Persistence-Targeted Smoking Cessation: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Persistence-Targeted Smoking Cessation (NCT01654107), a randomized phase 1 study. The primary outcome is 7-day Point Prevalence Abstinence.

2. Clinical Question

The clinical question is therefore a comparison of abstinence counts following two counseling approaches, with nicotine lozenge included in both arm descriptions. The outcome is a snapshot of abstinence over the 7-day point-prevalence period at the specified follow-up, rather than a measure of continuous abstinence over the entire time since quitting. The record describes the study as testing feasibility and preliminary efficacy, with cigarettes per day and prolonged abstinence also mentioned in the brief summary. However, only one outcome measure is posted, and the record does not provide posted results for those other measures.

3. Trial Design

This was a Phase 1, randomized, parallel-group trial with no masking listed. The registry record identifies Rutgers, The State University of New Jersey, as the sponsor. It lists the study start as 2012-07, primary completion as 2014-09, and status as completed.

The two arms were Persistence Targeted Smoking Cessation and Clearing The Air. Both arm descriptions include 8 weeks of counseling and 12 weeks of nicotine lozenge. The first arm is described as an individual counseling intervention, while the second is described as a smoking-cessation intervention. The registry does not provide more detail about how counseling was delivered, how participants were assigned, or whether the two counseling programs differed in content beyond their names and descriptions.

Enrollment is listed as 58. The primary outcome results list 25 participants in the Persistence Targeted Smoking Cessation arm and 28 in the Clearing The Air arm. The record does not explain the difference between the enrollment figure and the arm counts listed for this outcome, so those figures should not be treated as interchangeable descriptions of the same analysis population.

The record labels the trial randomized and parallel, but does not state the randomization sequence method, allocation concealment, or other implementation details. Masking is listed as none. The trial's own sample-size justification, original design assumptions, and any planned interim analyses are not reported in the registry record. The posted comparison is unadjusted; the record does not describe a detailed statistical analysis plan.

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 7-day Point Prevalence Abstinence, measured over 3-months.

The primary endpoint is 7-day Point Prevalence Abstinence, measured as the number of participants at 3-months after the Quit Date. The posted arm results give the count of participants meeting the abstinence definition rather than a continuous measurement. Four participants are listed for Persistence Targeted Smoking Cessation and one for Clearing The Air. The corresponding outcome group sizes are 25 and 28.

Point-prevalence abstinence is used to describe smoking status during a specified recent period at a follow-up assessment. It answers whether participants meet the stated abstinence criterion at that assessment, not whether they remained abstinent throughout all time since the quit date. The registry record separately mentions cigarettes per day and prolonged abstinence in its brief summary, but does not post results for those outcomes. Nor does the record provide a more detailed definition of how abstinence was verified or handled when information was missing. Those details are not reported in the registry record.

Because the endpoint is a count of participants with an event, the comparison can be expressed as a difference between the arms' observed abstinence proportions. The posted result should be read as an outcome at a specific follow-up, not as a complete description of the course of smoking behavior during the intervention or after it.

7. Results Posted in the Registry

• Clearing The Air: 3.6% (1/28) versus 16.0% (4/25) on control; risk difference -12.4 percentage points (95% CI -28.4 to 3.5), risk ratio 0.22 (0.03–1.87); unadjusted two-proportion z-test p = 0.122.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level: a participant either meets the 7-day point-prevalence abstinence outcome at the specified assessment or does not. The registry reports the number meeting the outcome in each arm. A binary outcome can be summarized as a count and as a proportion within each arm. The posted comparison reports a risk difference, which expresses the difference between those proportions. In this comparison the direction is Clearing The Air relative to Persistence Targeted Smoking Cessation, and the estimated risk difference is negative.

What does the risk difference convey?

The risk difference is an absolute contrast between the observed proportions. A value at zero would represent no difference in those proportions. A negative estimate in this comparison means the observed proportion is lower in Clearing The Air than in Persistence Targeted Smoking Cessation. This interpretation describes the estimate, not a definitive causal effect. Random allocation supports a comparative design, but the precision of the estimate and the study's conduct remain relevant to interpretation.

The registry also gives a confidence interval for the risk difference. In general, a confidence interval describes a range of estimates compatible with the data under the method used, while reflecting sampling uncertainty. It does not mean that every value in the interval is equally plausible, and it is not a guarantee that the true value lies inside that particular interval. Here, the reported interval crosses zero, so the data are compatible with a negative difference, no difference, or a positive difference under the interval procedure. The confidence level and construction method are not reported in the registry record.

