the record. It does not establish results for other timepoints, other populations, other definitions of response, or outcomes not reported. The registry does not explain the exact PPS criteria or how missing outcomes were handled.

Safety findings should be interpreted with similar care. The registry reports no serious adverse events affecting participants in either group, and reports other adverse events affecting 13 participants in the clotrimazole group and 10 in the fluconazole group. Those counts do not provide enough detail to characterize the nature, timing, or treatment relationship of events. The available record therefore supports a narrow description of posted outcomes, not medical advice or a broad claim about efficacy or safety.

17. Why This Trial Matters Statistically

This trial is statistically informative because it illustrates why an observed difference, a statistical test, and a clinical conclusion are separate things. The primary outcome is a binary clinical-cure measure with a stated definition and follow-up time. The posted counts permit an unadjusted comparison, while the confidence interval shows that the estimate remains compatible with differences in either direction. A single point estimate or p value would not communicate that uncertainty as clearly.

The registry’s analysis is labeled non-inferiority or equivalence, which makes the missing margin especially important. Such analyses are not established merely by observing a high p value in a test of difference. The margin defines how large a difference could still be considered compatible with the study’s objective, and the analysis must be interpreted against that boundary. Without the margin and further analysis details, readers cannot evaluate the stated non-inferiority or equivalence framework from the posted result alone.

The record also highlights the importance of knowing who was analyzed and how outcome data were handled. The primary result is reported for PPS, but the population definition, participant flow, and missing-data methods are not reported. For symptom-based outcomes, assessment procedures and masking may also matter; the registry records no masking and does not describe whether outcome assessment was masked.

Finally, the sample-size illustration is distinct from the trial’s original design. It shows how planning requirements depend on the effect targeted and desired power, but it is based on the observed effect and stated illustrative assumptions. It cannot be read as observed power or as evidence of the original sample-size justification. Together, these points make the study a useful example of interpreting effect estimates in context rather than treating one test result as a complete answer.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record leaves important details unavailable for independent assessment. It does not report the eligibility criteria, the operational definition of severe disease, the full PPS criteria, participant flow, or reasons why outcome analysis denominators differ from the enrollment figure. It does not report baseline characteristics or provide participant-level outcomes. As a result, the comparability of the analyzed groups and the effects of exclusions cannot be evaluated from the posted record.

The primary outcome depends on symptom resolution and a total severity score. The scoring instrument, assessor procedures, assessor training, and whether outcome assessment was masked are not reported in the registry record. The record states that masking was none, but does not clarify whether any separate measure was used to reduce assessment bias. The follow-up window is stated as 7-14 days after treatment; outcomes outside that window are not described.

The registry labels the analysis non-inferiority or equivalence but does not report the margin or detailed statistical plan. It does not report the original sample-size justification, missing-data method, multiplicity approach, or interim analyses. The primary result is PPS, with no intention-to-treat result posted. These limitations prevent a full evaluation of the analysis strategy and of how well the reported analysis addresses the randomized comparison.

Safety reporting is also brief. The record provides participant counts for serious and other adverse events but does not report event definitions, terms, severity grades, timing, attribution, or follow-up duration. Deaths are not reported in the registry record. The available safety summaries therefore cannot be expanded into a detailed comparison of adverse-event profiles.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Clotrimazole Vaginal Tablet vs Fluconazole for Severe Vulvovaginal Candidiasis — NCT02180828.
• Registry record last updated 2017-05-02; status last verified 2017-04.
• Results first posted 2016-09-30.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry describes a completed, randomized, parallel-group Phase 4 study of clotrimazole vaginal tablet versus fluconazole for severe vulvovaginal candidiasis. The listed enrollment is 240, and masking is recorded as none. The primary endpoint is clinical cure assessed 7-14 days after treatment in the PPS population.

The posted cure counts are 102 of 114 for clotrimazole and 98 of 110 for fluconazole. The registry reports a chi-squared p value of 0.925 for an analysis labeled non-inferiority or equivalence. An unadjusted recalculation gives p = 0.926, with a risk-difference confidence interval that crosses zero. The non-inferiority or equivalence margin is not reported in the registry record.

The record lists five secondary adverse-event outcomes. It reports zero serious adverse events in each group and other adverse events affecting 13 participants in the clotrimazole group and 10 in the fluconazole group. Definitions and further safety details are not reported in the registry record.