Advancing Tobacco Use Treatment for African American Smokers: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Advancing Tobacco Use Treatment for African American Smokers (NCT02360631), a randomized phase 4 study. The primary outcome is Number of Participants With Smoking Abstinence at Month 6.

2. Clinical Question

This question concerns abstinence status at a defined visit, rather than whether participants remained continuously abstinent throughout the study. The registry also lists smoking-abstinence outcomes at week 12 and week 26. Numerical results are posted for week 12, while a numerical week 26 result is not reported in the registry record.

3. Trial Design

The registry describes a phase 4, randomized, double-masked, parallel-group trial of Chantix (varenicline) and placebo. The listed enrollment was 500. The arm counts in the posted primary outcome are 300 participants in the Chantix group and 200 in the placebo group. Randomization indicates assignment to study groups by chance; double masking means the record identifies the trial as masked for two groups, but which specific people were masked is not reported in the registry record.

Participants in the Chantix arm were to receive 1mg pills twice a day for 12 weeks. Participants in the placebo arm were to receive placebo pills on the same twice-a-day schedule for 12 weeks. The study started on 2015-07-29, reached primary completion on 2018-07-12, and is listed as completed. The sponsor is Lisa Sanderson Cox, PhD.

The primary outcome was the number of participants with smoking abstinence at month 6. Two secondary outcomes are listed: smoking abstinence at week 12 and week 26. The registry record includes numerical results for the primary outcome and week 12 outcome, but a numerical result for week 26 is not reported in the registry record. The record lists three outcome measures overall, but does not provide further detail about the remaining measure in the material described by its outcome results.

Details such as eligibility criteria, the planned allocation ratio, concealment procedures, participant flow, and the original sample-size rationale are not reported in the registry record. The posted arm counts describe participants included in the outcome summaries; they should not be treated as a complete account of screening, enrollment, or follow-up.

4. Participant Flow and Accounting

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

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Smoking Abstinence at Month 6, measured over Month 6.

The primary endpoint counts participants who met the study’s definition of smoking abstinence at month 6. Specifically, abstinence was defined as biochemically verified 7-day point-prevalence abstinence, meaning that a participant reported smoking zero cigarettes at the month 6 visit and the status was biochemically verified. The posted result is a count of participants in each arm, rather than a continuous measure of smoking behavior.

A point-prevalence endpoint describes status over a specified period around an assessment visit. It is distinct from continuous abstinence, which would require a participant to remain abstinent throughout a stated interval. The registry record does not define the endpoint as continuous abstinence. The week 12 and week 26 secondary outcomes are also framed as counts of participants with smoking abstinence at their respective assessments.

Biochemical verification can complement self-report by adding an objective assessment to the classification of abstinence. In general, a defined assessment window and a stated verification method help make the outcome interpretable. They do not, by themselves, explain how missing visits or unverifiable results were classified; those rules are not reported in the registry record.

7. Results Posted in the Registry

• Chantix (Varenicline): 15.7% (47/300) versus 6.5% (13/200) on control; risk difference 9.2 percentage points (95% CI 3.8 to 14.5), risk ratio 2.41 (1.34–4.34); unadjusted two-proportion z-test p = 0.002.

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.

Number of Participants With Smoking Abstinence at Week 12

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Chantix (Varenicline): 18.7% (56/300) versus 7.0% (14/200) on control; risk difference 11.7 percentage points (95% CI 6.0 to 17.3), risk ratio 2.67 (1.53–4.66); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Chantix (Varenicline) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcome results with numerical comparisons cover smoking abstinence at week 12. The registry also lists smoking abstinence at week 26, but a numerical result for that outcome is not reported in the registry record. Across the numerical outcomes available at week 12 and month 6, the reported comparisons point in the same direction. The earlier result is relevant context for the primary month 6 finding, but it is not a substitute for the primary endpoint or an independent replication.

Repeated measurements within the same trial are related: they involve the same study groups and may include many of the same participants. Consequently, agreement across time points can provide context about the pattern of results, but the comparisons should not be treated as wholly independent evidence. The endpoints also describe abstinence at particular assessment times; they do not establish continuous abstinence between visits.

