Aspirin and Zileuton and Biomarker Expression in Nasal Tissue of Current Smokers: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Aspirin and Zileuton and Biomarker Expression in Nasal Tissue of Current Smokers (NCT02348203), a randomized phase 2 study. The primary outcome is Changes in a Smoking-related Gene Expression Signature Score in the Nasal Epithelium of Current Smokers.

2. Clinical Question

The registry describes this as a randomized phase II study of biomarkers related to tobacco use and carcinogenesis. Its primary question concerns a biological measure in nasal tissue, not the occurrence of lung cancer. The record states that prior research found a higher score in never smokers than in current smokers, and that an increased score implicated a more favorable intervention effect. That description gives context for the score, but it does not establish how a change in the score relates to later clinical outcomes.

The posted primary comparison is between the mean changes in the two arms. It is not a comparison of the participants’ final scores alone: the stated timeframe is baseline to the end of the 12-week intervention. The analysis includes 19 participants in Arm I and 21 in Arm II. The record says gene-expression analysis was restricted to samples meeting quality metrics, so these analysis counts should not be assumed to match the number enrolled or the participant-flow counts.

3. Trial Design

This is a randomized, single-masked, parallel-group phase II trial. The registry lists an enrollment of 63 participants and identifies current smokers and tobacco use disorder as the study population and condition. Participants were assigned to one of two arms: aspirin plus zileuton, or double placebo. The treatment period was 12 weeks. The record is marked completed.

In Arm I, participants received aspirin by mouth once daily and zileuton by mouth twice daily for 12 weeks, subject to unacceptable toxicity. In Arm II, participants received matching aspirin and zileuton placebos on the corresponding schedules. The registry also lists laboratory biomarker analysis as an intervention category. It does not identify which party was masked, so the meaning of single masking for participants, investigators, or outcome assessors is not reported in the registry record.

The trial’s enrollment is not the same as the number contributing to every endpoint. For the primary gene-expression outcome, 19 participants were analyzed in Arm I and 21 in Arm II; the registry explains that quality requirements for samples affected the analyzed numbers. Other posted outcomes have different arm-specific analysis counts. A complete account of who was randomized, who received treatment, who provided each sample, and why some records were not analyzed is not reported in the registry record.

The registry lists the study start as 2016-01-13 and primary completion as 2019-02-22. It does not report the original sample-size justification, detailed allocation procedure, protocol amendments, or the full statistical analysis plan. Those omissions limit what can be inferred about how the study was planned and how its analyses were selected.

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: The number of participants analyzed is different from the numbers provided in the Participant Flow Module because gene expression analysis was restricted to samples that met quality metrics.

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 Changes in a Smoking-related Gene Expression Signature Score in the Nasal Epithelium of Current Smokers, measured over Baseline to 12 weeks (End-of-intervention).

The primary endpoint is change in a smoking-related gene-expression signature score in nasal epithelium from baseline to 12 weeks, at the end of intervention. It is a continuous measure, reported as a mean and standard deviation. The score was derived from prior research. The registry states that higher scores had been observed in never smokers than in current smokers, and that an increased score implicated a more favorable intervention effect. It also states that the score has no minimum or maximum.

Gene-expression signatures are used to represent patterns across genes rather than a single gene measurement. In this trial, the nasal-tissue signature serves as a biomarker related to smoking. A biomarker can be useful for studying biological changes over a treatment period, but the score is not itself a lung-cancer diagnosis or a count of cancer cases. The registry does not report a threshold defining a meaningful change, nor does it report how a particular score difference predicts later disease.

The comparison of interest is the mean change in the combined-treatment arm relative to the mean change in the double-placebo arm. Because the endpoint is a change score, the interpretation concerns movement from baseline over the stated period. The number analyzed was 19 in Arm I and 21 in Arm II. The record notes that only samples meeting gene-expression quality metrics were included, an important qualification when interpreting the analyzed population.

7. Results Posted in the Registry

• Arm I (Aspirin, Zileuton): mean -0.15 versus 0.26 on control; difference -0.41 (95% CI -2.03 to 1.21), standardized effect d = -0.16; z-test p = 0.620.

