A Pilot Comparison of Short-course Nitrofurantoin in Females With Uncomplicated Bacterial Cystitis in the Emergency Department: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Pilot Comparison of Short-course Nitrofurantoin in Females With Uncomplicated Bacterial Cystitis in the Emergency Department (NCT01749605), a randomized phase 4 study. The primary outcome is Number of Participants With Clinical Cure at Day 7.

2. Clinical Question

This is a comparison of two short-course drug regimens in a specific emergency department setting. The endpoint is a participant-reported symptom status at a defined follow-up, not a laboratory measure or a longer-term assessment. The registry also posted adverse-event counts, which describe reported safety events over the recorded safety populations. The primary clinical question is limited to the day-7 outcome; other possible questions, such as symptom course after day 7 or recurrence, are not answered by the posted primary endpoint.

3. Trial Design

The registry identifies this as a phase 4, randomized, double-masked, parallel-group trial. It is described as a pilot comparison of short-course nitrofurantoin and ciprofloxacin in females with uncomplicated bacterial cystitis presenting to an emergency department. The stated purpose was to compare the efficacy and safety of the two 3-day, twice-daily regimens.

The planned treatments were nitrofurantoin monohydrate/macrocrystals 100 mg twice daily for 3 days and ciprofloxacin 250 mg twice daily for 3 days. The primary outcome was clinical cure at day 7. The registry describes a telephone call seven days after randomization to ask whether symptoms had completely resolved. Responses were restricted to “Yes” for clinical cure or “No” for treatment failure.

Enrollment is recorded as 35, and the status is completed. The posted primary outcome lists 14 participants in each arm. The outcome entries report 13 clinical cures in the nitrofurantoin arm and 12 in the ciprofloxacin arm. These outcome counts describe the participants included in the posted outcome, but the registry does not explain how they relate to the enrollment figure or whether any participants lacked an outcome response.

The allocation sequence method, concealment procedures, exact masking arrangements, and details of the analysis populations are not reported in the registry record. The registry also does not report the original sample-size rationale or the trial’s prespecified statistical analysis plan. These missing details limit assessment of how the trial was designed to manage allocation, follow-up, and analysis decisions.

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

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 Number of Participants With Clinical Cure at Day 7, measured over 7 days.

The primary endpoint is the number of participants with clinical cure at day 7. The registry defines clinical cure by a telephone response seven days after randomization: participants were asked whether their symptoms had completely resolved, and could answer only “Yes” or “No.” A “Yes” was counted as clinical cure and a “No” as treatment failure. This is a binary, participant-level outcome: each response falls into one of the two stated categories.

A symptom-based endpoint can capture whether participants feel that the problem being treated has resolved, which is directly relevant to the stated comparison of short-course regimens. It also gives a clear, interpretable outcome at a specified follow-up time. The endpoint does not, by itself, establish the timing or extent of symptom change during treatment, nor does it describe recurrence or symptoms after the day-7 assessment. Those outcomes are not reported as secondary results in the registry record.

Because the assessment is based on a telephone response, the recorded result depends on participants being reached and answering the symptom question. The registry describes the question and response categories but does not report the number of attempted calls, nonresponses, or procedures for handling unavailable responses. It also does not report a separate clinical assessment or laboratory confirmation as part of this endpoint. The primary result should therefore be interpreted as the posted count of participant-reported complete symptom resolution at the specified follow-up.

7. Results Posted in the Registry

• Ciprofloxacin 250 mg: 85.7% (12/14) versus 92.9% (13/14) on control; risk difference -7.1 percentage points (95% CI -29.9 to 15.6), risk ratio 0.92 (0.71–1.20); unadjusted two-proportion z-test p = 0.541.

8. Statistical Interpretation

9. Statistical Methods Explained

The posted primary outcome is binary: a participant either reported complete symptom resolution or did not. For a binary outcome, the central descriptive quantities are the number meeting the outcome and the number assessed in each arm. The registry reports 13 clinical cures among 14 participants in the nitrofurantoin arm and 12 among 14 in the ciprofloxacin arm. These counts are the basis for the arm-level proportions and the comparative estimates.

What does the risk difference express?