The week 12 comparison has an unadjusted p-value. When several outcomes or time points are tested, the chance of obtaining at least one apparently notable result can increase if no multiplicity strategy is used. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting the secondary outcomes. Therefore, unadjusted secondary findings generally carry less confirmatory weight than a prespecified primary result with a documented analysis plan. The absence of a posted numerical week 26 result also means that the listed outcome cannot contribute a numerical comparison to this reading.

These considerations are about the evidential role of secondary outcomes, not a claim that the results are invalid. They indicate why secondary findings are most useful as supporting context and why interpretation depends on the analysis plan, outcome reporting, and handling of repeated tests. Those details are not reported in the registry record.

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

• Number of Participants With Smoking Abstinence at Week 12
• Number of Participants With Smoking Abstinence at Week 26

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary at the participant level: each participant is classified according to whether they met the stated abstinence definition at month 6. The registry presents counts of participants meeting that definition in each arm and a comparison between the arms. The outcome is therefore not a mean score or a rate of change. The interpretation should stay tied to the stated assessment and classification.

What does a risk difference describe?

In general, a risk difference compares the probability of an event between two groups by subtracting one group’s probability from the other’s. It expresses the contrast on an absolute scale. The posted primary risk-difference estimate and its interval describe the estimated group separation and uncertainty around it. A value in the direction of the intervention group indicates more observed abstinence in that group than in the comparator, given the comparison’s orientation. This estimate does not explain why the groups differed.

How do relative measures differ?

In general, a relative risk compares the event probability in one group with the event probability in another. An odds ratio compares event odds instead of event probabilities. Both are relative measures, so their interpretation differs from an absolute risk difference. Relative measures can help describe the scale of a contrast, but they do not replace the actual participant counts. For this trial, the registry posts a relative-risk estimate and an odds-ratio estimate alongside the risk-difference comparison. Those estimates summarize the same endpoint contrast using different scales.

What does the p-value tell a reader?

In general, a p-value is calculated under a specified null model and analysis procedure. It measures how unusual data at least as incompatible with that null model as the observed data would be, assuming the model and procedure apply. It is not the probability that the null hypothesis is true, and it is not a measure of the size or clinical importance of an effect. The primary p-value is identified as unadjusted in the registry record. The analysis procedure behind it is not described in detail, so the p-value should be read as the posted unadjusted result rather than as a complete account of the statistical plan.

Why does the interval matter?

In general, a confidence interval gives a range of values compatible with the data and the interval’s method, under its assumptions. Its width reflects precision: a wider interval represents greater uncertainty about the estimated effect than a narrower interval would. An interval does not account automatically for every source of uncertainty. For example, it does not resolve bias from missing data, problems with outcome measurement, or departures from the assumptions used to construct it. The registry provides intervals for the posted comparisons, but does not report their construction method or confidence level in the record.

What does over-dispersion mean for this outcome?

In general, over-dispersion refers to observed variability exceeding what a particular statistical model expects. It is especially relevant to count models, where an incorrect assumption about variability can make standard errors and intervals too small. The posted primary outcome is a count of participants with an event in each arm, and the record does not report a dispersion estimate or an over-dispersion analysis. The outcome should not be described as having over-dispersion on the basis of these counts alone. The registry record also does not report a model specification, covariate adjustment, or a sensitivity analysis for the primary comparison.

These explanations describe general statistical concepts, not an assertion that every method was used in the trial. What is identifiable from the registry record is the endpoint definition, arm counts, posted comparison measures, intervals, and unadjusted p-value. The trial’s full statistical analysis plan and the rationale for each analysis are not reported in the registry record.

11. Confidence Intervals and Precision

Precision concerns how much uncertainty remains around an estimated contrast. The posted primary risk-difference interval runs from 0.038 to 0.145. The posted relative-risk estimate is 2.41, with an interval from 1.339 to 4.337; the odds-ratio estimate is 2.672, with an interval from 1.405 to 5.081. Each interval is tied to its own measure, so the limits should not be compared as if they were on one common scale.

In general, an interval describes a range of estimates compatible with the data and the method used to construct it. A narrower interval indicates greater precision than a wider interval on the same scale and under comparable methods. The record does not report the interval construction method or confidence level. The posted intervals therefore give useful information about uncertainty, but do not provide a complete account of the assumptions behind that uncertainty.