8. Secondary Efficacy Endpoints

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

Changes in a Smoking-related Gene Expression Signature Score in the Nasal Epithelium of Current Smokers 10-14 Days Post Intervention

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Arm I (Aspirin, Zileuton): mean -0.24 versus -1.16 on control; difference 0.92 (95% CI -1.12 to 2.96), standardized effect d = 0.28; z-test p = 0.377.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm I (Aspirin, Zileuton) and the control. The interval gives the range of effects that remain compatible with the data.

Change in Urinary PGE-M Levels

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Arm I (Aspirin, Zileuton): mean -5.90 versus 0.71 on control; difference -6.61 (95% CI -13.71 to 0.49), standardized effect d = -0.56; z-test p = 0.068.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm I (Aspirin, Zileuton) and the control. The interval gives the range of effects that remain compatible with the data.

Change in Urinary LTE (4) Levels

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Arm I (Aspirin, Zileuton): mean -57.60 versus 35.20 on control; difference -92.80 (95% CI -140.63 to -44.97), standardized effect d = -1.15; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Arm I (Aspirin, Zileuton) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes extend the biomarker question beyond the primary nasal gene-expression score. The registry lists additional gene-expression signatures, urinary biomarkers, adverse events, a gender-related question, and metabolomic changes. The posted secondary results cover selected outcomes, including a short-term gene-expression measure and urinary biomarker measures. The overall pattern is not a uniform set of changes moving in the same direction across all measures.

These outcomes provide related biological and safety information, but they do not replace the primary comparison. They also do not turn the primary biomarker into a clinical endpoint. The registry does not report a demonstrated link between the secondary biomarker changes and later lung-cancer outcomes. Each measure has its own scale, timeframe, variability, and analyzed participant count, so the results should be interpreted outcome by outcome rather than combined into a single general conclusion.

The registry lists ten posted secondary outcomes, but it lists no reported analyses for them. The comparisons available in the posted summaries are unadjusted recalculations from summary statistics. Multiple testing matters because examining many outcomes creates more opportunities for apparently notable results to arise by chance. Without a reported multiplicity plan or adjusted analyses, secondary findings generally carry less inferential weight than a prespecified primary result, even when an individual estimate appears relatively clear.

The record does not identify which secondary outcomes were prioritized, whether all were planned before data collection, or how missing measurements were handled. It is therefore not possible to distinguish confirmatory secondary questions from exploratory ones based on the registry information. The secondary findings are best treated as descriptive and hypothesis-generating evidence, with attention to their uncertainty and the absence of a reported analysis plan.

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

• Changes in Three Lung Cancer Gene Signatures (an 80-gene Bronchial Signature, a PI3K Pathway Gene Signature and a Nasal Diagnostic Gene Signature) in the Nasal Epithelium of Current Smokers
• Changes in a Smoking-related Gene Expression Signature Score in the Nasal Epithelium of Current Smokers 10-14 Days Post Intervention
• Changes in Three Lung Cancer Gene Signatures (an 80-gene Bronchial Signature, a PI3K Pathway Gene Signature and a Nasal Diagnostic Gene Signature) in the Nasal Epithelium of Current Smokers 10-14 Days Post Intervention
• Change in Urinary PGE-M Levels
• Change in Urinary LTE (4) Levels
• Number of Participants Experiencing Possibly/Probably/Definitely-related Adverse Events
• Gender Effect on Smoking-related Gene Expression Signature
• Changes in the Metabolomics Profile of the Arachidonic Acid Pathway

9. Statistical Interpretation

10. Statistical Methods Explained

The posted outcome is continuous: each analyzed participant contributes a score change, and the arm summaries report means and standard deviations. A mean describes the average change in an arm. A standard deviation describes how dispersed individual changes are around that arm’s mean. Greater dispersion means that individual values vary more widely; it does not by itself indicate bias or a treatment effect.

What does the mean difference represent?

The reported contrast compares the mean change in Arm I with the mean change in Arm II. For the primary outcome, the registry lists a mean of -0.15 for Arm I and 0.26 for Arm II, with a mean difference of -0.41. The negative direction means the Arm I mean change was lower than the Arm II mean change. The estimate is expressed in the score’s own units, not as a percentage or as a standardized clinical outcome.

A difference between two sample means is an estimate of the corresponding difference in the populations from which the samples were drawn. It is subject to sampling variation: repeating a study with different participants could produce a different estimate. The confidence interval describes uncertainty around the estimate under the calculation’s assumptions. The confidence level and the precise analysis procedure for the posted interval are not reported in the registry record.

