New Approaches to Smoking Cessation in Heavy Drinkers: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for New Approaches to Smoking Cessation in Heavy Drinkers (NCT02151591), a randomized phase 1 study. The primary outcome is Number of Participants With Smoking Abstinence at 6 Months.

2. Clinical Question

The question is relevant to the study’s stated aim of developing an integrated cognitive-behavioral intervention for smoking and alcohol among heavy-drinking smokers. The intervention addresses both behaviors in counseling, while the comparator focuses on the participant’s primary presenting concern. The registry record describes a randomized design, but the posted results are from a small pre-pilot study rather than the subsequent pilot mentioned in the study description.

The primary result is therefore best read as an early, descriptive comparison that can inform the refinement and planning of later research. The record does not report detailed eligibility rules, baseline characteristics, how the primary presenting concern was assigned, or whether participants could receive other care. Those omissions limit assessment of how representative the enrolled group was and how the two care approaches were delivered in practice.

3. Trial Design

The registry record describes a completed, randomized, parallel-group phase 1 study with no masking. Enrollment was 26. The study start was 2017-03-01, and primary completion was 2018-06-01. Yale University is listed as the sponsor. The record labels the study as a pre-pilot phase intended to refine a protocol for a subsequent randomized, controlled pilot phase; it describes an intake session and brief physical followed by a 12-week treatment phase.

Participants were assigned to integrated counseling for tobacco and alcohol or standard care for the primary presenting concern. The integrated condition included weekly counseling targeting both behaviors and 12 weeks of varenicline. Standard care is described as weekly counseling focused on smoking or alcohol, depending on the primary presenting concern. The standard-care description for participants presenting with alcohol is incomplete in the registry record, and the record does not report whether standard-care participants received varenicline.

The primary outcome was the count of participants with smoking abstinence at 6 months post treatment start, with the endpoint description specifying assessment 6 months after treatment completion. The abstinence definition was no smoking, not even a puff, over the last 7 days. Secondary outcomes were log transformed percentage of heavy drinking days at 6 months post treatment start and the count of participants who completed treatment at 12 weeks.

Detailed randomization procedures, allocation concealment, treatment adherence, masking of outcome assessment, the original sample-size rationale, and the trial’s prespecified statistical analysis plan are not reported in the registry record. The registry record also does not report whether the analyzed participants were treated according to an intention-to-treat, per-protocol, or other analysis population. These gaps mean the design can be characterized in broad terms, but not reconstructed in all operational or analytical details.

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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Number of participants with smoking abstinence at 6 months

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 6 Months, measured over 6 months post treatment start.

The primary endpoint is the number of participants with smoking abstinence at 6 months. The registry description defines point-prevalence abstinence as no smoking, not even a puff, over the last 7 days, assessed 6 months after treatment completion. This is a snapshot of recent smoking status at a specified follow-up time, rather than a measure of continuous abstinence throughout treatment and follow-up.

Counting participants who meet a defined criterion makes the endpoint interpretable as an event count within each group. It also allows a direct comparison of the observed proportions, while retaining the underlying counts needed to understand how much information the study contributes. In the posted results, 6 participants in the integrated-counseling group and 3 in standard care were counted as abstinent. The estimated risk difference was 0.231, with a confidence interval from -0.124 to 0.586.

This endpoint is used because it corresponds to the study’s central tobacco-related question and has a specific operational definition. It does not measure the amount smoked among participants who did not meet the abstinence criterion, nor does it describe abstinence at other time points. The registry record does not report additional details about how smoking status was verified, how missing follow-up observations were classified, or how the timing relative to treatment completion was handled for individual participants.

7. Results Posted in the Registry

• Integrated Counseling for Tobacco and Alcohol (INT): 46.2% (6/13) versus 23.1% (3/13) on control; risk difference 23.1 percentage points (95% CI -12.4 to 58.6), risk ratio 2.00 (0.63–6.34); unadjusted two-proportion z-test p = 0.216.

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.

Log Transformed Percentage of Heavy Drinking Days

• 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 errors.
• Result:
  • Integrated Counseling for Tobacco and Alcohol (INT): mean 2.06 versus 1.45 on control; difference 0.61 (95% CI -0.47 to 1.69), standardized effect d = 0.43; z-test p = 0.269.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Integrated Counseling for Tobacco and Alcohol (INT) and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants Who Completed Treatment.