The counts and intervals should be considered together. Counts show the observed outcomes in the two arms; intervals convey how uncertain the estimated contrast is. Neither establishes that the observed estimate will be reproduced in a different setting. Precision also does not address potential systematic problems, such as missing outcome data or differences in how outcomes were measured. The registry record does not report missing-data rules or a sensitivity analysis that would show how such choices might affect the estimate.

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 sample-size figures are planning illustrations based on the observed effect, not the trial’s original design justification. They are expressed as participants per arm, not total participants or total events. The assumptions listed for the illustrations are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and a target effect set to a stated fraction of the observed effect. The trial’s own original sample-size assumptions and justification are not reported in the registry record.

For planning at 100% of the observed effect, the illustration gives 183 participants per arm for 80% power and 245 participants per arm for 90% power. For planning at 75% of the observed effect, it gives 297 participants per arm for 80% power and 396 participants per arm for 90% power. For planning at 50% of the observed effect, it gives 599 participants per arm for 80% power and 801 participants per arm for 90% power.

In general, power is the chance that a study design will detect an effect of a specified size using the stated test and assumptions. The 80% and 90% columns describe different target chances of detecting the planned effect if that effect and the planning assumptions hold. Smaller effects require more participants to achieve the same target power, which is why the illustrations increase as the assumed fraction of the observed effect gets smaller. These planning figures are not observed power.

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

Worked calculation for this trial

1. Control proportion p₀ = 0.065; treatment proportion p₁ = 0.157; average p̄ = 0.111.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4440 = 0.8701.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4392 = 0.3696.
4. n = (0.8701 + 0.3696)² / (0.0917)² = 182.9, rounded up to 183 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 <- 0.065                          # control proportion
p1 <- 0.156666666666667                          # 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(2360631)
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 = 183 (80% power), 245 (90% power)
 75% of observed effect: n per arm = 297 (80% power), 396 (90% power)
 50% of observed effect: n per arm = 599 (80% power), 801 (90% power)
power.prop.test: 182.9 
Simulated power at n = 183 per arm: 0.816 (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.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and secondary smoking-abstinence outcomes at week 12 and week 26. The record does not report how the outcomes were prioritized for statistical testing, whether a testing hierarchy was prespecified, or whether any adjustment for multiple comparisons was planned or applied. The primary p-value and the week 12 p-value are unadjusted. Without a reported multiplicity strategy, secondary p-values should be interpreted as exploratory or supportive rather than as a set of independently confirmatory tests.

Missing outcome data can affect both the number of participants analyzed and the estimated comparison. The registry record does not report how many participants lacked an evaluable month 6 or week 12 outcome, how missing abstinence assessments were classified, or whether any imputation or sensitivity analyses were used. The arm counts in the outcome summaries do not by themselves establish what happened to every enrolled participant or how missing outcomes were treated.

The analysis population is also not described in detail. The registry record does not state whether the results used an intention-to-treat population, a per-protocol population, or another defined analysis set. It does not report whether exclusions were made after randomization or how protocol deviations were handled. These omissions limit the ability to assess whether the posted comparisons preserve the planned randomized groups and how robust they are to alternative analysis choices.

These are reporting limitations: the absence of details in the registry record does not establish that a particular procedure was or was not used. The protocol and full analysis documentation would be needed to clarify multiplicity, missing data, and analysis-population decisions.

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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: renal failure (0.5%), bronchial inflammation (0.5%).

The serious adverse event summary lists 0 affected participants among 300 at risk in the Chantix group and 2 among 200 at risk in the placebo group. Deaths are listed as 0 in each group. The record also lists other adverse events for 276 of 300 participants in the Chantix group and 178 of 200 in the placebo group. These are posted counts and denominators, not adjusted comparisons.

The listed serious adverse-event terms include Renal Failure and Bronchial inflammation, each reported as 0.5%. The record does not assign those terms to a particular arm in the information. The adverse-event summary alone does not establish whether an event was caused by a study treatment, how events were defined or collected, or whether the groups differed in risk after accounting for follow-up and other factors. It should be read as a descriptive account of the registry’s reported events, not as a complete comparative safety analysis.

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

The posted results describe more participants meeting the month 6 abstinence definition in the Chantix arm than in the placebo arm, with a reported unadjusted comparison and intervals. They provide an estimate of the difference observed in these randomized groups under the outcome definition recorded in the registry. The interval communicates uncertainty about the estimated contrast, while the p-value addresses compatibility with a null model under the unadjusted analysis.