What does a confidence interval add?

A confidence interval gives a range of values compatible with the data and the method used to calculate it. For the primary contrast, the reported interval is -2.03 to 1.21. Because it spans both negative and positive values, the data do not pin down the direction of the population difference. The interval is not a guarantee that the true value lies inside it, and it does not identify which values are clinically important. The registry does not report a meaningful-change threshold for the score.

The interval is also informative about precision. A broad interval indicates less precision than a narrow interval, all else being equal. Precision depends on factors including the variability of the outcome and the number of analyzed participants. In this trial, the primary analysis counts were 19 and 21, and the arm-level standard deviations were 2.89 and 2.26. The registry notes that sample quality criteria limited which participants’ tissue samples entered the gene-expression analysis.

How should the p-value be read?

The unadjusted p-value for the primary comparison was 0.62. In general, a p-value describes how unusual results at least as discrepant as those observed would be under a specified null model and its assumptions. It is not the probability that the null hypothesis is true, nor is it a measure of the size or practical importance of a difference. The registry does not report the complete analysis specification, including the inferential procedure used by the study investigators. The posted comparison is an unadjusted recalculation from summary statistics.

Unadjusted means that the displayed comparison has not been modified to account for other endpoints or other statistical tests. It does not mean that the result is necessarily incorrect; it does mean that a reader should distinguish it from a prespecified, multiplicity-adjusted analysis. No reported analysis is listed for the primary outcome in the registry record, and the original statistical analysis plan is not reported.

Why does over-dispersion matter in general?

General explanation: when observations are more variable than a statistical model assumes, standard errors can be too small and intervals can be too narrow. The primary outcome is continuous and is summarized by means and standard deviations, rather than by an event count. The registry does not report a specific over-dispersion assessment or a model-based correction, so no claim about such a problem in this trial can be made from the record.

What is known about the design and analysis?

The registry identifies randomized allocation, single masking, and a parallel model. Those design features describe how the trial was organized, but they do not specify the statistical test, covariate adjustment, handling of missing data, or whether assumptions were checked. These details are not reported in the registry record. The sample-size planning illustration uses a two-sided significance level of 0.05, equal allocation, and a normal approximation, but those are assumptions for that illustration, not a documented account of the trial’s original design calculations.

11. Confidence Intervals and Precision

The primary mean difference is -0.41, with a reported confidence interval from -2.03 to 1.21. The interval extends from a negative value to a positive value, so the posted estimate does not establish the direction of the population difference with precision. The confidence level and the exact interval method are not reported in the registry record. The associated unadjusted p-value is 0.62.

The interval’s width matters because the point estimate alone can give a misleading impression of certainty. A mean difference of -0.41 is one estimate from the analyzed participants; the interval shows that appreciably different values are also compatible with the data and calculation. The arm-level standard deviations, 2.89 and 2.26, describe variability in the score changes, while the analyzed counts were 19 and 21. These features help explain why a sample mean difference should not be treated as an exact population effect.

Precision is not the same as clinical importance. The registry reports that the score has no minimum or maximum and gives a direction considered favorable based on prior research, but it does not define a smallest meaningful difference. It also does not report a relationship between a given score change and a later clinical outcome. Thus, the interval can be interpreted as statistical uncertainty about the mean contrast, but not as a range of treatment effects known to be clinically meaningful or harmless.

The primary analysis was limited to samples meeting gene-expression quality metrics. That restriction is documented, but the record does not provide the full information needed to evaluate how excluded samples might affect precision or representativeness. The posted interval should therefore be understood in the context of the analyzed samples and the unadjusted summary-statistic comparison, not as a complete account of uncertainty across every enrolled participant.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm, not a total across both arms and not total events. They use the observed effect as a starting point and show planning for 100%, 75%, and 50% of that effect. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. For time-to-event outcomes, the planning convention would be total events, but the outcomes are not time-to-event outcomes.

The 80% power column represents the number of participants per arm that the planning calculation estimates would give an 80% chance of detecting the specified effect under those assumptions, if the effect and model assumptions were correct. The 90% column uses a higher target chance of detection and therefore requires more participants per arm. For any fixed power target, planning for a smaller effect requires more participants, because a smaller difference is harder to distinguish from random variation.

