Informing Tobacco Treatment Guidelines for African American Non-Daily Smokers: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Informing Tobacco Treatment Guidelines for African American Non-Daily Smokers (NCT02244918), a randomized phase 4 study. The primary outcome is Smoking Abstinence.

2. Clinical Question

In plain terms, the trial compared a counseling program with the same counseling program accompanied by a choice of nicotine replacement therapy. Random allocation means the study was designed to assign participants to groups by chance; it does not, by itself, remove uncertainty from the results or show that the groups were otherwise identical. The record identifies the study population broadly, but details such as eligibility thresholds and baseline smoking patterns are not reported in the registry record.

The central statistical question is about a difference between assigned groups at a specified follow-up point, rather than a comparison of each group with its own starting value. The primary outcome is a count of participants meeting the abstinence definition. The posted comparison therefore concerns the proportion meeting that definition in each group, while the plotted and tabulated counts give the underlying event totals and group sizes.

The question is deliberately limited to the listed outcome and time point. The record also names other outcomes, but their presence does not make them equivalent to the primary endpoint or give them the same role in the analysis. Results should be interpreted as evidence about this particular assignment comparison, endpoint definition, and follow-up, not as a conclusion about every form of smoking cessation support.

3. Trial Design

The registry describes a completed Phase 4, randomized, parallel-group study with no masking. Enrollment was 278. The record lists the University of Kansas Medical Center as sponsor and gives a start of 2015-05 and primary completion of 2017-11-01. These administrative details describe the registered study; they do not add information about how participants were recruited, how allocation was generated or concealed, or how follow-up was conducted. Those details are not reported in the registry record.

The two groups shared a counseling program described as occurring over 12 weeks and comprising 5 total sessions. The counseling-plus-NRT group was also assigned 12 weeks of a nicotine replacement therapy of the participant’s choice, with patch, gum, and lozenge named as examples. The other group was assigned counseling without the listed NRT component. The record does not describe adherence to counseling or NRT, the specific products or doses selected, or whether participants changed treatment during follow-up.

The primary outcome was smoking abstinence at Week 12. The registry defines it as biochemically confirmed 30-day point prevalence abstinence, assessed using urine anabasine and anatabine and a recommended cut-off of 2 ng/ml. The outcome table reports 185 participants in the counseling-plus-NRT group and 93 in the counseling group. These are the group sizes shown for the primary outcome; the record does not explain whether they represent all randomized participants or only participants with outcome data.

The record also includes smoking abstinence at Week 26 and lists secondary outcome topics involving urinary cotinine, urinary NNAL, total days abstinent, and cigarettes used. The details and results for all listed outcomes are not present in the posted analyses. The exact follow-up procedures, analysis population, handling of missing outcomes, and original sample-size rationale are not reported in the registry record. This means the design can be summarized from the assigned groups and endpoint description, but some important implementation and analysis details remain unknown.

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 Smoking Abstinence, measured over Week 12.

The primary endpoint is the count of participants with biochemically confirmed 30-day point prevalence abstinence at Week 12. “Point prevalence” here refers to abstinence over the specified period before assessment, rather than continuous abstinence throughout the study. The registry describes urine anabasine and anatabine as the biochemical measures and gives a recommended cut-off of 2 ng/ml to differentiate smokers from non-smokers.

The endpoint is recorded as participants meeting the definition, so the displayed group results are event counts, not average changes in a continuous measurement. The comparison translates those counts and group sizes into a contrast between groups. The specific abstinence definition matters: a result for this Week 12 measure does not automatically describe abstinence at other time points or under a different definition.

General statistical context: biochemical confirmation can complement self-reported smoking information by bringing a laboratory measure into the outcome definition. It does not remove every possible source of bias or uncertainty, and interpretation still depends on how samples were collected, how results were handled, and what happened when data were unavailable. Those operational details are not reported in the registry record.

