Acupuncture for Female IC/PBSyndrome and Its Effect on the Urinary Microbiome: A Randomized Controlled Trial: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Acupuncture for Female IC/PBSyndrome and Its Effect on the Urinary Microbiome: A Randomized Controlled Trial (NCT02232282), a randomized na study. The primary outcome is Efficacy of Acupuncture to Reduce Pain in Women With Interstitial Cystitis/Painful Bladder Syndrome.

2. Clinical Question

The registry record frames the study as a randomized comparison of acupuncture with sham or minimal treatment, with a further hypothesis about urinary microbiome differences among acupuncture responders. The posted primary result concerns pain change, not microbiome findings. Urinary microbiome results are not reported in the registry record.

The primary measure is change in worst pain on the Brief Pain Inventory-Short Form, calculated as the 6 weeks score minus the baseline score. A negative change therefore represents a lower score at 6 weeks than at baseline. The comparison asks whether the average change differed between standard and minimal acupuncture, not whether every participant changed in the same way.

The registry record reports 22 enrolled participants, while the primary arm summaries include 10 and 11 participants. It does not explain the difference between enrollment and the number represented in those summaries. The registry record also lists tolerability and safety as secondary outcomes, but detailed secondary outcome results are not reported in the registry record.

3. Trial Design

The registry record describes a randomized, single-masked, parallel-group trial. It lists 22 participants enrolled and the study status as completed. The condition fields name painful bladder syndrome and interstitial cystitis. The sponsor is Loyola University. The listed phase is NA; the record does not give a drug-development phase.

Participants were assigned to standard acupuncture treatment or minimal acupuncture. The arm descriptions indicate that each approach was paired with medical management of interstitial cystitis. For the minimal-acupuncture condition, the registry describes superficial needle insertion at locations not recognized as true acupoints. For standard acupuncture, the description names 4 gates plus GV 20, but the description is truncated and does not provide a complete protocol.

The arm descriptions state that fifteen participants would be allocated to each group, whereas the posted primary summaries include 10 in Minimal Acupuncture and 11 in Standard Acupuncture Treatment. The registry record does not explain this difference or report the reasons why the analysis summaries contain fewer participants than the enrollment total. These are distinct counts: the enrollment figure is not interchangeable with the group sizes shown for the primary outcome.

The primary outcome timeframe is 0 weeks and 6 weeks, corresponding to baseline and the 6-week assessment. The registry identifies the outcome as a least-squares mean of change in worst pain and gives standard errors for the arm summaries. Allocation concealment procedures, the masking target, and details about how masking was maintained are not reported in the registry record. The record also does not report the original sample-size justification, the planned analysis model, or whether interim analyses were planned.

The record lists tolerability and safety as secondary outcomes. It describes four outcome measures, but detailed results for those secondary outcomes are not reported in the registry record. Although the study title and hypothesis refer to urinary microbiome differences, microbiome results 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.

Overall Study

Analysis population for the primary outcome, as defined in the registry: All participants were included.

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 Efficacy of Acupuncture to Reduce Pain in Women With Interstitial Cystitis/Painful Bladder Syndrome, measured over 0 weeks, 6 weeks.

The primary endpoint is change in worst pain, measured with the Brief Pain Inventory-Short Form. The scale ranges from 0 to 10, and higher scores indicate more pain. Change is calculated by subtracting the baseline score from the score at 6 weeks. A negative change means the later score was lower than the baseline score; a positive change would mean it was higher.

Change scores provide a way to describe how pain ratings shifted over the stated follow-up period. The comparison between groups then describes whether their average shifts were different. This is not the same as comparing only the final scores, and it does not show the pattern of pain ratings at every point during follow-up.

The registry identifies the arm results as least-squares means and reports standard errors. A least-squares mean is generally a model-based group mean; however, the specific model and any adjustments used for these results are not reported in the registry record. The posted values are -2.08 for Minimal Acupuncture and -2.91 for Standard Acupuncture Treatment. The negative values indicate decreases in the group-average pain scores from baseline to 6 weeks. The endpoint is relevant to the stated clinical question because pain is a central symptom in the named conditions, but the result alone does not characterize other symptoms, functioning, or longer-term outcomes.