• 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:
  • Integrated Counseling for Tobacco and Alcohol (INT): 53.8% (7/13) versus 76.9% (10/13) on control; risk difference -23.1 percentage points (95% CI -58.6 to 12.4), risk ratio 0.70 (0.39–1.26); unadjusted two-proportion z-test p = 0.216.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Integrated Counseling for Tobacco and Alcohol (INT) and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes add context on drinking behavior and study participation, but they do not answer the same question as the primary smoking-abstinence endpoint. The heavy-drinking-days measure is a log-transformed percentage score, while treatment completion is a count of participants completing the 12-week period. These outcomes can help describe different aspects of the intervention experience, but they should not be treated as interchangeable measures of smoking abstinence.

Across the posted outcomes, the estimated contrasts have substantial uncertainty. The secondary comparisons are unadjusted, and the registry record lists no reported analyses for them. No multiplicity adjustment or hierarchy for secondary outcomes is reported. Without a prespecified approach to multiple comparisons, each additional test creates another opportunity for a result to appear notable by chance. For that reason, secondary findings generally carry less confirmatory weight than a clearly prespecified primary analysis, especially when the study is small and several outcomes are considered.

The secondary results can be viewed as descriptive signals that may inform later protocol development and selection of measures. They do not independently validate the primary smoking result, because they concern distinct outcomes and arise from the same participants and study context. Nor should a pattern across endpoints be treated as a single combined effect: the record does not report a composite endpoint or a joint analysis.

The record does not report how missing secondary outcome measurements were handled, whether analyses were adjusted for baseline values, or what participant population was included in each outcome analysis. The meaning of the secondary comparisons is therefore bounded by both their statistical uncertainty and the limited reporting of analysis procedures. Any conclusions drawn from these outcomes should remain exploratory and should not be elevated to evidence of a definitive treatment effect.

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

• Log Transformed Percentage of Heavy Drinking Days
• Number of Participants Who Completed Treatment.

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is a count of participants meeting a binary definition: either a participant met the smoking-abstinence criterion at follow-up or did not. For such an outcome, the group-specific proportions are the number meeting the criterion divided by the number in the group. The posted counts are 6 of 13 in integrated counseling and 3 of 13 in standard care. These proportions are reported as 0.462 and 0.231, respectively. The comparison expresses the difference as the integrated-group proportion minus the standard-care proportion.

What does a risk difference describe?

A risk difference is an absolute contrast between proportions. A value of 0.231 means that the observed proportion in the integrated group exceeded the observed proportion in standard care by 0.231 on the proportion scale. It is not a relative increase, and it does not describe the probability that the intervention caused the outcome. The confidence interval quantifies uncertainty around the estimated contrast under the statistical approach used. Because the interval ranges from -0.124 to 0.586, it includes no difference and contrasts in either direction.

The record also gives a risk ratio and an odds ratio for the primary comparison. These are relative measures, unlike the risk difference. The risk ratio is 2.0, with an interval from 0.631 to 6.336; the odds ratio is 2.857, with an interval from 0.528 to 15.47. These estimates are based on the same small set of observed outcomes and are consequently imprecise. Their intervals include the value corresponding to no relative difference. Different effect measures answer different descriptive questions, and they should not be read as independent evidence because they use the same group data.

What does the p-value contribute?

The unadjusted p-value for the primary comparison is 0.216. In general, a p-value describes how compatible the observed data are with a specified null model, under the assumptions of the test. It is not the probability that the null hypothesis is true, and it is not a measure of effect size. The registry record does not report a detailed analysis plan or test specification, so the posted p-value should be read as the unadjusted value attached to this comparison rather than as evidence about an unreported modeling strategy.

A confidence interval and p-value provide related but not identical information. The interval displays a range of effect estimates compatible with the data under the method used, making the uncertainty and direction of possible contrasts visible. The p-value compresses information about compatibility with a null value into a single measure. Neither resolves the limitations created by sparse outcome counts or missing reporting about analysis decisions.

Why does the mean difference use a different interpretation?

The heavy-drinking-days outcome is a mean log-transformed percentage score, not a binary count. Its posted group means are 2.06 for integrated counseling and 1.45 for standard care, and the mean difference is 0.61, with a confidence interval from -0.471 to 1.691. A mean difference is an absolute contrast on the scale analyzed. Because the outcome is log transformed, the difference applies to that transformed scale; it should not be translated directly into a difference in the original percentage without a specified transformation procedure and interpretation. The registry record does not report further details for such a translation.