The record names anabasine and anatabine and the cut-off, but does not provide a fuller account of the assay procedures or explain how discordant or missing measurements were classified. Thus, the endpoint’s stated definition is clear at a high level, while some details needed to reproduce its implementation are not reported in the registry record.

7. Results Posted in the Registry

• Counseling: 8.6% (8/93) versus 11.4% (21/185) on control; risk difference -2.7 percentage points (95% CI -10.1 to 4.6), risk ratio 0.76 (0.35–1.65); unadjusted two-proportion z-test p = 0.479.

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.

Smoking Abstinence

• 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:
  • Counseling: 6.5% (6/93) versus 7.0% (13/185) on control; risk difference -0.6 percentage points (95% CI -6.8 to 5.6), risk ratio 0.92 (0.36–2.34); unadjusted two-proportion z-test p = 0.858.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Counseling and the control. The interval gives the range of effects that remain compatible with the data.

The record lists secondary topics including smoking abstinence, urinary cotinine concentration, urinary NNAL concentration, total days abstinent, and cigarettes used. A Week 26 smoking-abstinence result is also posted. However, the record does not provide detailed results for every listed secondary topic, and it lists no reported secondary analysis models. The presence of an outcome name in the registry should not be mistaken for a complete result or a fully described analysis.

Across the available smoking-abstinence information, the Week 12 primary comparison and the later Week 26 comparison do not provide a precise basis for declaring a group difference. The later follow-up is related to the primary question because it concerns abstinence, but it is a separate time point and should not be merged with or substituted for the Week 12 endpoint. Different follow-up times can describe different aspects of the outcome and may be affected by different amounts of missing information or measurement uncertainty.

General statistical context: secondary outcomes can broaden a trial’s description, but they commonly involve multiple comparisons. When many outcomes or time points are examined, the chance of finding an apparently unusual result by chance can increase if each is interpreted as a separate confirmatory test. Unadjusted secondary results therefore carry less weight than a single prespecified primary comparison, unless a clear analysis plan and multiplicity approach justify a stronger interpretation. No multiplicity procedure is reported in the registry record.

The secondary outcomes can also differ in measurement scale and meaning. A laboratory concentration, a count of abstinent days, and a count of cigarettes are not interchangeable indicators. Their interpretation depends on definitions, timing, missing-data handling, and analysis methods, several of which are not reported. The available secondary information should therefore be treated as supplementary context rather than a set of independent confirmations of the primary result.

In short, the secondary section is useful for showing what else the study intended to assess and which later abstinence result is posted. It does not support claims about the unreported outcomes, nor does it resolve the uncertainty in the primary Week 12 comparison.

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

• Smoking Abstinence
• Concentration of Urinary Cotinine
• Urinary Concentration of NNAL (4-(Methyl Nitrosamine)-1-(3-pyridyl)-1-butanol)
• Total Days Abstinent
• Cigarettes Used

9. Statistical Interpretation

10. Statistical Methods Explained

What is being compared?

The primary outcome is binary at the participant level: a participant either meets the recorded abstinence definition at Week 12 or does not. The arm summaries therefore show counts of participants with an event, alongside the numbers in each group. A comparison of event proportions is appropriate to this kind of outcome, but the exact analysis method used by the trial investigators is not reported in the registry record.

The posted comparison gives a risk difference, a risk ratio, and an odds ratio. General statistical context: the risk difference expresses an absolute contrast between the event proportions; the risk ratio expresses one proportion relative to another; and the odds ratio compares event odds. They summarize the same underlying comparison using different scales. The choice of scale affects how the size of an estimate is described, not the observed group counts. The risk difference is especially direct for understanding an absolute change in event probability, while relative measures can be useful for other questions but may be less intuitive when event rates are not large or when translated into practical expectations.

How should the comparison be read?

