RhinAer Procedure for Treatment of Chronic Rhinitis Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for RhinAer Procedure for Treatment of Chronic Rhinitis Study (NCT04533438), a randomized na study. The primary outcome is Reflective Total Nasal Symptom Score (rTNSS) Responder Rate.

2. Clinical Question

The registry record describes a prospective, randomized controlled trial comparing the procedure with sham control. The primary outcome is a count of participants classified as responders, rather than a comparison of average symptom scores. A responder was defined as an individual with at least 30% improvement, meaning a decrease, in rTNSS from baseline. The registry reports 52 responders among 77 participants in the Active Treatment group and 16 among 39 in the Sham Control group.

This question is about the observed responder outcome at the specified follow-up, not about every symptom, later outcomes, or a lasting effect beyond the recorded timeframe. The record identifies the trial as crossover, but the posted primary result does not explain whether or how observations after crossover contribute to this comparison. That detail is not reported in the registry record.

3. Trial Design

RHINTRAC is a prospective, multicenter, randomized controlled trial of the RhinAer procedure compared with sham control in participants with chronic rhinitis. The record lists single masking and a crossover model. It gives an enrollment of 116 and a completed status. The record lists a start date of 2020-07-31 and a primary completion date of 2021-04-09.

The active procedure used the RhinAer Stylus and Aerin Console to deliver bipolar radiofrequency energy to tissue. In the control procedure, the Stylus was used and audible sounds simulated active treatment, but radiofrequency energy was not generated or delivered. The control description says other aspects of the procedure were the same as in active treatment, although the record excerpt does not fully describe all procedural details.

The primary outcome was the rTNSS responder rate at the 3 months visit following the study procedure. The record lists 77 participants for Active Treatment and 39 for Sham Control in the posted result. It does not explain the relationship between these outcome groups and the crossover sequence, whether all randomized participants contributed to this endpoint, or how crossover observations were handled. Those details are not reported in the registry record.

The record lists three secondary outcomes: rTNSS mean change, rTNSS mean change, and the percentage of participants with treatment-related events. It also lists five outcome measures overall, but the posted registry record does not give enough detail to resolve the duplicate wording or explain the relation between the listed outcome measures and the secondary outcomes. The sponsor is Aerin Medical. The trial is marked completed; that status does not by itself establish that every planned analysis or all follow-up information is present in the 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: There was no wash out or run in for this study

Initial Enrollment

Crossover Period

Reasons for not completing this period:

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 Reflective Total Nasal Symptom Score (rTNSS) Responder Rate, measured over 3 months visit following the study procedure..

The primary endpoint is the Reflective Total Nasal Symptom Score (rTNSS) responder rate at the 3 months visit following the study procedure. The rTNSS is a patient self-rating of four nasal symptoms: rhinorrhea, nasal congestion, nasal itching, and sneezing. Each symptom is scored from 0, absent, through 3, severe; their sum has a maximum of 12, indicating the most severe symptoms.

For this trial, a participant was classified as a responder if their rTNSS decreased from baseline by at least 30%. The protocol’s stated baseline criteria required a rhinorrhea rating of 2 or 3, a congestion rating of 1, 2, or 3, and a total rTNSS score of at least 6. The endpoint therefore converts a change in a self-rated symptom score into a participant-level yes-or-no outcome.

Responder outcomes are often used to express whether participants crossed a prespecified threshold of change, rather than relying only on the average change across a group. This can make the result easier to interpret as the frequency of participants meeting the trial’s definition of improvement. It also discards some information about the size of each participant’s score change: participants meeting the threshold are counted alike, and changes that do not meet it are not counted as responses. The registry record does not report the rationale for selecting the 30% threshold.

7. Results Posted in the Registry

• Active Treatment: 67.5% (52/77) versus 41.0% (16/39) on control; risk difference 26.5 percentage points (95% CI 7.9 to 45.2), risk ratio 1.65 (1.10–2.47); unadjusted two-proportion z-test p = 0.006.

8. Statistical Interpretation

9. Statistical Methods Explained

What kind of outcome is being compared?

The primary outcome is binary at the participant level: each participant either meets the responder definition or does not. The threshold is at least 30% improvement, defined as a decrease in rTNSS from baseline. The registry reports the number of participants classified as responders and the group sizes, so the primary comparison concerns proportions. This differs from comparing mean score changes, which would retain information about the amount of change rather than only whether a threshold was reached.