These are planning illustrations based on the observed effect, not the trial’s original sample-size calculation. The original design assumptions and sample-size justification are not reported in the registry record. The figures are not observed power: they do not measure the probability that this completed trial detected an effect, and they should not be used to reinterpret the trial’s results after the fact. They describe hypothetical planning under the stated assumptions, rather than the number enrolled or analyzed in this study.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.410; pooled standard deviation σ = 2.578.
2. n = 2 × (1.96 + 0.842)² × 2.578² / -0.410² = 620.5, rounded up to 621 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 <- -0.41                      # observed difference in means
sigma <- 2.57768664136133                     # 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(2348203)
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 = 621 (80% power), 831 (90% power)
 75% of observed effect: n per arm = 1,104 (80% power), 1,477 (90% power)
 50% of observed effect: n per arm = 2,482 (80% power), 3,323 (90% power)
power.t.test: 621.4 
Simulated power at n = 621 per arm: 0.796 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry identifies one primary outcome and lists ten secondary outcomes. The secondary list spans multiple gene-expression signatures, urinary biomarkers, adverse events, a gender-related question, and metabolomic profiling. Testing multiple outcomes can increase the chance that at least one result appears unusual by chance. Statistical plans sometimes address this through a prespecified testing hierarchy or multiplicity adjustment, but such a plan is not reported in the registry record.

No reported analyses are listed for the primary or secondary outcomes. The posted comparisons are unadjusted recalculations from summary statistics. No adjusted p-values, confidence intervals accounting for multiple testing, or testing hierarchy are reported. Accordingly, individual secondary results should not be read as if they were protected against the interpretive risks of multiple comparisons. The registry does not report whether multiplicity was addressed in an analysis outside the posted record.

Missingness and analysis-population details are also limited. For the primary gene-expression outcome, the registry explicitly says the analyzed number differs from the Participant Flow Module because analysis was restricted to samples meeting quality metrics. It does not give the participant-flow counts in the information available for this outcome, the characteristics of samples that failed quality checks, or a comparison of included and excluded participants. Reasons for missingness on other outcomes and the statistical handling of missing values are not reported in the registry record.

The record therefore does not establish whether each outcome analysis followed an intention-to-treat population, a per-protocol population, or another prespecified analysis population. Nor does it report imputation methods, sensitivity analyses, or adjustments for baseline measurements. These absences do not prove that such procedures were not used; they mean their use and implications cannot be assessed from the registry record. Interpretation should remain specific to the participants and samples contributing to each posted outcome.

15. 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 registry reports serious adverse events for 31 participants at risk in Arm I and 32 at risk in Arm II. The number affected by a serious adverse event was 0 in each arm, and deaths were 0 in each arm. No serious-event terms are listed. These are counts in the registry record for the stated groups; they do not establish that the risk of a rare event is absent.

For other adverse events, the record lists 25 participants affected in Arm I, among 31 at risk, and 17 affected in Arm II, among 32 at risk. The registry’s outcome label refers to possibly, probably, or definitely related adverse events, but the posted group figures do not provide event types, severity breakdowns, or detailed attribution for each participant. Those details are not reported in the registry record.

Safety counts should be read in light of the recorded risk groups and the trial’s size and duration. The registry lists a 12-week intervention period. Zero recorded serious events during that period is a description of the observed record, not proof that serious events cannot occur. The counts alone also do not establish a causal difference between treatment and placebo.

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

The principal result concerns a change in a nasal gene-expression score among current smokers whose samples met quality requirements. The observed mean difference between the aspirin-plus-zileuton arm and the double-placebo arm was -0.41, with a confidence interval from -2.03 to 1.21 and an unadjusted p-value of 0.62. The interval includes values in both directions, and the registry does not define a threshold for a meaningful score change.

The endpoint is a biomarker, not a direct measure of lung-cancer incidence, cancer prevention, symptoms, or survival. The trial’s stated rationale connects the score to smoking-related gene expression and tobacco-related carcinogenesis, but the posted results do not show whether the score predicts a clinical outcome. No conclusion about preventing lung cancer can be drawn from this biomarker comparison alone.

The study was randomized, which supports a comparative design, but the information in the registry is not sufficient to reconstruct every feature of the analysis. The identity of the masked party, original sample-size assumptions, detailed statistical plan, missing-data procedures, and multiplicity strategy are not reported in the registry record. In addition, the primary gene-expression analysis was restricted to samples meeting quality metrics, and the analyzed counts were 19 and 21.