The primary comparison is oriented as counseling relative to counseling plus NRT. Its risk difference is -0.028. The sign indicates the direction on that scale, while the confidence interval gives a range of values compatible with the data and the model used for the interval. The interval crosses zero, the value that corresponds to no absolute difference. The unadjusted p-value is 0.479. General statistical context: a p-value summarizes how unusual data at least as incompatible with a specified null hypothesis would be if that null model held; it is not the probability that the null hypothesis is true, and it does not measure the probability that the observed result will be reproduced.

The record does not list the investigators’ statistical model, covariate adjustments, or test procedure. It also lists no reported secondary analysis models. The estimates can be described as unadjusted comparisons from the posted outcome summaries, but they should not be attributed to a particular regression model or analysis strategy that is not documented. The registry record reports no discrepancy between the comparison and the posted arm results.

Why does random allocation matter?

General statistical context: random allocation is intended to make assigned groups comparable, on average, with respect to measured and unmeasured characteristics before treatment assignment. It supports interpretation of group differences as effects of assignment when the trial is properly conducted and analyzed. Randomization does not guarantee identical baseline groups in a particular study, ensure adherence, prevent loss to follow-up, or eliminate bias from outcome measurement and analysis decisions. Baseline characteristics and allocation procedures are not reported, so those aspects cannot be assessed from this record alone.

The study is listed as unmasked. That means masking is not recorded for the trial, but the registry does not describe who knew group assignments or how that may have influenced counseling, reporting, laboratory procedures, or follow-up. Biochemical measurement is part of the abstinence definition, but it does not on its own answer all questions about bias or missing outcomes.

What do the intervals and p-value contribute?

General statistical context: a confidence interval communicates uncertainty around an estimate under the assumptions of its method. It is not a guarantee that the true effect lies in the interval, nor does it identify a single most likely value. The interval should be interpreted in relation to the endpoint, comparison scale, and precision of the data. Here, the risk-difference interval includes both negative and positive values, leaving the direction of the underlying group contrast unresolved by this estimate.

The p-value and confidence interval are related summaries, but neither supplies information about clinical importance by itself. A small p-value would not establish that an effect is important, and a larger p-value does not establish equivalence. To assess whether a range of effects would matter, readers would need a prespecified threshold for meaningful difference, which is not reported in the registry record.

What are the planning illustrations?

The sample-size section presents planning illustrations based on the observed effect, with rows considering 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. The displayed sample sizes are planning quantities, not the number enrolled or a reconstruction of the original trial design. The stated calculation assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The original design assumptions are not reported in the registry record.

General statistical context: power is the probability that a specified analysis will meet its statistical decision criterion under a specified true effect and model. The 80% and 90% columns show illustrative participants per arm for those target power levels, under the listed assumptions. Smaller effects generally require more participants to distinguish them from random variation with the same target power. Because the illustrations use an observed effect as their starting point, they are sensitive to uncertainty in that estimate and should not be treated as a forecast of what a future study will find.

For the Week 12 endpoint, the table gives participants per arm; the same is true for the Week 26 binary endpoint. No time-to-event outcome is being presented in these tables. The calculation description specifies a normal approximation and equal allocation, which are planning assumptions rather than confirmed features of the trial’s original design. The record does not report the original sample-size justification, any planned interim analyses, or a prespecified statistical analysis plan.

What remains undocumented?

The record does not report how missing outcome data were handled, which analysis population was used, whether all randomized participants were included, or whether analyses followed assigned group regardless of treatment received. It also does not report a multiplicity strategy for the primary and secondary outcomes. These omissions matter because analysis choices can affect how estimates and uncertainty should be interpreted. They cannot be filled in from the group counts alone.

General statistical context: a transparent analysis description normally identifies the endpoint definition, estimand or comparison of interest, analysis population, model, handling of missingness, and approach to multiple testing. This record supports a careful account of the posted counts and unadjusted comparisons, but not a reconstruction of every analytic decision made during the trial.