The risk difference expresses the difference between the proportions with the outcome in the two arms, using the stated comparison direction. In this record, the estimate is framed as ciprofloxacin relative to nitrofurantoin. A negative estimate therefore points toward a lower observed cure proportion in the comparison arm, while a positive estimate would point in the other direction. The estimate is a sample result; it does not by itself establish the true difference in a wider population.

The risk difference is expressed on an absolute scale, which can be helpful for understanding how far apart the observed outcome proportions are. Other comparative measures, such as a risk ratio or odds ratio, express the relationship on different scales. Their numerical values can look different because their definitions differ. They do not turn the small study into a more precise one: interpretation still depends on the amount of information in the outcome data and the uncertainty around each estimate.

How should the p-value be read?

The posted unadjusted p-value is 0.541. In general, a p-value describes how unusual data at least as inconsistent with a specified null hypothesis would be if that null hypothesis and the test assumptions were true. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. A p-value above a conventional significance threshold does not demonstrate equivalence or absence of an effect. The registry record does not state the original prespecified analysis plan or a decision threshold, so the p-value should be read as a posted unadjusted result, not as proof of a particular conclusion.

What do confidence intervals contribute?

A confidence interval gives a range of values compatible with the data under the method used to construct it. In repeated use of a specified method, intervals would cover the true parameter at the method’s stated confidence level at the corresponding frequency. For an individual study, the interval communicates uncertainty about the estimated effect; it is not a range containing a known proportion of individual outcomes. Here, the risk-difference interval includes values on both sides of zero, so the data are compatible with differences in either direction. Its breadth is an important part of interpretation, rather than a detail that can be replaced by the point estimate or p-value.

General statistical principle: estimates based on limited outcome information tend to be less precise than estimates based on more information, all else being equal. A small number of participants can leave substantial uncertainty even when the observed counts look similar. This is why the interval and the arm counts should be read together.

Why can over-dispersion matter?

Over-dispersion is a general concern when the variability in observed data is greater than a model assumes. For binary outcomes, a simple model may not capture clustering or other dependence among observations; if that structure is present and ignored, standard errors and intervals can be misleading. The registry does not report evidence of clustering, an over-dispersion assessment, or a model-based adjustment for it. This concept is therefore a general statistical consideration, not a claim about a problem identified in this trial.

What analysis details are available?

The record labels the trial randomized, double-masked, and parallel-group. It posts a primary outcome and an unadjusted comparison, but does not report the test or interval-construction method, covariate adjustment, handling of missing outcome responses, or an analysis population definition. The record also lists zero posted analyses. Without those details, readers cannot determine whether the reported comparison followed a prespecified plan, whether all randomized participants were included in the same way, or how departures from the intended follow-up were handled. Those details are not reported in the registry record and should not be inferred from the numerical output alone.

10. Confidence Intervals and Precision

Precision concerns how narrowly the data locate the comparative effect. The posted risk-difference estimate has a confidence interval that spans negative and positive values. This means the interval includes a possible advantage in either direction; the study does not estimate the direction narrowly enough to rule out both possibilities. The interval should be considered with the arm counts, which are 14 participants in each arm, rather than treating the point estimate as a settled result.

The p-value of 0.541 is also consistent with uncertainty, but it answers a different question from the interval. It does not quantify the range of plausible effects, and it is not evidence that the treatments are identical. The interval is the more direct expression of how much uncertainty surrounds the estimated difference. Because the registry does not state a clinically meaningful difference or an equivalence margin, the interval cannot be judged against such a threshold from the record.

General statistical principle: wider confidence intervals indicate less precision, while narrower intervals indicate more precision under the method used. Precision depends on the amount and structure of information, not just on whether a test crosses a significance threshold. The original trial’s target precision and sample-size rationale are not reported in the registry record. The posted estimate therefore supports a description of the observed comparison and its uncertainty, but not a precise claim about the size or direction of a broader treatment difference.

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 participants per arm, not total events. The record gives illustrations for detecting 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For each of those planning scenarios, the figures are listed separately for 80% power and 90% power. In plain language, a power level describes the probability that a planned study would detect an effect of the specified size under the stated assumptions, if that effect were the true effect and the assumptions held. The 90% power column calls for more participants per arm than the 80% column for each listed scenario.