The secondary outcome reports standard errors of 0.4 and 0.38 for the group means. A standard error describes the estimated sampling variability of a mean, rather than the spread of individual participant values. General statistical note: standard errors help quantify precision of an estimate, while a standard deviation describes variability among observations. The posted mean comparison has an unadjusted p-value of 0.269, and its interval includes no difference.

What can be learned from the planning illustrations?

The planning illustrations use observed effects as starting points and show participant requirements per arm for specified target power levels. They assume a two-sided significance level of 0.05, equal allocation between the arms, and a normal approximation. The assumed effect is a stated fraction of the observed effect. Such calculations are sensitive to the assumed effect: planning for a smaller effect requires more participants to achieve the same target power. These numbers are prospective planning illustrations, not a description of the original study’s design rationale.

General statistical note: power is the probability that a planned analysis will detect a specified effect under stated assumptions if that effect is present. A planning calculation depends on the effect size, outcome variability or event frequency, significance threshold, allocation, and analysis method. The registry record does not report the study’s original sample-size justification or its own design assumptions. The calculations associated with the posted results therefore cannot establish what the investigators planned before enrollment.

The record identifies a randomized, parallel design with no masking, but does not report details of random sequence generation, allocation concealment, missing-data methods, or analysis population. Such features can affect interpretation independently of the choice of effect measure. General statistical note: randomization is intended to make assigned groups comparable on average, but it does not ensure balance in every small study, and the way participants with missing outcomes are handled can change an estimate. Those procedures are not described in the registry record, so their impact cannot be assessed from the posted information.

11. Confidence Intervals and Precision

The primary risk-difference estimate is 0.231, with a 95% confidence interval from -0.124 to 0.586. This interval is wide relative to the point estimate and covers both a negative contrast and a positive contrast. In practical statistical terms, the posted data do not pin down the magnitude of the difference with much precision. The range includes a lower observed abstinence proportion for integrated counseling, no difference, and a higher proportion.

A confidence interval is a range produced by a statistical procedure that, under its assumptions, conveys uncertainty about the underlying effect estimate. It is not a guarantee that the true value lies in the interval, nor is it a range of individual participant outcomes. The confidence interval should be considered alongside the small group counts: 6 abstinent participants in integrated counseling and 3 in standard care. With sparse event counts, a modest change in observed outcomes can materially alter the estimated contrast.

The relative-effect intervals also show substantial uncertainty. The risk-ratio interval ranges from 0.631 to 6.336, and the odds-ratio interval ranges from 0.528 to 15.47. Both span the no-relative-difference value and include a broad set of possible effect sizes. These are alternative summaries of the same primary outcome data, rather than separate replications of the comparison.

For the heavy-drinking-days mean difference, the interval ranges from -0.471 to 1.691 around the estimate of 0.61. That interval likewise includes no difference and contrasts in either direction. These intervals emphasize that the posted point estimates should not be interpreted as precise predictions of what a larger study would find. The registry record does not report additional uncertainty analyses, missing-data sensitivity analyses, or adjusted estimates.

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 illustrations report participants per arm for the binary outcomes and for the continuous heavy-drinking-days outcome. They are not totals across arms and are not total-event counts. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row uses a specified fraction of the observed effect as the effect the hypothetical study is intended to detect.

The 80% power column gives the illustrated number of participants per arm for a design with an 80% chance of detecting the assumed effect under the stated assumptions, if that effect is present. The 90% power column gives the corresponding requirement for a 90% chance under those assumptions. These are target probabilities for a proposed design, not properties of the completed study. This is not observed power.

For the primary smoking-abstinence outcome, the illustration gives 66 participants per arm when planning for 100% of the observed effect, 113 per arm for 75% of the observed effect, and 241 per arm for 50% of the observed effect at the 80% target. At the 90% target, the corresponding entries are 88, 150, and 322 participants per arm. The continuous secondary outcome has its own planning values, which depend on its observed mean difference and variability.