The result does not show that every participant assigned to Chantix achieved abstinence, nor does it mean that the observed group contrast will be the same in other populations or settings. The primary endpoint is status at the month 6 assessment, not continuous abstinence throughout follow-up. The registry record does not report sufficient detail about eligibility, participant characteristics, missing data, or analysis populations to determine how those factors might affect broader interpretation.

Statistical evidence and clinical meaning are not identical. A p-value does not measure the size or importance of an effect, and an interval does not resolve questions about study conduct or generalizability. The posted counts and comparisons are informative about the trial outcome as recorded, but they should not be extended beyond the endpoint, participants, and analysis information described in the registry record.

The record also lists a week 12 and a week 26 abstinence outcome. Numerical week 12 results are posted, while a numerical week 26 result is not reported in the registry record. The secondary outcomes can add context, but the record does not report how multiple comparisons were addressed. A complete judgment of the evidence would also require protocol and analysis-plan details that are not reported in the registry record.

17. Why This Trial Matters Statistically

This trial illustrates why a binary clinical endpoint should be read through both its definition and its comparison measure. “Abstinence” is not a self-explanatory outcome: the record specifies biochemical verification, a 7-day point-prevalence window, zero cigarettes, and a month 6 assessment. Those details clarify what was counted and distinguish the endpoint from continuous abstinence or a measure of smoking frequency.

The results also show why absolute and relative comparisons serve different purposes. A risk difference describes separation on an absolute scale, while relative risk and odds ratio express group contrasts differently. Alongside the participant counts and intervals, these measures help readers understand both the observed pattern and its uncertainty without collapsing distinct statistical questions into one number.

Finally, interpretation depends on more than a nominal p-value. The primary comparison is identified as unadjusted, while multiplicity procedures, missing-data handling, and analysis-population definitions are not reported in the registry record. The secondary outcomes and planning illustrations have different evidential roles: secondary results provide context, while sample-size illustrations describe hypothetical future planning under stated assumptions. Distinguishing those roles helps prevent descriptive results from being mistaken for a complete account of the trial’s analysis or design rationale.

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.

Several trial-specific details needed for a fuller assessment are not reported in the registry record. These include eligibility criteria, baseline characteristics, participant flow, the number with evaluable outcomes at each visit, and the rules for handling missing assessments. The posted arm counts do not clarify whether every enrolled participant contributed an outcome or how the analysis population was defined.

The primary endpoint is a point-prevalence assessment at month 6, so it describes abstinence status at that specified time rather than continuity of abstinence over the full follow-up period. Week 12 is also reported, but a numerical week 26 result is not reported in the registry record. The record does not describe adherence to the assigned pills, treatment discontinuation, or whether any outcome assessments were unavailable or unverifiable.

The registry provides unadjusted comparisons but does not report a detailed statistical analysis plan, covariate-adjusted estimates, a multiplicity procedure, or sensitivity analyses. The unequal posted arm counts, 300 and 200, are visible in the outcome summaries, but the reason for that pattern is not reported in the registry record. The record also does not provide the original sample-size justification, so the planning illustrations based on the observed effect should not be mistaken for the trial’s design rationale.

These gaps limit assessment of robustness and generalizability. They do not establish that a specific problem occurred; they mark information that is not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Advancing Tobacco Use Treatment for African American Smokers — NCT02360631.
• Registry record last updated 2020-07-15; status last verified 2020-07.
• Results first posted 2019-07-24.
• 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

NCT02360631 is a completed phase 4, randomized, double-masked, parallel-group trial titled “Advancing Tobacco Use Treatment for African American Smokers.” The listed enrollment is 500. Participants were assigned to Chantix (varenicline) or placebo, with both arms scheduled for twice-daily pills for 12 weeks. The primary outcome was biochemically verified 7-day point-prevalence smoking abstinence at month 6.

The posted primary counts are 47 of 300 in the Chantix group and 13 of 200 in the placebo group. The registry reports a risk-difference comparison with an unadjusted p-value of 0.002. Secondary abstinence outcomes are listed for week 12 and week 26; numerical results are posted for week 12, while a numerical week 26 result is not reported in the registry record. Details on missing data, multiplicity, analysis populations, and the trial’s original sample-size rationale are not reported in the registry record.