11. Confidence Intervals and Precision

The primary risk-difference estimate is -0.028, with a 95% confidence interval from -0.101 to 0.046. The interval extends across zero, so the data are compatible with a negative difference, no difference, or a positive difference on this scale. The estimate’s direction is therefore not established precisely. The risk-ratio interval, 0.349 to 1.645, and the odds-ratio interval, 0.312 to 1.729, likewise include their respective no-difference values.

General statistical context: a confidence interval is a way to summarize sampling uncertainty under a specified statistical method. A 95% interval does not mean that there is a 95% probability that this particular interval contains the true value. Rather, the method is constructed to cover the true value at the stated rate over repeated studies when its assumptions hold. The interval does not account automatically for every source of uncertainty, such as outcome misclassification, missing data, or an unreported analysis choice.

The group counts and sizes help explain why precision matters. The primary event counts are limited, and the interval permits a broad range of risk differences. The point estimate should not be treated as a stable or exact measure of the difference that would occur in another study. Conversely, the interval’s inclusion of zero is not evidence that there is no effect. It says that the available estimate does not distinguish the direction and size with high precision.

The registry provides no prespecified margin for equivalence or non-inferiority. General statistical context: demonstrating equivalence requires a design and analysis built around an acceptable range of differences, not merely a nonsignificant test of a zero difference. Since no such margin is reported, the confidence interval cannot be used to claim that the groups are equivalent. It is best read as a measure of uncertainty about the observed comparison, within the limits of the posted analysis.

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 table gives planning illustrations for the posted binary comparisons. The figures are participants per arm, not total events. This distinction matters: the values describe how many participants the illustration indicates would be needed in each group under its assumptions; they are not observed enrollment or observed event counts.

The calculation assumptions listed in the record are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The target is to detect the stated fraction of the observed effect. Rows show planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For each row, the 80% power column gives the illustrative participants per arm for a study designed to have an 80% chance of meeting its statistical criterion if that assumed effect were true. The 90% power column gives the corresponding figure for a 90% target.

Smaller effects are harder to distinguish from random variation, so the table requires more participants per arm when the assumed effect is smaller. The Week 12 and Week 26 entries are based on their respective observed comparisons; their planning figures should not be confused with the actual group sizes in the outcome tables. The trial’s original sample-size justification and design assumptions are not reported in the registry record. These illustrations are not observed power: they are planning calculations based on the observed effect and the stated assumptions, not a measure of what the completed trial achieved.

General statistical context: planning figures depend on the assumed effect, event frequency, allocation, significance level, analysis method, and target power. A changed assumption can change the required sample size. In particular, an effect estimated imprecisely in a small study can produce an unstable planning illustration. The values are therefore best used to understand how assumptions relate to planned scale, not as a standalone recommendation for a future 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.114; treatment proportion p₁ = 0.086; average p̄ = 0.100.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4238 = 0.8307.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4234 = 0.3563.
4. n = (0.8307 + 0.3563)² / (-0.0275)² = 1,864.2, rounded up to 1,865 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 <- 0.113513513513514                          # control proportion
p1 <- 0.0860215053763441                          # 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(2244918)
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 = 1,865 (80% power), 2,496 (90% power)
 75% of observed effect: n per arm = 3,417 (80% power), 4,573 (90% power)
 50% of observed effect: n per arm = 7,914 (80% power), 10,594 (90% power)
power.prop.test: 1864.2 
Simulated power at n = 1,865 per arm: 0.797 (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 names a primary outcome and several secondary outcome topics, and it includes a secondary smoking-abstinence result at Week 26. It does not report a strategy for controlling multiplicity, such as a hierarchy of tests, an adjustment method, or a distinction between confirmatory and exploratory secondary analyses. The number and exact structure of analyses planned by investigators are therefore not reported in the registry record.