The pattern follows a general principle: smaller effects are harder to distinguish from random variation, so detecting them with the same target power requires more participants. These calculations are illustrative because they begin with effects observed in a small study, which may be unstable. The sample-size justification and assumptions used when the original trial was designed are not reported in the registry record. The planning values should not be mistaken for enrollment targets that were actually used 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.231; treatment proportion p₁ = 0.462; average p̄ = 0.346.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6728 = 1.3187.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6527 = 0.5493.
4. n = (1.3187 + 0.5493)² / (0.2308)² = 65.5, rounded up to 66 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 <- 0.230769230769231                          # control proportion
p1 <- 0.461538461538462                          # 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(2151591)
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 = 66 (80% power), 88 (90% power)
 75% of observed effect: n per arm = 113 (80% power), 150 (90% power)
 50% of observed effect: n per arm = 241 (80% power), 322 (90% power)
power.prop.test: 65.5 
Simulated power at n = 66 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 record lists a primary smoking-abstinence outcome and two secondary outcomes. It does not report a multiplicity strategy, such as adjustment for testing multiple outcomes, a hierarchy of hypotheses, or a rule for interpreting secondary analyses. It also does not report an analysis plan specifying which outcomes were confirmatory and which were exploratory. The posted p-values are unadjusted, so they do not account for the possibility of chance findings across multiple comparisons.

General statistical note: multiplicity arises when several hypotheses are tested or several outcomes are examined. If each is interpreted separately without accounting for the set of tests, the chance of at least one apparently unusual result can increase. Adjustment methods and prespecified testing hierarchies are ways to manage that issue, but the appropriate choice depends on the study’s aims and analysis plan. Because no such plan is reported in the registry record, the secondary results should be regarded as exploratory rather than as a set of definitive confirmatory tests.

Missing-data procedures are also not reported in the registry record. The primary outcome is defined at follow-up, but the record does not explain how participants without an observed follow-up status were treated, whether outcomes were imputed, or whether any sensitivity analyses were performed. Details on missingness for the secondary outcomes are not reported either. General statistical note: when outcome availability is related to participant characteristics or outcomes, complete-case analysis and other missing-data approaches can lead to different estimates. Without the methods and missingness information, the direction or size of any effect cannot be assessed.

The analysis population is not reported in the registry record. It is therefore unclear whether the posted comparisons included all randomized participants, only participants with available outcome data, or another defined group. The record reports 13 participants in each group for the outcome summaries, but that fact alone does not identify the analysis principle used or establish how missing observations were handled.

The registry record reports no analyses in its analysis listing, and no adjusted analyses are described. It also does not report interim analyses, stopping rules, or a detailed statistical analysis plan. These are reporting gaps, not evidence that a particular procedure was or was not used. They limit assessment of prespecification, multiplicity control, and robustness.

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.

The serious adverse event figures report 0 affected participants in the integrated-counseling group and 0 in standard care. The registry record also reports 0 other adverse events and 0 deaths in each group. For the serious-event summaries, 13 participants are listed as at risk in each group; the same at-risk counts are reported for other adverse events.

These figures describe what was recorded in the registry results. They do not establish that no adverse events of any kind occurred outside the reported categories, nor do they quantify the risk of rare events precisely. Zero observed events in a small study can coexist with uncertainty about the frequency that might be observed in a larger population. The registry record does not list serious adverse event terms or provide additional detail about event definitions, collection procedures, severity, or timing.

Safety interpretation is therefore limited to the posted counts. The figures should not be taken as a comprehensive assessment of safety or as a comparison that rules out differences between groups. The record’s adverse-event summaries do not alter the interpretation of the smoking-abstinence endpoint.

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

The posted primary result shows a higher abstinence count in integrated counseling than in standard care: 6 participants compared with 3. The estimated risk difference is 0.231, but its confidence interval, from -0.124 to 0.586, is wide and includes no difference as well as possible contrasts in either direction. The result therefore describes the observed data but does not provide a precise estimate of what would occur in a larger study.

These findings do not establish that the integrated intervention caused a difference in abstinence. Although the study was randomized, details about randomization procedures, outcome ascertainment, analysis population, and missing data are not reported in the registry record. The registry record characterizes the work as a pre-pilot intended to refine a protocol for a subsequent randomized, controlled pilot phase, which is consistent with an early development purpose rather than a definitive evaluation.

The primary endpoint captures recent abstinence at a specific follow-up assessment. It does not measure continuous abstinence, smoking intensity among those not abstinent, or outcomes at other time points. The secondary outcomes address heavy drinking days and treatment completion, not the same construct. Their results cannot be combined with the primary endpoint to make a broader claim unless a prespecified analysis supports doing so, and no such approach is reported.