The listed planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. These are planning illustrations based on the observed effect, not the original trial’s documented design assumptions. The original sample-size rationale and assumptions are not reported in the registry record.

The table gives participants per arm for 80% power and participants per arm for 90% power. The values increase when planning for a smaller fraction of the observed effect: detecting a smaller effect generally requires more participants, all else equal. The curve should be read as a visual representation of the same planning relationship, not as a report of what the completed pilot was powered to detect. These figures are not observed power.

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 = 0.929; treatment proportion p₁ = 0.857; average p̄ = 0.893.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4374 = 0.8573.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4345 = 0.3657.
4. n = (0.8573 + 0.3657)² / (-0.0714)² = 293.2, rounded up to 294 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 <- 0.928571428571429                          # control proportion
p1 <- 0.857142857142857                          # 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(1749605)
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 = 294 (80% power), 392 (90% power)
 75% of observed effect: n per arm = 484 (80% power), 647 (90% power)
 50% of observed effect: n per arm = 1,000 (80% power), 1,338 (90% power)
power.prop.test: 293.2 
Simulated power at n = 294 per arm: 0.811 (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. Multiplicity, Missing Data and Analysis Populations

The registry record posts one primary outcome: participants with clinical cure at day 7. It reports no secondary outcome results and lists zero posted analyses. The registry’s outcome section therefore offers no set of additional reported tests from which to assess how multiple comparisons may have been handled.

Multiplicity is a general statistical concern when several outcomes, time points, subgroups, or comparisons are tested. With repeated testing, the chance of at least one apparently notable result can rise unless the analysis plan addresses that issue. The registry record does not report whether additional outcomes or analyses were prespecified, whether any multiplicity adjustment was planned, or whether the primary outcome was the only planned efficacy analysis. No adjustment method should be inferred from the available record.

The record does not report a missing-data method, the number of participants with unavailable day-7 responses, or rules for classifying such responses. The endpoint description specifies a telephone call and a yes-or-no response, but it does not describe follow-up completion or how nonresponse would be treated. The outcome lists 14 participants per arm, while enrollment is recorded as 35; the registry does not explain the relationship between the enrollment figure and the outcome populations. This is a reporting gap, not evidence by itself about why the figures differ.

The record also does not identify an intention-to-treat, per-protocol, or other analysis population, and does not state whether participants were analyzed according to random assignment. These omissions matter because analysis populations and missing-data decisions can affect the interpretation of randomized comparisons. The available results can be described as posted, but the registry does not provide enough detail to verify the handling of incomplete follow-up or to reproduce the analysis choices.

14. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent non-serious adverse event terms

The safety record reports serious adverse events for 18 participants at risk in the nitrofurantoin group and 17 in the ciprofloxacin group. It lists zero serious adverse events in each group and zero deaths in each group. For other adverse events, it reports one event in each group, with 18 and 17 participants at risk, respectively. No top serious-event terms are listed.

These figures describe the safety counts posted in the registry record. The participants-at-risk counts differ from the primary outcome counts, and the registry does not explain the relationship between these safety populations and the outcome populations. It also does not provide event descriptions for the other adverse events, severity details, timing, or a more complete account of event ascertainment. The absence of a listed serious adverse event in these groups should not be interpreted as proof that a regimen has no risk. The counts are limited to the trial’s recorded safety populations and reporting.

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

The posted results show that most participants included in the day-7 outcome in both arms reported complete symptom resolution. The registry records 13 of 14 participants with clinical cure in the nitrofurantoin arm and 12 of 14 in the ciprofloxacin arm. The comparative estimate is imprecise: its confidence interval includes differences in either direction, and the unadjusted p-value is 0.541. These results describe the observed trial data; they do not establish that the regimens are equivalent or that one is superior.

The endpoint is a participant-reported answer at a single specified follow-up. It does not establish how quickly symptoms changed, whether symptoms returned later, or what happened beyond day 7. The registry does not report secondary outcome results. The posted safety counts show no serious adverse events or deaths in either reported group and one other adverse event in each, but the event details and broader safety context are not reported.