General statistical context: when several outcomes, time points, or statistical contrasts are examined, each additional test creates another opportunity for a result to appear noteworthy by chance. A multiplicity plan helps specify which comparisons carry confirmatory weight and how uncertainty should be interpreted across them. Without a reported plan, secondary findings are appropriately read as exploratory or descriptive, rather than as independent proof of a result. This does not mean that the outcomes are uninformative; it means that the strength of claims should reflect the lack of a documented testing framework.

The record also does not explain how missing outcomes were handled. It does not state whether participants without a Week 12 urine measure were counted as smoking, excluded, imputed, or addressed in another way. The same uncertainty applies to the secondary follow-up. The displayed arm sizes and counts do not establish which participants were randomized, which attended follow-up, or which contributed to the analysis.

The analysis population is not described. In particular, the record does not say whether the comparison followed an intention-to-treat principle, included only participants with available endpoint data, or used another population definition. It also does not describe adherence-based analyses. Those distinctions can matter because analyses that include different participants answer different questions and may be affected differently by missingness or treatment discontinuation.

General statistical context: missingness can affect estimates when the likelihood of observing an outcome is related to participant characteristics or outcome status. The direction and size of any such effect cannot be inferred without information about follow-up and missingness. The registry record also does not report an original statistical analysis plan or interim-analysis procedures. These gaps limit assessment of whether the posted comparisons follow a prespecified approach and how fully they represent all assigned participants.

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 non-serious adverse event terms

The serious adverse event section reports 0 participants with serious adverse events in the counseling-plus-NRT group and 0 in the counseling group. It also reports 0 deaths in each group. The listed numbers at risk are 185 and 93, respectively. The registry provides no serious adverse event terms, consistent with the empty list of serious terms.

The record also reports other adverse events affecting 161 participants in the counseling-plus-NRT group and 83 participants in the counseling group. These are separate from the serious adverse event figures. The summary does not provide event descriptions, severity details, timing, relatedness assessments, or a breakdown by type. The figures should therefore be read as reported counts, not as a comparison of specific harms or an assessment of causality.

General statistical context: observing zero serious events in the posted groups does not prove that no serious event could occur, and it does not establish that the groups have equal safety profiles. Rare events can be difficult to characterize in a trial of limited size, and the interpretation depends on the duration and completeness of safety follow-up. Those details are not reported in the registry record. The posted safety information is a summary of recorded counts, not a comprehensive account of all possible safety outcomes.

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

The posted primary result describes biochemically confirmed 30-day point prevalence abstinence at Week 12 among participants assigned to counseling plus NRT and participants assigned to counseling. It gives the observed event counts, an unadjusted comparison, and uncertainty intervals. The estimate does not precisely establish the direction or size of a difference between the assigned groups. The result should therefore be presented as inconclusive about a group difference, rather than as evidence that the groups are identical.

The comparison is between two counseling-based assignments, one with an added NRT component and one without the listed NRT component. It does not answer what would happen with NRT alone, with no counseling, with a different counseling program, or with a different NRT schedule. The endpoint is specific to its stated definition and Week 12 timing; it does not describe continuous abstinence or all possible measures of smoking behavior.

General statistical context: an estimate and its confidence interval describe uncertainty about a population comparison under assumptions. They do not guarantee the same result in another population or setting. Applying this result beyond the people and intervention arrangements represented in the study requires information about eligibility, participant characteristics, delivery, adherence, and follow-up. Many of those details are not reported in the registry record.

The secondary smoking-abstinence result is at a different follow-up point, and other secondary outcomes are named without detailed posted analyses. Those data do not remove the uncertainty in the primary estimate. The registry also does not report the original sample-size rationale, missing-data approach, analysis population, or multiplicity plan. Readers should not infer these methods from the numerical results alone.

This account is statistical interpretation, not medical advice. It does not establish whether an individual should use a particular treatment. The appropriate conclusion is limited to what the posted record shows: a randomized, parallel-group comparison, a defined Week 12 abstinence outcome, observed counts, and an imprecise unadjusted contrast whose interval includes no difference.