The results do not establish that the intervention changed the score in a particular direction, nor do they establish equivalence between the arms. A broad interval that crosses zero can reflect uncertainty about the direction and magnitude; it is not evidence that the arms are identical. Likewise, the unadjusted p-value does not state the probability that the treatment has no effect. The record supports a cautious description of the measured biomarker comparison, not a clinical recommendation or a claim about cancer prevention.

17. Why This Trial Matters Statistically

This trial illustrates the distinction between a biological endpoint and a patient-important clinical outcome. A nasal gene-expression score can be studied over a defined intervention period, but its statistical behavior and clinical meaning are not interchangeable with cancer incidence. The registry describes a rationale for the score and its direction, while leaving its relationship to later clinical outcomes unspecified.

It also demonstrates why the analyzed population matters. Enrollment was 63, while the primary gene-expression comparison included 19 and 21 participants in the two arms. The registry attributes the difference to quality requirements for tissue samples. That explanation is important, but without fuller information about excluded samples and participant flow, readers cannot assess whether the analyzed subset differs systematically from the enrolled population.

The primary estimate is accompanied by an interval spanning negative and positive values. This makes precision central to interpretation: a point estimate alone would conceal the range of uncertainty. The registry’s absence of a reported meaningful-change threshold also shows why statistical estimation and substantive interpretation are separate tasks. A numerical difference may be estimated without a documented basis for deciding whether its size matters biologically.

Finally, the record lists many secondary outcomes but no reported analyses or multiplicity plan. That combination highlights the value of clear prespecification and transparent reporting. When several biomarkers are examined, readers need to know how outcomes were selected, how analyses were conducted, and whether multiplicity was addressed. The available record supports cautious, outcome-specific interpretation rather than a single broad conclusion from the biomarker set.

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 main trial-specific limitation is that the primary endpoint analysis was restricted to samples meeting gene-expression quality metrics. The registry reports analysis counts of 19 in Arm I and 21 in Arm II and notes that these differ from Participant Flow Module counts. It does not provide the full flow information or describe the excluded samples, so the representativeness of the analyzed samples cannot be evaluated from the registry record.

The primary endpoint is a nasal tissue biomarker rather than a clinical outcome. The registry does not report whether changes in the score predict lung-cancer incidence or another health outcome, and it gives no minimum meaningful difference. The treatment period was 12 weeks; longer-term biomarker persistence and clinical outcomes are not reported in the record.

The record does not report the identity of the party masked, the original sample-size justification, the statistical analysis plan, the inferential method used by the investigators, missing-data procedures, or a multiplicity strategy. The posted comparisons are unadjusted recalculations from summary statistics, and no reported analyses are listed. As a result, consistency between the displayed estimates and a prespecified sponsor analysis cannot be assessed.

Several outcomes use different analyzed sample counts and measurement scales. The registry does not provide enough detail to determine why all measurements are unavailable for every participant or whether missingness could affect comparisons. The recorded serious adverse-event counts are also limited to the reported period and group totals; detailed event descriptions and broader safety follow-up are not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Aspirin and Zileuton and Biomarker Expression in Nasal Tissue of Current Smokers — NCT02348203.
• Registry record last updated 2022-06-02; status last verified 2022-06.
• Results first posted 2020-03-23.
• 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

NCT02348203 is a completed randomized, single-masked, parallel-group phase II study sponsored by the National Cancer Institute (NCI). The registry lists enrollment of 63 and the condition tobacco use disorder. The study compared aspirin plus zileuton with double placebo over 12 weeks in current smokers.

The primary outcome was change from baseline to 12 weeks in a smoking-related gene-expression signature score in nasal epithelium. The posted mean difference was -0.41, with a confidence interval from -2.03 to 1.21 and an unadjusted p-value of 0.62. The analysis included 19 participants in the combination arm and 21 in the placebo arm, with sample inclusion restricted by gene-expression quality metrics.

The registry also lists secondary biomarker and safety outcomes. It does not report the original sample-size justification, detailed statistical analysis plan, multiplicity handling, or full missing-data procedures. The findings therefore describe posted biomarker and safety measurements rather than clinical cancer outcomes.