Switching Individuals in Treatment for Opioid Use Disorder Who Smoke Cigarettes to the SREC: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Switching Individuals in Treatment for Opioid Use Disorder Who Smoke Cigarettes to the SREC (NCT05881304), a randomized na study. The primary outcome is Cigarettes Smoked Per Day.

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group pilot trial with a waitlist-control design. The registry lists allocation as randomized and masking as none. It describes a mixed-methods sequential explanatory design intended to assess feasibility, acceptability, and preliminary effects of SREC provision. The study status is completed. Enrollment was 41; the brief description had planned N=40.

Participants in the immediate-start group were offered a free 8-week supply of standardized research e-cigarettes and asked to try to switch completely to the device. Participants assigned to the waitlist control did not receive SREC provision until after an 8-week delay. The primary comparison was defined from baseline to Week 8, corresponding to the immediate group’s initial provision period and the control group’s waitlist period. The registry describes additional follow-up after provision ends, to 12 weeks in the immediate-start group and 20 weeks in the waitlist-control group.

The posted primary outcome is cigarettes smoked per day. Secondary outcomes include e-cigarette use during provision, breath carbon monoxide, Anabasine, enrollment, and study completion. The registry also describes broader areas of interest, including dependence, withdrawal, tolerability, respiratory symptoms, and substance use, but those descriptions should not be mistaken for reported comparative results. No secondary analyses are listed as reported analyses.

The registry record does not report the randomization sequence method, allocation concealment, the original sample-size justification, or a detailed statistical analysis plan. It also does not report a masking procedure. The intervention was a device, and no drug phase is applicable in the record. These design details matter when judging how far the posted estimates can be generalized beyond this pilot trial.

4. Participant Flow and Accounting

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

Overall Study

Analysis population for the primary outcome, as defined in the registry: The numbers are different denominators because there were missing Anabasine data in both Baseline and Week 8.

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 Cigarettes Smoked Per Day, measured over Baseline to Week 8.

The primary endpoint is the change in cigarettes smoked per day between baseline and Week 8. It is defined as the change in the mean number of cigarettes smoked in the past 7 days, comparing the immediate SREC group with the waitlist-control group. Cigarettes per day is a continuous measure of smoking behavior, so the registry reports group means and standard deviations and a mean difference between groups.

This measure was chosen to address the trial’s central behavioral question: whether cigarette consumption changed differently during the period when one randomized group had immediate access to SREC and the other was in the waitlist-control period. It offers a direct measure of reported cigarette use, while other outcomes such as e-cigarette use and biomarkers provide related but distinct information. A change in cigarettes per day does not, by itself, establish complete switching, changes in dependence, or longer-term health effects.

The registry reports a Baseline to Week 8 timeframe and labels the primary outcome as a group comparison of change. Its posted group summaries are 8.1 for immediate start and 1.4 for waitlist control, with standard deviations of 4.7 and 7.6. The mean difference is reported as -6.7, with a confidence interval from -10.64 to -2.759. The record does not describe the precise coding of change or the detailed method used to estimate the comparison, so interpretation should stay close to the stated outcome definition and posted contrast.

7. Results Posted in the Registry

• SREC Waitlist Control (WLC): mean 1.40 versus 8.10 on control; difference -6.70 (95% CI -10.64 to -2.76), standardized effect d = -1.08; z-test p = <0.001.

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.

E-cigarette Use During E-cigarette Provision

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • SREC Waitlist Control (WLC): mean 1.80 versus 6.20 on control; difference -4.40 (95% CI -5.63 to -3.17), standardized effect d = -2.30; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for SREC Waitlist Control (WLC) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Breath Carbon Monoxide

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • SREC Waitlist Control (WLC): mean -6.10 versus -10.60 on control; difference 4.50 (95% CI -2.83 to 11.83), standardized effect d = 0.44; z-test p = 0.229.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SREC Waitlist Control (WLC) and the control. The interval gives the range of effects that remain compatible with the data.