For a binary outcome, the risk or proportion in a group is the number of participants with the event divided by the number considered in that group. Here, response is the event being counted; it is not an adverse event. The posted proportions are 0.675 for Active Treatment and 0.410 for Sham Control. The risk difference gives the absolute separation between those proportions, reported as 0.265. The risk ratio, 1.646, describes their relative scale. The odds ratio, 2.99, uses odds rather than proportions directly. Each measure can be useful, but they answer different descriptions of the group contrast.

How should the confidence interval and p-value be read?

A confidence interval gives a range of values compatible with the observed data under the interval’s statistical assumptions and method. It conveys uncertainty about an effect estimate; it is not a range containing every participant’s outcome, nor a guarantee that the true value lies within the particular interval. The risk-difference interval is 0.079 to 0.452. The ratio-scale intervals are 1.096 to 2.473 for the risk ratio and 1.348 to 6.632 for the odds ratio. All are posted as unadjusted results.

A p-value evaluates how unusual data at least as extreme as those observed would be under a specified null model. The posted unadjusted p-value is 0.006. It should not be treated as an estimate of effect size, a probability that the null is true, or a measure of whether the result is important to patients. Interpretation also depends on the analysis choices, outcome definition, and any multiplicity of comparisons. The particular test and any multiplicity procedure are not reported in the registry record.

What does unadjusted mean?

An unadjusted comparison is presented without a reported adjustment for covariates or other modeling features. It is a direct summary of the posted group data on the stated scale. The registry record does not describe covariate adjustment, stratification, or a model used to estimate the result. It also does not give a statistical analysis plan, so it is not possible to determine whether the posted comparison matches a prespecified primary analysis or whether alternative analyses were planned.

The trial is labeled randomized, which is relevant to the intended comparison, but randomization alone does not answer all analysis questions. The record identifies a crossover model and single masking. It does not specify the sequence, timing, or analytical handling of the crossover, or whether the posted group comparison uses only a particular period. Crossover data can involve repeated observations from a participant; methods may need to account for that dependence. Whether such methods were used is not reported in the registry record. The simple group summaries should therefore be read as the posted result, without assuming a particular crossover model.

Why can over-dispersion matter in other outcomes?

Over-dispersion is a general statistical concern for count outcomes when variation is greater than a model expects. If ignored, standard errors and confidence intervals can be too small, making uncertainty look less than it is. It is not the main issue for this primary endpoint, which is a binary responder outcome rather than a count of multiple events per participant. The registry lists mean rTNSS change among secondary outcomes, but the posted record does not provide its results in the registry record for this analysis. No model or dispersion estimate is reported.

What remains unknown about the analysis?

The record gives group counts, proportions, effect estimates, confidence intervals, and an unadjusted p-value. It does not report the approach to missing primary outcomes, the definition of the analysis population, whether participants were analyzed according to randomized assignment, or whether any exclusions occurred. These omissions matter because the denominator and treatment of participants with missing outcomes can affect a responder proportion.

The record lists five outcome measures and three secondary outcomes, including duplicated wording for rTNSS mean change. It does not report how the primary outcome was prioritized relative to other analyses, whether adjustments were made for multiple comparisons, or whether interim analyses took place. It also does not report the original sample-size justification or trial-specific power assumptions. Without these details, the posted effect estimates can be described, but their relationship to all planned analyses cannot be fully assessed.

10. Confidence Intervals and Precision

The confidence intervals communicate the precision of the estimated group contrasts. For the risk difference, the posted estimate is 0.265, and the 95% confidence interval extends from 0.079 to 0.452. The interval gives a range of values compatible with the data under the method’s assumptions. Its lower endpoint is above zero, but the range of possible differences remains substantial; the point estimate is not the only plausible value.

On the relative scales, the risk ratio is 1.646, with a 95% confidence interval from 1.096 to 2.473, and the odds ratio is 2.99, with a 95% confidence interval from 1.348 to 6.632. These intervals do not express the same quantity as the risk-difference interval, so their widths should not be compared directly as though they used a common scale. All are posted as unadjusted estimates.

Precision is affected by the amount of information in the data and by the variability or event pattern. The group counts are 52 responders among 77 participants and 16 among 39 participants. The registry record does not provide a detailed account of missing data, exclusions, or the exact confidence-interval method. It also does not explain how the crossover design was reflected in these intervals. Those gaps limit how fully the uncertainty can be evaluated.

A confidence interval is not a prediction interval for individual participants, and it does not capture every source of uncertainty. It does not account automatically for unreported design choices, outcome selection, missingness, or multiple testing. The estimates therefore provide useful precision information for the posted comparison while leaving important features of the analysis unreported in the registry record.

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 illustrations based on the observed effect, not the trial’s original sample-size justification. They assume a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. For each planning scenario, the effect to detect is the stated fraction of the observed effect. The figures are participants per arm, not total participants or total events.