7. Results Posted in the Registry

• Minimal Acupuncture: mean -2.08 versus -2.91 on control; difference 0.83 (95% CI -0.93 to 2.59), standardized effect d = 0.40; z-test p = 0.357.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: it is a score-based measure, summarized as a mean change. For a continuous endpoint, the mean describes the average value in a group, while each participant's value can differ from that average. The two reported group means are least-squares means, and the registry lists standard errors as their dispersion measure. A standard error describes the precision of an estimated mean; it is not the same as the spread of individual participant scores.

Change is defined as the score at 6 weeks minus the baseline score. This direction is important: negative arm estimates correspond to lower scores at follow-up than at baseline. The comparison uses the group mean changes and reports their difference. The comparison estimate of 0.83 is oriented as Minimal Acupuncture minus Standard Acupuncture Treatment, consistent with the listed group values. The meaning of a positive or negative contrast depends on that ordering and on the endpoint's direction.

The registry identifies the arm estimates as least-squares means. In general, least-squares means are estimates produced from a statistical model, rather than necessarily being simple arithmetic averages. A model can account for specified features of the data, but the registry record does not report which model was used, whether covariates were included, or how repeated measurements were handled. Those details should not be inferred from the label alone.

A standard error is commonly used to quantify uncertainty in an estimated mean. It tends to be smaller when an estimate is more precise and larger when it is less precise. Its interpretation depends on the analysis and assumptions used to calculate it. The registry does not provide individual participant outcomes, so the observed score distribution and the extent of within-group variation cannot be directly inspected from the posted arm summaries.

The group contrast is accompanied by a confidence interval from -0.934 to 2.595. In general, a confidence interval expresses the uncertainty around an estimate under a statistical procedure and its assumptions. Here, the interval crosses zero, so it includes a value representing no difference in average change. The interval also includes values on either side of zero. That breadth cautions against treating the point estimate as a settled or highly precise contrast.

The reported unadjusted p-value is 0.357. In general, a p-value describes how compatible the observed data are with a specified null hypothesis under the statistical model; it is not the probability that the null hypothesis is true, nor a direct measure of clinical importance. The registry record does not report a formal statistical analysis entry, and no adjustment for multiple comparisons is described. Accordingly, the posted p-value should be read as an unadjusted comparison rather than as evidence that a multiplicity procedure was applied.

The comparison is a summary-statistic re-calculation, and the pooled standard deviation is marked as approximate. In general, pooling variability estimates assumes a suitable common measure of spread across groups. When variability differs across groups, an equal-variance approach can misrepresent uncertainty. Over-dispersion means that observed variability is greater than a model assumes; if present, it can make standard errors too small and confidence intervals too narrow. The registry record does not report a diagnostic assessment of variance or over-dispersion, and individual data are unavailable in the posted summaries to assess these features.

Random allocation is useful because, when implemented as intended, it aims to make the groups comparable in expectation at the start of a study. It does not guarantee that small groups will have closely matched baseline characteristics, and the record does not post baseline characteristics for evaluating balance. The record describes the trial as single-masked but does not specify who was masked or report an assessment of masking. Thus the design label alone does not show how effectively expectations were controlled.

Missing outcome data can affect a change-score analysis if participants with unavailable scores differ from those with observed scores. Statistical approaches can address missingness in different ways, but their assumptions and implementation matter. The primary outcome description says all participants were included; the registry record does not report the number with missing baseline or follow-up scores, a missing-data method, or a sensitivity analysis. It is therefore not possible to determine from the record whether missingness altered the estimate.

The comparison and interval were recalculated from the posted summary statistics and are unadjusted. They do not replace a full analysis based on participant-level data. The discrepancy flag is false, so there is no identified discrepancy between the sponsor's own analysis and the recalculation that would make the sponsor's analysis take precedence. However, details of any sponsor analysis are not reported in the registry record, and the calculated contrast should not be mistaken for a documented adjusted analysis.