Study Completion

• 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:
  • SREC Waitlist Control (WLC): 84.2% (16/19) versus 81.8% (18/22) on control; risk difference 2.4 percentage points (95% CI -20.6 to 25.4), risk ratio 1.03 (0.78–1.36); unadjusted two-proportion z-test p = 0.839.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SREC Waitlist Control (WLC) and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes provide complementary evidence about intervention engagement, biomarkers, and study participation, rather than repeating the primary behavioral measure. E-cigarette-use frequency describes use of the assigned device, while breath carbon monoxide is a biomarker measure. Study completion is a measure of retention over the follow-up periods. Each outcome therefore addresses a different part of feasibility or preliminary assessment, and none alone substitutes for the primary cigarette-use endpoint.

The overall pattern should be read cautiously. The posted e-cigarette-use comparison is distinct from the cigarette-consumption comparison; it can provide context about device use but does not establish complete substitution. The breath carbon monoxide estimate is comparatively uncertain, with an interval that includes zero. The study-completion comparison is also imprecise. These outcomes neither independently confirm nor overturn the primary result, particularly because their measurement scales and meanings differ.

The registry lists no reported analyses for the secondary outcomes. Their posted comparisons are unadjusted, and the record does not state how multiplicity was handled. When multiple endpoints are examined, the chance of finding at least one apparently notable result by chance can increase. This general concern means secondary findings should ordinarily carry less weight than a clearly prespecified primary analysis, especially when there is no reported adjustment or confirmatory analysis plan.

Differences in denominators also matter when comparing secondary outcomes. The carbon monoxide outcome has fewer observations than the primary outcome, and the registry’s note identifies missing Anabasine data at baseline and Week 8. The record does not give a complete endpoint-by-endpoint explanation of missing observations. As a result, secondary comparisons are best regarded as descriptive signals about different study domains, not as a unified demonstration of efficacy or safety.

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

• Study Enrollment
• E-cigarette Use During E-cigarette Provision
• Breath Carbon Monoxide
• Anabasine
• Study Completion

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous: it is a mean change in cigarettes smoked per day. A comparison of group means summarizes how the average outcome differs between randomized groups. In the registry’s primary comparison, the reported mean difference is -6.7, with the waitlist-control group listed as the comparison arm. The two group means are 8.1 and 1.4. The record does not report the calculation details or an adjusted model, so the contrast should be read as the reported group comparison rather than as a fully specified model estimate.

What does a standard deviation describe?

A standard deviation describes how spread out individual measurements are around a group mean. Larger standard deviations indicate greater participant-level variability in the measured outcome. They do not describe uncertainty in the estimated difference between groups, and they are not ranges containing every participant’s value. For the primary outcome, the recorded standard deviations are 4.7 and 7.6. The mean difference and its confidence interval answer a different question: they describe the estimated contrast between groups and the uncertainty around that contrast.

How should the confidence interval be read?

A confidence interval gives a range of estimates compatible with the data and the statistical procedure used, under that procedure’s assumptions. It is not a range of individual participant outcomes and does not mean that every value in the interval is equally likely. The primary interval runs from -10.64 to -2.759. Because zero is not within that interval, it is inconsistent with a zero group difference at the corresponding conventional two-sided test level. This statement concerns statistical compatibility, not clinical importance or certainty that the estimated contrast is the true effect.

What does the p-value add?

The unadjusted p-value for the primary comparison is <0.001. A p-value is a measure of how compatible the observed data are with a specified null hypothesis under the statistical test and its assumptions. It is not the probability that the null hypothesis is true, nor is it a measure of effect size. The registry labels this p-value unadjusted. Since the analysis method is not detailed in the record, readers should not assume a particular covariate adjustment, repeated-measures model, or missing-data procedure.

Why does the analysis population matter?