How should the p-value be read?

The unadjusted p-value is 0.122. In general, a p-value describes how unusual the observed data, or data more extreme, would be under a specified null model. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of a difference. The registry identifies the value as unadjusted and does not report an adjusted analysis. The result should therefore be read as a single posted, unadjusted comparison rather than as the outcome of a documented family of tests.

Why are risk ratios and odds ratios also reported?

A risk ratio compares the proportions between arms as a ratio. An odds ratio compares the odds of the outcome between arms. Both are relative measures, whereas a risk difference is an absolute measure. Their interpretation depends on the underlying outcome frequency, and an odds ratio is not the same quantity as a risk ratio. The posted relative-effect intervals cross their respective values indicating no relative difference. With few outcome events, these estimates can be unstable and their intervals broad. The registry does not state which measure was designated as the primary inferential comparison in a protocol or analysis plan.

These effect measures are alternative descriptions of the same endpoint comparison, not separate trial findings. They should be considered alongside the event counts and the risk-difference interval. No adjusted model, covariate set, or subgroup analysis is described in the registry record. The posted result is therefore most straightforwardly understood as an unadjusted comparison of the arm-level outcome counts.

What does randomization contribute?

In general, random allocation is intended to make treatment groups comparable with respect to measured and unmeasured characteristics at assignment. It does not guarantee exact balance in a small study, and it cannot by itself resolve missing outcome data or implementation differences. The registry labels allocation as randomized but does not report the sequence-generation method, concealment procedure, or details of the analysis population. Masking is listed as none. The absence of masking can matter for outcomes or assessments that involve judgment, although the record does not describe outcome verification sufficiently to assess its role in this endpoint.

The posted data contain no analysis entries, despite the primary outcome result being present. A detailed statistical plan, including methods for missing outcomes and the analysis population, is not reported in the registry record. Consequently, it is not possible to establish from the registry which protocol-specified method, if any, governed the posted comparison. The statistical interpretation should remain tied to the unadjusted result and the information actually recorded.

10. Confidence Intervals and Precision

Precision is limited by the modest arm counts and the small number of participants meeting the abstinence endpoint. Four participants are listed as abstinent in Persistence Targeted Smoking Cessation and one in Clearing The Air. With sparse events, moving a small number of outcomes between categories could materially change the estimated arm contrast. This is one reason to give the interval and counts more weight than a point estimate alone.

The confidence interval for the risk difference extends across zero. That means the posted data do not pin down the direction of the difference with precision: the interval includes values on either side of no difference. Its width reflects substantial uncertainty about the magnitude as well. The registry record does not state the confidence level or interval method, so those details cannot be used to refine the interpretation.

The relative-effect intervals also span their no-difference values. Relative estimates can be particularly difficult to interpret when outcome counts are sparse, because small count changes can produce pronounced shifts in ratios. The interval information is therefore central: a single point estimate should not be treated as a precise estimate of the likely underlying effect.

The unadjusted p-value of 0.122 is consistent with uncertainty, but does not quantify precision by itself. A p-value cannot distinguish a small effect from a larger but imprecisely estimated effect. The posted confidence intervals and event counts convey that uncertainty more directly. The result is suitable for describing the observed comparison and its imprecision; the registry record does not support a precise estimate of the true difference.

11. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total participants or total events. They are illustrations based on the observed effect, with calculations specified as two-sided at a significance level of 0.05, equal allocation between the arms, and a normal approximation. The displayed scenarios use 100%, 75%, and 50% of the observed effect as the effect to detect. The registry record does not report the trial's own original design assumptions or sample-size justification.

The 80% power column gives the planned number of participants per arm for a hypothetical study with an 80% chance of detecting the specified effect under those assumptions, if that effect and model were correct. The 90% power column gives the corresponding planning number for a 90% chance. These are design targets, not probabilities that the observed result is correct and not measures of what this trial achieved.

The figures rise as the target effect becomes smaller: planning for 75% of the observed effect requires more participants per arm than planning for the full observed effect, and planning for 50% requires more again. This reflects a general statistical principle: smaller differences are harder to distinguish from random variation, so larger studies are generally needed to detect them with the same planned power and significance level.

For the listed scenarios, the figures are 89 and 119 participants per arm for planning for 100% of the observed effect; 181 and 242 for 75%; and 456 and 610 for 50%, for 80% and 90% power respectively. These are hypothetical planning illustrations derived from the observed effect, not observed power for the completed trial.