Finally, statistical significance and effect size address different questions. A p-value concerns compatibility with a null hypothesis under assumptions; an estimated difference describes the scale and direction of the observed contrast; and a confidence interval conveys uncertainty around that estimate. Each is needed for a careful reading. None alone establishes causation, clinical importance, or whether the result applies beyond the participants and timeframe represented in the registry record.

10. Confidence Intervals and Precision

The point estimate for the group difference in mean pain change is 0.83, with a confidence interval from -0.934 to 2.595. The interval is important because it shows how uncertain the estimated contrast is, not just the single value at its center. It includes zero, so a no-difference value is compatible with the interval, as are differences in either direction.

The interval spans values that would imply a contrast favoring either group, given the subtraction order of Minimal Acupuncture minus Standard Acupuncture Treatment. This means the posted result does not determine a precise direction for the difference in average change. The interval's breadth reflects limited precision in the estimated contrast. The unadjusted p-value of 0.357 is consistent with the interval including zero, but the interval is more informative about the range of estimates compatible with the calculation than the p-value alone.

Precision is affected by the amount of information available and by variability in the outcome. The posted summaries include 10 participants in one group and 11 in the other, with standard errors of 0.68 and 0.59. These standard errors concern the estimated arm means, whereas the confidence interval concerns the contrast. The approximate pooled standard deviation is 2.051; it is a derived variability estimate, not a direct description of every participant's score.

The confidence interval is based on a simple unadjusted re-calculation from posted summaries. It does not account for undisclosed modeling choices, missing-data procedures, or adjustments that might have been used in an analysis not described in the registry record. The interval should therefore be understood as conditional on the re-calculation and its assumptions. A narrow interval would indicate greater statistical precision, but would not by itself establish clinical importance; this interval leaves substantial uncertainty about the magnitude and direction of the group contrast.

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 sample-size figures are planning illustrations based on fractions of the observed effect, not the original design targets for this trial. The assumptions stated for these illustrations 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 sample-size assumptions and justification are not reported in the registry record.

For this continuous-outcome comparison, the figures are participants per arm, not total participants and not total events. The 80% power column describes the number of participants per arm in a hypothetical design intended to have an 80% chance of detecting the specified effect under the planning assumptions, if that effect were the true one. The 90% power column describes the corresponding hypothetical design with a 90% chance under those same assumptions. These are planning concepts, not guarantees about the result of a future study.

The rows use the observed effect, 75% of the observed effect, and 50% of the observed effect. The estimated participants per arm increase as the target effect becomes smaller: for example, the row planning for 75% of the observed effect lists 171 for 80% power and 229 for 90% power, while the row planning for 50% lists 384 and 514. Smaller effects generally require more participants because they are harder to distinguish from background variation.

These calculations are not observed power. They do not describe the probability that this completed trial detected an effect after its results were known. They are illustrations of how planning requirements change with the chosen effect size and power target, under the stated assumptions. The registry record does not report that these sample sizes were used to design the trial.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 0.830; pooled standard deviation σ = 2.051.
2. n = 2 × (1.96 + 0.842)² × 2.051² / 0.830² = 95.8, rounded up to 96 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 <- 0.83                      # observed difference in means
sigma <- 2.050763657506                     # 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(2232282)
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 = 96 (80% power), 129 (90% power)
 75% of observed effect: n per arm = 171 (80% power), 229 (90% power)
 50% of observed effect: n per arm = 384 (80% power), 514 (90% power)
power.t.test: 96.8 
Simulated power at n = 96 per arm: 0.793 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry record lists two secondary outcomes: tolerability and safety of acupuncture in women with interstitial cystitis/painful bladder syndrome. It also reports four outcome measures, but detailed secondary results and analysis specifications are not reported in the registry record. The number of formal analysis entries is zero. The record does not state which outcomes were tested together, whether the primary endpoint was designated before analysis, or whether a multiplicity adjustment was planned or applied.