For each outcome, the number of participants contributing data can affect the estimate and its precision. The primary outcome lists 22 in the immediate-start group and 19 in the waitlist-control group. The registry’s primary-outcome population note attributes different denominators to missing Anabasine data at baseline and Week 8. That explanation does not fully clarify the relationship between missing biomarker data and the cigarette-use endpoint, so the endpoint-specific missing-data handling is not reported in the registry record. There is no reported account of whether analyses followed intention-to-treat assignment, used only observed cases, or applied imputation.

When data are missing, the implications depend on why values are absent and how missingness relates to participant characteristics and outcomes. If missingness differs between groups or is related to smoking behavior, a complete-case comparison can be biased. This is a general statistical concern, not evidence that a particular bias occurred in this trial. The registry record does not provide enough detail to assess the missingness mechanism or to compare alternative analysis strategies.

Why does over-dispersion matter?

Over-dispersion is a general issue that arises when observed variability is greater than a statistical model expects. For count outcomes, a simple model may underestimate uncertainty if the outcome varies more widely than its assumptions allow. Cigarettes per day is recorded as a continuous mean outcome in this registry, and the posted group standard deviations show variability, but the record does not report an over-dispersion assessment or a model that addresses it. It would therefore be inappropriate to claim that over-dispersion was present or that a particular adjustment was used.

What can be inferred from the posted analysis details?

The registry gives group summaries, contrasts, confidence intervals, and unadjusted p-values for posted comparisons. It does not list reported analysis descriptions for the secondary endpoints, and it does not provide a full statistical analysis plan. The random allocation and parallel design define the intended comparison, but do not reveal whether the analysis adjusted for baseline values, incorporated repeated observations, or accounted for other variables. Inferences should therefore be limited to the posted summaries and their stated uncertainty. General explanations of statistical quantities do not fill in unreported analytic decisions.

11. Confidence Intervals and Precision

The primary confidence interval extends from -10.64 to -2.759 around a mean difference of -6.7. Its endpoints are both negative, so the interval does not include a zero contrast. This indicates that the posted estimate is statistically distinguishable from zero under the procedure used to calculate the interval. It does not establish that the point estimate is exact, nor does it describe the range of individual changes among participants.

The interval still allows a range of possible group contrasts. Its width reflects uncertainty in the estimate, which can be influenced by sample size, outcome variability, and the analysis method. The primary group standard deviations, 4.7 and 7.6, indicate that participant outcomes varied within each arm. The registry does not report enough analytic detail to assess whether the interval accounts for baseline values, repeated measures, or missing outcomes in a particular way.

Precision differs across outcomes. The breath carbon monoxide comparison has an interval from -2.828 to 11.83, which includes zero. The study-completion risk difference has an interval from -0.206 to 0.254, also including zero. These intervals are compatible with a range of contrasts and do not provide a precise estimate of a direction of difference. Their interpretation should remain tied to the particular outcome, its scale, and its contributing observations.

A confidence interval is not a guarantee that the true effect lies inside its limits for this specific study. In repeated use of the same procedure under its assumptions, intervals of this type have a stated coverage property. That general interpretation depends on assumptions that cannot be fully checked from the registry record. The pilot scale and unreported analysis details counsel against treating any estimate as definitive.

12. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm for the continuous and binary outcomes listed; they are not total sample sizes. The sample-size assumptions stated in the registry are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect. The time-to-event convention does not apply to these outcomes; the registry says time-to-event figures, when present, are total event counts, while the other figures are participants per arm.

The 80% power column describes the number of participants per arm that a planning calculation estimates would give an 80% chance of detecting the specified effect under those assumptions, if that effect were the true effect and the assumptions held. The 90% column uses a higher probability of detecting the specified effect, so it generally requires more participants per arm. These are planning illustrations derived from observed effects, not the trial’s original sample-size justification; that original justification is not reported in the registry record.

Each planning scenario uses a fraction of the observed effect. Planning for 75% or 50% of the observed effect means targeting a smaller effect than planning for 100% of the observed effect. Smaller effects are harder to distinguish from random variation, so they require more participants under otherwise similar assumptions. The figures are not observed power and do not measure whether this completed trial was adequately powered. They also do not account for unreported design choices or missing-data procedures in the original trial plan.