12. How the Sample Size Is Derived

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

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.160; treatment proportion p₁ = 0.036; average p̄ = 0.098.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4202 = 0.8236.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4109 = 0.3458.
4. n = (0.8236 + 0.3458)² / (-0.1243)² = 88.5, rounded up to 89 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 <- 0.16                          # control proportion
p1 <- 0.0357142857142857                          # 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(1654107)
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 = 89 (80% power), 119 (90% power)
 75% of observed effect: n per arm = 181 (80% power), 242 (90% power)
 50% of observed effect: n per arm = 456 (80% power), 610 (90% power)
power.prop.test: 88.5 
Simulated power at n = 89 per arm: 0.836 (20000 replicates)

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

13. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes, time points, subgroups, or statistical comparisons are tested. If many tests are conducted, the chance of at least one apparently notable result can increase unless the analysis plan addresses that issue. The registry lists one outcome measure and no analysis entries. Its brief summary mentions cigarettes per day and prolonged abstinence as outcomes of interest, but results for those measures are not posted in the registry record. It is therefore not possible to determine from the record whether additional outcome analyses were conducted or how any family of tests was handled.

The record reports one unadjusted p-value for the posted arm comparison. It does not describe a multiplicity adjustment, a hierarchy of outcomes, or a prespecified testing strategy. The absence of such details should not be taken as evidence that no other analyses took place; those details are not reported in the registry record. The p-value should be interpreted as the value for the posted unadjusted comparison, without assuming that it accounts for other possible analyses.

Missing-data handling is also not reported in the registry record. The outcome group sizes are 25 and 28, while enrollment is listed as 58. The record does not explain how participants without an outcome, if any, were handled, whether all assigned participants were included in the comparison, or whether any imputation was used. The difference among the listed counts cannot by itself establish a particular missing-data pattern or analysis population.

The registry does not state whether the analysis followed intention-to-treat principles, a per-protocol approach, or another defined population. Nor does it report sensitivity analyses for missing outcomes. These omissions matter because handling unavailable outcome information can affect estimated proportions and the comparison between arms. Interpretation should therefore distinguish the posted outcome counts from assumptions about all randomized participants.

The absence of analysis entries also limits assessment of whether the reported comparison matches a prespecified method. The registry record does not provide an analysis plan, covariate adjustments, interim-analysis details, or subgroup methods. None of these should be inferred from the single unadjusted result.

14. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

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 figures list zero affected participants in each arm's recorded risk set: 28 for Persistence Targeted Smoking Cessation and 30 for Clearing The Air. This is a count of serious adverse events recorded in the registry, not proof that no serious events occurred outside the recorded data or that risk is absent. No serious adverse event terms are listed.

The other adverse event figures list 19 affected participants among 28 at risk in Persistence Targeted Smoking Cessation and 13 among 30 at risk in Clearing The Air. These are the registry's event-group counts. The record does not provide further descriptions of the events, their severity, timing, relationship to an intervention, or the method used to collect them. Death counts are not reported in the registry record.

The adverse-event risk sets differ from the outcome group sizes listed for the abstinence endpoint. The registry does not explain that difference, so these denominators should be read within their own outcome group rather than substituted for one another. Counts alone do not establish comparative safety, especially without event descriptions and fuller follow-up information.

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

The posted data describe a completed randomized comparison of two smoking-cessation intervention packages. At the stated assessment, four participants in Persistence Targeted Smoking Cessation and one participant in Clearing The Air met the 7-day point-prevalence abstinence outcome. The estimated risk difference is negative when Clearing The Air is compared with Persistence Targeted Smoking Cessation, and its interval includes zero. The unadjusted p-value is 0.122.

These results describe the observed participants and the uncertainty around the comparison. They do not establish that one intervention is superior, that the interventions are equivalent, or that there is no difference. An interval spanning the no-difference value means the estimate is not precise enough to rule out effects in either direction under the reported interval procedure. The p-value does not settle that uncertainty and should not be interpreted as a probability that a treatment effect exists.

The endpoint is a point-prevalence measure at 3-months after the Quit Date. It does not establish continuous abstinence over the full period, nor does it give the broader pattern of cigarette consumption. The registry's brief summary also refers to cigarettes per day and prolonged abstinence, but those results are not posted. There is no basis in the record for attributing the observed comparison to one component of the intervention, since both arm descriptions include counseling and nicotine lozenge.