Multiplicity arises when several outcomes, time points, or comparisons are examined. In general, conducting many statistical tests can increase the chance of finding an apparently notable result by chance. Methods such as adjusting significance thresholds or prioritizing a prespecified primary outcome can address this issue, but no such approach is described in the registry record. The posted unadjusted p-value should not be taken as evidence of multiplicity control.

The primary outcome description says all participants were included. Yet the enrollment total is 22, and the arm summaries contain 10 and 11 participants. The record does not explain that difference, report the number of participants with complete baseline and follow-up scores, or describe exclusions from the primary analysis. It also does not report how missing measurements were handled, whether an intention-to-treat approach was used, or whether sensitivity analyses examined alternative assumptions about missing data.

These omissions matter because missingness and analysis-population choices can influence a change-score comparison. In general, excluding participants with unavailable outcomes may produce a biased estimate if the likelihood of missingness is related to pain or treatment assignment. Methods that retain participants under explicit assumptions can reduce some concerns, but the assumptions need to be reported and evaluated. No method can be attributed to this trial from the available record.

The stated population label does not resolve the issue: the record's phrase that all participants were included is not accompanied by a participant flow or a clear accounting linking enrollment to the analyzed groups. Baseline characteristics, reasons for non-inclusion, and outcome completion by group are not reported in the registry record. Consequently, the completeness and representativeness of the primary analysis cannot be independently assessed.

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 0% reporting threshold.

The serious adverse event summaries report 0 affected participants in Minimal Acupuncture among 10 at risk, and 0 affected participants in Standard Acupuncture Treatment among 11 at risk. The deaths count is 0 in each group. No serious adverse event terms are listed in the registry record.

These figures describe the events reported for the participants counted as at risk; they do not show that an event is impossible or that a treatment is free of risk. With small group counts, the absence of a reported serious event provides limited information about uncommon events. The registry record does not give detailed definitions, monitoring procedures, event timing, or a narrative account of adverse events.

The record also lists safety and tolerability as secondary outcomes, but the detailed results for those outcomes are not reported in the registry record. The serious-event summary should therefore be read narrowly: it reports no serious adverse events and no deaths in either posted group summary, but it does not provide a complete account of all possible symptoms, minor events, or tolerability findings.

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

The posted results show decreases in average worst-pain scores from baseline to 6 weeks in both groups: -2.08 for Minimal Acupuncture and -2.91 for Standard Acupuncture Treatment. The estimated difference in average change is 0.83, oriented as Minimal Acupuncture minus Standard Acupuncture Treatment. Its confidence interval, from -0.934 to 2.595, includes zero and values on both sides of zero. The unadjusted p-value is 0.357. Taken together, these statistics show that the estimated group contrast is uncertain.

They do not establish that the groups are identical. A result that does not distinguish the group means statistically can arise when there is little difference, when the estimate is imprecise, or both. The interval demonstrates that multiple values for the underlying contrast remain compatible with the summary-statistic calculation. The posted result is not precise enough to support a firm conclusion about the direction or size of the between-group difference.

The two within-group decreases should not be interpreted as proof that either assigned approach caused a decrease. Change over time can reflect several influences, and a within-group comparison is not the same as a randomized between-group comparison. The randomized comparison is the more relevant estimate for asking whether the groups differed, but its uncertainty is substantial and the registry record does not explain the gap between enrollment and the arm summaries.

The findings are restricted to the recorded pain measure and the 6-week timeframe. They do not establish longer-term outcomes, changes in urinary microbiome, or effects on other symptoms. The study hypothesis includes a urinary microbiome question, but corresponding results are not reported in the registry record. The posted serious-event counts are also limited information about safety, particularly for events that may be uncommon.

These results should be read as a small trial's reported group summaries and an unadjusted re-calculation, not as a definitive assessment of clinical benefit or harm. The registry record does not provide the analysis details, missing-data methods, or full secondary results needed to resolve several important uncertainties.