At 100% of the observed effect, the illustration gives 55 participants per arm for 80% power and 73 participants per arm for 90% power. At 75% of the observed effect, it gives 99 participants per arm for 80% power and 131 participants per arm for 90% power. At 50% of the observed effect, it gives 222 participants per arm for 80% power and 297 participants per arm for 90% power.

In plain terms, the 80% power column represents the planning number per arm under which a study would have an 80% chance of detecting the specified effect if the assumptions hold and that effect is real. The 90% power column represents the corresponding planning number for a 90% chance. These are design calculations, not observed power for RHINTRAC. Smaller effects require more participants under these assumptions, as reflected by the increasing figures when the assumed effect fraction becomes smaller.

These calculations do not establish that the original trial was designed using the same assumptions. The trial’s own sample-size rationale and original design assumptions are not reported in the registry record. A planning illustration based on the observed result is sensitive to that observed estimate and should not be treated as a guarantee that a future study will achieve a particular result.

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 = 0.410; treatment proportion p₁ = 0.675; average p̄ = 0.543.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7045 = 1.3808.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6791 = 0.5716.
4. n = (1.3808 + 0.5716)² / (0.2651)² = 54.3, rounded up to 55 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 <- 0.41025641025641                          # control proportion
p1 <- 0.675324675324675                          # 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(4533438)
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 = 55 (80% power), 73 (90% power)
 75% of observed effect: n per arm = 99 (80% power), 131 (90% power)
 50% of observed effect: n per arm = 222 (80% power), 297 (90% power)
power.prop.test: 54.3 
Simulated power at n = 55 per arm: 0.799 (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

Multiplicity arises when several outcomes, time points, subgroup comparisons, or analyses are tested. As the number of tests increases, the chance of at least one apparently unusual result can increase, even when no underlying effect exists. Statistical procedures can address this, but the registry record does not report whether any multiplicity adjustment was planned or applied. The posted primary p-value is unadjusted, and the record does not provide enough information to determine how it relates to all analyses conducted.

The registry lists the primary rTNSS responder rate and three secondary outcomes: rTNSS mean change, rTNSS mean change, and the percentage of participants with treatment-related events. It also lists five outcome measures overall. The repeated wording for rTNSS mean change is not clarified. A registry listing alone does not show whether every listed measure was analyzed, how outcomes were prioritized, or whether the reported measures reflect a final prespecified plan. Those details are not reported in the registry record.

Missing outcome data can affect both the numerator and denominator of a responder analysis. The record provides group counts for the posted primary result but does not state how many participants lacked an outcome, how such cases were handled, or whether any imputation or sensitivity analysis was used. It also does not describe the analysis population, exclusions, or whether the analysis followed randomized assignment. The listed group counts should be read as the denominators of the posted result, not as proof that every enrolled participant contributed.

The crossover label raises additional questions about which period and observations were included and how within-participant dependence was handled. The record does not report the sequence, timing, period-specific analysis, or a model for crossover data. It also does not report interim analyses, the statistical analysis plan, or the original sample-size justification. These omissions do not alter the posted numerical summaries, but they restrict assessment of whether the inference accounts for all planned outcomes and the design’s analysis requirements.

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.

Most frequent non-serious adverse event terms

The adverse-event record separates serious adverse events from other adverse events and reports counts with participants at risk. For RhinAer Treatment, the serious adverse event figures are 0 affected among 77 at risk; for Control Treatment, they are 0 among 39 at risk. The record also reports 0 deaths in each group.

For other adverse events, the record lists 7 affected among 77 at risk in RhinAer Treatment and 1 among 39 at risk in Control Treatment. These are counts of participants affected, not necessarily counts of every event occurrence. The summary does not name the individual events or give their severity, timing, duration, or relationship to treatment beyond the outcome’s label.

Zero serious adverse events in the posted record means none were counted in those groups under the registry’s reporting. It does not establish that serious events are impossible or that all aspects of safety were assessed. The record does not provide enough detail to determine completeness of safety follow-up, how events were collected, or how treatment-relatedness was assessed. The counts should be interpreted as registry-reported observations, not as a comprehensive safety conclusion.

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

The primary result describes how often participants met the trial’s responder definition at the 3 months visit following the study procedure. The posted counts were 52 of 77 in Active Treatment and 16 of 39 in Sham Control. The unadjusted risk difference was 0.265, with a 95% confidence interval from 0.079 to 0.452, and the unadjusted p-value was 0.006. These statistics describe the observed comparison in the registry record.