The trial is described as a feasibility and preliminary efficacy study. The small event counts and wide uncertainty make the findings more useful as a preliminary estimate than as a definitive answer. The sample-size illustrations show the scale of planning requirements under stated hypothetical assumptions, but they do not establish the original design rationale or the trial's observed power. The record also leaves important questions about analysis populations, missing outcomes, and multiplicity unanswered.

Accordingly, the result supports a cautious statistical reading: the arm counts differ in the observed sample, while the estimate remains imprecise. The registry record does not supply enough detail to extend that finding to other outcomes, explain intervention mechanisms, or characterize long-term abstinence.

16. Why This Trial Matters Statistically

This trial is statistically informative because it makes clear how easily a difference in a binary endpoint can remain uncertain when event counts are sparse. The observed counts differ, but the confidence interval crosses the no-difference value. Reporting counts together with an effect estimate and interval helps prevent the observed direction from being mistaken for a precise or definitive treatment contrast.

The study also illustrates the importance of separating the endpoint from broader clinical ideas. Seven-day point-prevalence abstinence captures status during a defined recent period at a follow-up. It is not equivalent to prolonged abstinence, and it does not describe changes in cigarettes per day. The record's brief summary names those additional outcomes, yet only the point-prevalence outcome has posted results. Careful outcome-specific interpretation is therefore essential.

Another statistical issue is the distinction between an observed result and a planning calculation. The sample-size illustrations use fractions of the observed effect under explicit assumptions. They show that smaller target effects require larger per-arm samples, but they do not reveal the trial's original rationale or provide observed power. Keeping these planning quantities separate from the completed trial result avoids a common misreading of post hoc calculations.

Finally, the registry's limited reporting on the analysis population, missing data, and multiplicity highlights why transparent reporting is part of statistical interpretation. The randomization label and unadjusted comparison are useful, but they do not answer every question about implementation or analysis. The result is most valuable when read alongside its uncertainty and the limits of what the registry record documents.

17. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several limitations are specific to the information recorded for this trial. The registry lists enrollment of 58, while the primary outcome counts are associated with groups of 25 and 28. The record does not explain the difference or identify the analysis population. Missing outcome handling and whether all randomized participants were included are not reported in the registry record.

The posted endpoint is 7-day point-prevalence abstinence at 3-months after the Quit Date. The record does not provide a more detailed operational definition, describe verification, or state how unavailable responses were treated. Other outcomes named in the brief summary, including cigarettes per day and prolonged abstinence, do not have posted results. The single posted endpoint therefore cannot represent the full set of outcomes the investigators described as relevant.

The study is Phase 1 and described as assessing feasibility and preliminary efficacy. The posted arm counts include few abstinence events, and the effect estimate is imprecise. The registry does not provide a sample-size justification or its original design assumptions, so the planning illustrations should not be mistaken for the trial's original target or rationale.

Although the allocation is listed as randomized, methods for sequence generation and allocation concealment are not reported. Masking is listed as none. The record does not provide enough detail to judge implementation or outcome assessment. It also does not describe intervention adherence, counseling fidelity, or use of nicotine lozenge beyond the arm descriptions.

Finally, analysis entries, multiplicity procedures, covariate adjustments, interim analyses, and missing-data sensitivity analyses are not reported in the registry record. Safety reporting is limited to event counts, without event descriptions or deaths reported. These gaps constrain interpretation of both the efficacy comparison and safety counts.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Persistence-Targeted Smoking Cessation — NCT01654107.
• Registry record last updated 2017-08-21; status last verified 2017-07.
• Results first posted 2015-09-16.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

The completed Phase 1 study, NCT01654107, compared Persistence Targeted Smoking Cessation with Clearing The Air in a randomized, parallel-group design with no masking listed. Enrollment was 58, and the sponsor was Rutgers, The State University of New Jersey. The study start is recorded as 2012-07 and primary completion as 2014-09.

The primary posted outcome was 7-day Point Prevalence Abstinence at 3-months after the Quit Date. Four participants in Persistence Targeted Smoking Cessation and one in Clearing The Air met the outcome. The unadjusted comparison reports a negative risk difference for Clearing The Air relative to Persistence Targeted Smoking Cessation, with an interval crossing zero and an unadjusted p-value of 0.122.

The record describes the interventions as 8 weeks of counseling and 12 weeks of nicotine lozenge in both arms. It does not post results for other outcomes mentioned in the brief summary, and important analysis details, including missing-data handling and the analysis population, are not reported in the registry record.