The trial is identified as a pilot and has a recorded enrollment of 35. The primary outcome lists 14 participants in each arm, and the registry does not explain the relation between these figures. The record also does not report the original sample-size rationale, missing-data handling, or analysis populations. These limitations mean that the findings should be read as a small, incomplete registry-level account of one short-term comparison, not as a definitive estimate applicable to all patients or settings.

General statistical principle: a lack of a statistically significant result is not the same as evidence of no effect. Determining equivalence requires a design that defines an acceptable difference in advance and estimates the effect precisely enough to assess that margin. Such a margin or design is not reported in the registry record. The data support describing the observed counts and their uncertainty, but not a treatment recommendation or a conclusive claim about comparative efficacy.

16. Why This Trial Matters Statistically

This trial illustrates why a randomized comparison should be read through both its observed counts and its uncertainty. The posted cure counts are close in size, but the confidence interval for the comparative estimate spans effects in either direction. A point estimate can appear to favor one arm while the interval makes clear that the estimate is not precise enough to settle the direction of an underlying difference.

The registry also illustrates the distinction between a pilot result and a definitive comparison. The trial is labeled a pilot, while the outcome groups are small. The planning illustrations show how larger participant counts would be needed when the target effect is smaller, under the stated planning assumptions. Those illustrations do not establish what the original investigators planned or what the completed trial could reliably detect.

Reporting detail matters as much as the headline estimate. The registry defines a participant-reported endpoint and posts arm-level counts, but does not report the missing-data approach, analysis population, or original statistical plan. The enrollment figure and the outcome denominators are not reconciled in the record. These omissions limit independent assessment of how the randomized comparison was carried through to analysis.

For clinical researchers and biostatisticians, the central lesson is methodological: distinguish observed proportions from comparative effect estimates, read confidence intervals as measures of uncertainty, and avoid treating a nonsignificant p-value as proof of equality. Clear reporting of follow-up, analysis populations, and prespecified methods is necessary to interpret the numerical result with confidence.

17. 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.

This trial has a small posted outcome population, with 14 participants in each arm. The registry records enrollment as 35 but does not explain how that figure relates to the outcome denominators. It does not report whether participants were unavailable for the day-7 telephone assessment, how many calls were unsuccessful, or how missing responses were handled. Consequently, the completeness of the primary outcome cannot be assessed from the record.

The primary endpoint is based on a yes-or-no report of complete symptom resolution at day 7. The registry does not report a validated symptom scale, a clinician assessment, or an additional measure confirming the response. It also does not post secondary outcome results, so the record does not address outcomes beyond this single assessment or provide a broader account of symptom course.

The original sample-size justification and statistical analysis plan are not reported. The record does not specify the analysis population, allocation sequence procedures, concealment, or detailed masking arrangements. It also does not report baseline characteristics, which limits assessment of the participants represented and the comparability of the randomized groups in the posted results.

Safety reporting is limited to event counts and participants at risk. The record provides no descriptions for the listed other adverse events, and no serious-event terms are listed. These reporting limitations do not establish that events were absent beyond the recorded counts; they restrict what can be concluded from the registry record. The findings are therefore best considered a limited report of a pilot comparison, with substantial uncertainty and incomplete methodological detail.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: A Pilot Comparison of Short-course Nitrofurantoin in Females With Uncomplicated Bacterial Cystitis in the Emergency Department — NCT01749605.
• Registry record last updated 2017-05-31; status last verified 2017-05.
• Results first posted 2017-04-27.
• 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.

21. Record Summary

The registry describes a completed phase 4, randomized, double-masked, parallel-group pilot comparing nitrofurantoin monohydrate/macrocrystals 100 mg twice daily for 3 days with ciprofloxacin 250 mg twice daily for 3 days in females with uncomplicated bacterial cystitis presenting to an emergency department. Enrollment is recorded as 35.

The primary outcome was participant-reported clinical cure at day 7. The posted counts are 13 of 14 for nitrofurantoin and 12 of 14 for ciprofloxacin. The unadjusted p-value is 0.541, and the confidence interval for the risk difference spans values in both directions. The record lists zero serious adverse events and zero deaths in each safety group, and one other adverse event in each group.

The original sample-size rationale, missing-data handling, analysis populations, and detailed statistical plan are not reported in the registry record. The outcome counts describe a small pilot comparison and do not establish superiority or equivalence.