The result does not say that every participant experienced the same change. A responder classification depends on meeting the specified threshold; it does not report the full distribution of symptom-score changes. It also does not establish how long any change lasted beyond the stated follow-up, or whether the result applies to people who would not meet the protocol’s baseline symptom criteria. The registry record does not report results for all listed secondary outcomes in the registry record for this interpretation.

The figures do not, by themselves, resolve the statistical implications of the crossover design. The record does not explain whether the primary result includes observations after crossover or how those observations were analyzed. Missing-data handling, analysis population, and adjustment for multiple outcomes are also not reported. Those methodological details can affect the meaning and robustness of an estimate and should not be assumed from the group counts alone.

Nor does the primary symptom endpoint summarize safety. The registry reports no serious adverse events or deaths in either group and reports other adverse-event counts of 7 in RhinAer Treatment and 1 in Control Treatment. The detail available is limited, so these counts do not establish a comprehensive safety profile. Overall, the posted result is evidence about a particular responder definition, comparison, and follow-up point; it should not be extended to other outcomes or interpreted as medical advice.

16. Why This Trial Matters Statistically

RHINTRAC illustrates how a trial can turn a patient-rated symptom measure into a responder endpoint. The rTNSS captures four symptoms on an ordinal scale, and the primary outcome classifies participants according to whether their score decreased from baseline by at least 30%. Reporting both the responder counts and the score-based definition helps clarify what the binary outcome represents and what information it leaves out.

The result also demonstrates why absolute and relative effect measures should be distinguished. The risk difference of 0.265 describes the observed separation in responder proportions, while the risk ratio of 1.646 and odds ratio of 2.99 express the contrast on relative scales. Confidence intervals add information about precision, while the p-value addresses compatibility with a null model rather than effect size or clinical importance.

Statistically, the crossover designation makes analysis details especially relevant. A crossover design can involve repeated observations from the same participant, which may require accounting for their dependence. The registry record does not explain how its posted primary comparison handles that feature. Missing-data procedures, the analysis population, and multiplicity handling are also unreported. These are not minor interpretive details: they help determine which data the estimate summarizes and how uncertainty should be understood.

The sample-size illustrations make a separate point about planning. Under the stated assumptions, planning for smaller fractions of the observed effect requires larger participant counts per arm. Because those calculations use the observed effect and are not the original design rationale, they are useful for illustrating sensitivity to the effect size rather than documenting how the trial was planned.

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 registry record leaves several trial-specific uncertainties. Although the design is identified as crossover, the posted primary comparison does not describe the sequence, timing, or handling of crossover observations. It is therefore not possible to tell from the result alone whether the comparison uses an initial randomized period, later observations, or a model accounting for repeated measures within participants.

The record also does not report the original sample-size justification, the planned statistical analysis, the analysis population, or the handling of missing primary outcomes. The group denominators in the posted result do not explain whether participants were excluded or had missing outcome data. The listed secondary outcomes include repeated wording for rTNSS mean change, and the record does not clarify how these outcomes were prioritized or whether multiplicity was addressed.

The primary endpoint is a threshold-based classification. It does not retain the full magnitude of each participant’s change, and the record does not state the rationale for the at least 30% responder threshold. The reported follow-up is the 3 months visit following the study procedure; the primary result does not establish outcomes at other time points. The registry record lists the trial as single-masked but does not identify who was masked.

Safety reporting in the available record is limited to affected-participant counts for serious and other adverse events and deaths. Event descriptions and details of collection and follow-up are not reported in the registry record. These limitations concern what can be concluded from the registry entry; they do not establish that the trial team did not collect or analyze information that is absent from the record.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: RhinAer Procedure for Treatment of Chronic Rhinitis Study — NCT04533438.
• Registry record last updated 2025-05-02; status last verified 2025-04.
• Results first posted 2022-12-20.
• 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 RHINTRAC, a prospective, multicenter, randomized controlled crossover trial comparing RhinAer radiofrequency treatment with sham control for chronic rhinitis. It lists single masking, enrollment of 116, and completed status. The listed dates are 2020-07-31 for study start and 2021-04-09 for primary completion.

The primary endpoint is the rTNSS responder rate at the 3 months visit following the study procedure. The posted counts are 52 of 77 participants in Active Treatment and 16 of 39 in Sham Control. The unadjusted risk difference is 0.265, with a 95% confidence interval from 0.079 to 0.452; the unadjusted p-value is 0.006.

The registry reports 0 serious adverse events and 0 deaths in each group, alongside other adverse-event counts of 7 for RhinAer Treatment and 1 for Control Treatment. The record does not report the statistical analysis plan, missing-data handling, analysis population, crossover analysis details, multiplicity procedure, or original sample-size rationale.