13. How the Sample Size Is Derived

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

Formula

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

Worked calculation for this trial

1. Observed difference Δ = -6.700; pooled standard deviation σ = 6.209.
2. n = 2 × (1.96 + 0.842)² × 6.209² / -6.700² = 13.5, rounded up to 14 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -6.7                      # observed difference in means
sigma <- 6.20911241024649                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(5881304)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 14 (80% power), 19 (90% power)
 75% of observed effect: n per arm = 24 (80% power), 33 (90% power)
 50% of observed effect: n per arm = 54 (80% power), 73 (90% power)
power.t.test: 14.5 
Simulated power at n = 14 per arm: 0.787 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a multiplicity plan. It lists one primary outcome and several secondary outcomes, but does not state whether outcomes were ordered hierarchically, whether any adjustment was planned, or whether secondary findings were intended to be confirmatory. Without such information, unadjusted secondary p-values should be interpreted cautiously. Examining multiple outcomes can increase the chance that at least one result appears unusual even if no corresponding underlying difference exists. This is a general statistical issue, not a claim that any particular finding in this trial is spurious.

Missing data are relevant because the record notes different denominators and attributes them to missing Anabasine data at baseline and Week 8. The primary group summaries list 22 and 19 participants, while the carbon monoxide summaries list 18 and 14. The registry does not report a full accounting of missingness by outcome or time point, the reasons values were missing, or whether the missingness differed by randomized group. The specific impact of missing data on the estimates therefore cannot be determined from the record.

The record also does not describe an intention-to-treat analysis population, a per-protocol population, imputation, sensitivity analyses, or a missing-data model. These are not interchangeable choices. An analysis using only observed values can differ from an analysis that imputes missing outcomes or models repeated observations. The likely direction and magnitude of any resulting change cannot be inferred without further information.

Similarly, the registry does not report how the primary comparison handled baseline measurements or whether it adjusted for other variables. The posted contrast and unadjusted p-value should not be described as an adjusted model result. For a pilot trial with multiple outcomes, transparent reporting of the prespecified analysis plan, outcome-specific denominators, and sensitivity analyses would help distinguish planned inference from exploratory findings. Those details are not reported in the registry record.

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 summaries report zero affected participants in each listed group-period. The immediate-start group lists 22 participants at risk and 0 with a serious adverse event. The waitlist-control group during SREC provision lists 19 at risk and 0 affected; during the control period it also lists 19 at risk and 0 affected. Deaths are listed as 0 in each group-period.

These counts should be read as the registry’s reported serious adverse event figures for the periods and groups named. A zero count means no serious adverse events were recorded in those summaries; it does not prove that an event is impossible or that there is no safety concern. The record also lists other adverse events separately, but the serious-event figures alone do not describe the nature, severity, duration, or causal relationship of any non-serious events. The registry record does not provide further detail on serious-event definitions or adjudication.

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

The primary result is a reported group difference in change in cigarettes smoked per day from baseline to Week 8. Its estimate is -6.7, and its confidence interval does not include zero. The posted summaries therefore indicate a difference between the randomized groups on this measured outcome during the stated period. The estimate describes a group-level comparison and should not be treated as the response expected for any particular participant.

The result does not establish that participants switched completely from cigarettes to SREC, even though the immediate-start group was asked to try to switch completely. Nor does a change in cigarettes per day by itself establish changes in long-term smoking, dependence, withdrawal, health effects, or substance use. Those are distinct outcomes, and the registry record does not report full comparative results for all of them.

The trial was described as a pilot focused on feasibility, acceptability, and preliminary effects. It enrolled 41 participants and used a randomized waitlist-control design, but the record does not report the original sample-size rationale or detailed analysis plan. The confidence interval captures statistical uncertainty under the procedure used, but it cannot correct for incomplete reporting or unresolved questions about missing data and analytic choices.