17. Why This Trial Matters Statistically

This trial is statistically informative because it places a common design question in a population and treatment context explicitly described in the registry: counseling alone compared with counseling plus a choice of nicotine replacement therapy for African American non-daily smokers. Its randomized parallel-group structure gives a framework for comparing assigned strategies, and the registry specifies a biochemical component to the primary abstinence definition.

It also illustrates why an observed point estimate is not enough. The Week 12 comparison has a direction and a numerical size, but its confidence interval spans values on both sides of no difference. Reporting the interval alongside the counts shows that the result is uncertain, rather than allowing the point estimate or a single p-value to dominate interpretation. The alternative risk-difference, risk-ratio, and odds-ratio summaries further demonstrate that an effect can be expressed on several scales, each of which requires context.

The record is also a useful example of the boundary between a posted result and a fully documented analysis. A study can have a named primary outcome, group counts, and a comparison while leaving the analysis population, missing-data handling, multiplicity approach, and original planning rationale unreported. Those omissions matter when judging how complete and reproducible the statistical account is.

Finally, the planning illustrations show how assumed effect size and target power relate to required participants per arm. They are not a measure of the completed study’s power and do not replace the missing original design rationale. Taken together, the trial highlights three statistical habits: distinguish observed data from planning scenarios, give uncertainty as much attention as the point estimate, and keep conclusions within the scope of the registered outcome and documented methods.

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 limitations are specific to what is documented for this trial. The registry describes the target population broadly as African American non-daily smokers, but detailed eligibility criteria and enrolled participant characteristics are not reported. Without those details, it is difficult to judge how closely the participants represented the broader population described by the title or how widely the result may apply.

The primary outcome is defined, but the record does not provide detailed assay procedures, sample collection methods, or rules for handling missing or indeterminate urine results. It also does not explain whether all randomized participants contributed to the listed outcome counts. This limits assessment of the completeness of endpoint ascertainment and the consequences of any missing data.

The registry identifies the study as unmasked but does not describe who knew the assignments or how the absence of masking was managed. It does not report allocation concealment, baseline characteristics, adherence, treatment changes, or counseling attendance. These details would help readers assess implementation and possible differences in care or follow-up between groups.

The exact statistical analysis plan is not reported. In particular, the record does not specify the analysis population, adjustment strategy, missing-data method, multiplicity procedure, or interim-analysis approach. It also does not report the original sample-size justification. Planning figures elsewhere on the page are illustrations based on observed effects and stated calculation assumptions, not a substitute for the trial’s own rationale.

Finally, the registry lists several secondary outcome topics, but detailed results are not posted for all of them. The Week 26 abstinence result is a separate time point and does not answer every question raised by those outcomes. These documentation limits do not invalidate the posted counts, but they constrain how completely the result can be assessed or reproduced.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Informing Tobacco Treatment Guidelines for African American Non-Daily Smokers — NCT02244918.
• Registry record last updated 2019-01-09; status last verified 2018-12.
• Results first posted 2019-01-09.
• 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

The record describes a completed Phase 4 randomized, parallel-group trial with no masking and enrollment of 278. It compares smoking cessation counseling over 12 weeks, with 5 sessions, against the same counseling plus 12 weeks of a participant-chosen over-the-counter nicotine replacement therapy. The listed examples are the patch, gum, and lozenge.

The primary outcome is biochemically confirmed 30-day point prevalence abstinence at Week 12, assessed using urine anabasine and anatabine with a recommended cut-off of 2 ng/ml. The posted unadjusted comparison has a risk difference of -0.028 and a 95% confidence interval from -0.101 to 0.046, which includes zero. A separate Week 26 abstinence result is also posted.

The record reports no serious adverse events or deaths in either group, and includes counts for other adverse events. It does not report the original sample-size rationale, analysis population, missing-data handling, multiplicity strategy, or a detailed statistical analysis plan. Interpretation should remain limited to the outcomes and methods actually documented.