16. Why This Trial Matters Statistically

This trial illustrates why a point estimate should be read alongside its confidence interval. The estimated difference in mean change is 0.83, but the interval extends from -0.934 to 2.595. The single estimate gives a concise contrast; the interval makes clear that the available data do not pin that contrast down precisely. The unadjusted p-value of 0.357 is not a substitute for considering that range.

It also highlights the distinction between a change within each group and a difference between groups. Both arm means are negative, indicating reductions in the measured score from baseline to 6 weeks, yet the comparison of those changes is uncertain. Describing only the within-group changes would not answer the randomized comparative question.

The record's counts raise another statistical issue: enrollment is 22, while the arm summaries contain 10 and 11 participants. Because the registry does not reconcile these counts or explain missing outcomes, readers cannot fully evaluate which participants contributed to the primary estimates. Transparent participant flow and analysis-population reporting are essential for understanding the reach of a result.

Finally, the trial's title and hypothesis refer to the urinary microbiome, but the posted outcome description and comparative result address pain change. This distinction matters: a study's broad scientific motivation does not mean every stated question has a reported answer. The registry record makes the pain comparison available while leaving microbiome and detailed secondary results unreported. Statistically, the example reinforces the value of clear outcome definitions, analysis methods, and complete reporting alongside effect estimates.

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.

The posted primary summaries represent small groups, with 10 participants in Minimal Acupuncture and 11 in Standard Acupuncture Treatment, and the confidence interval for the difference is broad. This limits precision and leaves considerable uncertainty about the contrast. The enrollment total is 22, but the registry record does not explain why the group summaries account for fewer participants than that total.

The registry record does not report a complete participant flow, baseline characteristics, reasons for missing outcomes, or how missing data were handled. Although the primary outcome description says all participants were included, the group counts do not clarify how that statement relates to the enrollment total. Without this accounting, the analysis population and potential selection effects cannot be assessed.

The statistical model underlying the least-squares means is not described. Details of covariate adjustment, repeated-measures handling, and model diagnostics are not reported in the registry record. The displayed comparison is an unadjusted summary-statistic re-calculation, and its pooled standard deviation is approximate. It cannot reproduce or verify a participant-level model that is not documented.

The record identifies the study as single-masked but does not specify who was masked or how masking was assessed. The intervention descriptions are incomplete, and the record does not provide enough detail to evaluate treatment delivery or adherence. Detailed results for the named tolerability and safety outcomes are not reported, nor are urinary microbiome results.

Finally, the reported primary timeframe ends at 6 weeks. Longer-term outcomes are not reported in the registry record. These limitations mean the result should be interpreted as a short-term, imprecise comparison based on limited posted summaries, rather than as a comprehensive account of efficacy, safety, or microbiome effects.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Acupuncture for Female IC/PBSyndrome and Its Effect on the Urinary Microbiome: A Randomized Controlled Trial — NCT02232282.
• Registry record last updated 2022-04-14; status last verified 2022-03.
• Results first posted 2021-03-25.
• 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 record describes a completed randomized, single-masked, parallel-group trial of standard acupuncture and minimal acupuncture for women with interstitial cystitis/painful bladder syndrome. It reports 22 participants enrolled and identifies change in worst pain from baseline to 6 weeks as the primary outcome.

The primary arm summaries are -2.08 for Minimal Acupuncture and -2.91 for Standard Acupuncture Treatment. The estimated difference, Minimal Acupuncture minus Standard Acupuncture Treatment, is 0.83, with a confidence interval from -0.934 to 2.595 and an unadjusted p-value of 0.357. The interval includes zero and is broad, indicating substantial uncertainty in the group contrast.

The posted group counts are 10 and 11, and the record does not explain their relationship to total enrollment. Detailed secondary outcome results, analysis methods, missing-data procedures, and urinary microbiome findings are not reported in the registry record. The serious adverse event summary lists zero affected participants and zero deaths in each group.