The findings should not be generalized automatically to people outside the study population described in the registry. The participants were adults stable on buprenorphine treatment who reported daily smoking and were recruited from Massachusetts General Hospital primary care practices. The record does not establish that the same estimates would apply in other clinical settings, to people with different treatment circumstances, or over longer periods.

Accordingly, the posted data support a cautious description of an observed between-group difference in the primary measure, alongside limitations in precision, reporting, and scope. They do not amount to a definitive claim about overall benefit, harm, or suitability of SREC use.

17. Why This Trial Matters Statistically

This trial is statistically interesting because it combines random assignment with a waitlist-control comparison in a pilot study of a behavioral outcome. Randomization aims to make the groups comparable in expectation, while the waitlist arrangement defines a clear initial period for comparing immediate access with delayed access. The primary outcome is a continuous measure, allowing the registry to report means, standard deviations, a mean difference, and a confidence interval.

The reported primary estimate and its interval illustrate why effect estimates and precision should be read together. A small p-value alone does not communicate the size or uncertainty of a contrast; the estimate and confidence interval provide that context. Conversely, secondary estimates with intervals including zero should not be treated as proof of no difference. Their uncertainty and distinct outcome meanings matter.

The pilot setting also makes planning illustrations easy to misuse. Sample-size calculations based on an observed effect can be useful for exploring future design scenarios, but observed pilot estimates may be unstable. The posted planning figures are not the original trial’s design justification and are not observed power. They show how required enrollment changes when a design targets smaller effects or seeks a higher chance of detecting a specified effect, under stated assumptions.

Finally, the record demonstrates the importance of reporting denominator details, missing-data handling, multiplicity decisions, and analysis methods. These details influence how confidently readers can connect a randomized design to a particular numerical estimate. The trial’s results are informative as pilot evidence, but the registry’s incomplete analytic reporting limits the strength and breadth of statistical conclusions.

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 the information recorded for this trial. The primary outcome is defined as change in cigarettes smoked per day, but the registry does not explain the detailed coding of the change or the method used to estimate the group contrast. The primary population note refers to missing Anabasine data, leaving the relationship between that missing biomarker information and the primary cigarette-use denominator unclear.

The record does not report how randomization was generated or concealed, and masking is listed as none. Open-label assignment can affect behavior or reporting, particularly for self-reported cigarette consumption and e-cigarette use. This is a potential design concern, not evidence that reporting was biased in a particular direction. The registry also does not report an objective validation procedure for the primary self-reported measure.

The enrolled cohort was small, and the numbers contributing to some outcomes differ. The record does not provide a complete participant flow, reasons for missing observations, or sensitivity analyses. It also does not report the prespecified statistical analysis plan, baseline adjustment, or population definition for analysis. These omissions make it difficult to assess robustness.

The study is described as a pilot, so its findings are preliminary by design. Its follow-up periods extend to 12 weeks for the immediate-start group and 20 weeks for the waitlist-control group, but the registry does not report longer-term comparative outcomes. The evidence therefore does not establish durability beyond the reported follow-up or broad generalizability beyond the population and setting described.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Switching Individuals in Treatment for Opioid Use Disorder Who Smoke Cigarettes to the SREC — NCT05881304.
• Registry record last updated 2026-10-21; status last verified 2026-09.
• Results first posted 2026-10-21.
• 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 describes a completed randomized, open-label, parallel pilot trial of immediate versus delayed SREC provision among adults stable on buprenorphine treatment for opioid use disorder who smoked cigarettes daily. Enrollment was 41. The primary outcome was change in cigarettes smoked per day from baseline to Week 8.

The posted primary comparison reports a mean difference of -6.7, with a confidence interval from -10.64 to -2.759 and an unadjusted p-value of <0.001. Secondary outcomes cover e-cigarette use, breath carbon monoxide, and study completion, among other registered measures. The record does not report a detailed analysis plan, multiplicity strategy, or complete missing-data handling. The primary result is therefore best understood as a preliminary group-level finding with uncertainty and reporting limitations.