The planning illustrations are not evidence about the study’s observed power or its original design. They use effects estimated from the posted results to illustrate requirements for hypothetical future studies. As those estimates are imprecise, future planning should not rely on them alone. The original sample-size rationale and design assumptions are not reported in the registry record.

In summary, the registry results offer a preliminary comparison that may be useful for refining later research questions and methods. They neither demonstrate a definitive benefit nor establish the absence of an effect. Interpretation should remain cautious because of the small group counts, wide intervals, and gaps in reporting about analysis and missing data.

17. Why This Trial Matters Statistically

This study is statistically notable as an early randomized comparison focused on an integrated approach to smoking and alcohol counseling among heavy-drinking smokers. Its primary outcome is directly interpretable as a participant count under a stated abstinence definition, while the secondary outcomes reflect drinking behavior and treatment completion. Together, the outcomes illustrate how a developing intervention can be assessed across related but distinct domains.

The principal statistical lesson is the distinction between an observed point estimate and its precision. The integrated group had more participants meeting the abstinence criterion, but the risk-difference interval is broad and includes values on either side of no difference. The point estimate is therefore not a stable forecast of the effect a later study would observe. Reporting the interval alongside the counts helps keep the size and uncertainty of the result in view.

The study also illustrates the role of exploratory data in planning. The sample-size illustrations show how planning requirements vary with the assumed effect, with smaller effects requiring more participants for the same target power. Such illustrations can inform later design discussions, but the observed effects in a small pre-pilot should be treated cautiously. They are not a substitute for a justified design based on prior evidence and a prespecified clinical question.

Finally, the registry record highlights the importance of transparent reporting. Information about missing data, analysis populations, multiplicity, and randomization procedures is needed to fully assess the statistical interpretation. The absence of those details does not itself invalidate the posted results, but it narrows the conclusions that can be drawn. The clearest use of these findings is as a preliminary description that motivates careful design and reporting in subsequent work.

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.

This was a small pre-pilot study, with 13 participants reported in each group for the primary outcome. The primary abstinence counts were 6 and 3, so the estimate is based on relatively few observed events. The wide confidence interval reflects substantial uncertainty. Results from a study of this size may also be sensitive to individual outcome classifications.

The record describes the study as open label, with no masking. It does not report whether outcome assessors were masked or how abstinence was verified. The precise procedures for random sequence generation and allocation concealment are also not reported in the registry record. These omissions make it difficult to assess protections against bias in assignment and outcome measurement.

The standard-care description is incomplete for participants whose primary presenting concern was alcohol, and use of varenicline in the standard-care group is not reported. Details on treatment adherence, fidelity, outside treatment, and how the primary presenting concern was determined are not reported in the registry record. These details would help clarify how the intervention and comparator differed in practice.

The record does not explain how missing outcomes were handled or which analysis population was used. Baseline participant characteristics and detailed eligibility criteria are not reported. The original sample-size justification, prespecified statistical plan, multiplicity strategy, and interim analyses are also not reported in the registry record. In addition, the secondary outcome analyses are not listed as reported analyses. These gaps constrain assessment of selection, missingness, and selective interpretation.

The study’s purpose was to refine an intervention for later evaluation, which limits how far its results can be generalized. The registry record does not report enough detail to determine how representative participants were of heavy-drinking smokers more broadly. The findings should therefore be interpreted as preliminary and specific to the posted study results.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: New Approaches to Smoking Cessation in Heavy Drinkers — NCT02151591.
• Registry record last updated 2020-02-24; status last verified 2020-02.
• Results first posted 2020-02-10.
• 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 registry record describes a completed randomized, parallel-group phase 1 pre-pilot study sponsored by Yale University. Enrollment was 26, and the study compared integrated smoking-and-alcohol counseling with standard care for the primary presenting concern. The integrated condition included 12 weeks of counseling and varenicline.

The primary outcome was smoking abstinence at 6 months, defined as no smoking, not even a puff, over the last 7 days. The posted counts were 6 in integrated counseling and 3 in standard care. The estimated risk difference was 0.231, with a 95% confidence interval from -0.124 to 0.586 and an unadjusted p-value of 0.216. Secondary outcomes concerned log-transformed percentage of heavy drinking days and treatment completion.

The registry record does not report the original sample-size rationale, detailed analysis plan, multiplicity approach, missing-data methods, or analysis population. The results are best interpreted as preliminary, with substantial uncertainty around the primary comparison.