Penn State TXT2Quit Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Penn State TXT2Quit Study (NCT02367391), a randomized na study. The primary outcome is Point Prevalence of 7-day Tobacco Abstinence Biochemically Validated by Exhaled CO < 10ppm at Visit 3 (12 Weeks After Target Quit Day).

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group pilot trial, with single masking recorded in the registry. The sponsor was Milton S. Hershey Medical Center. The study began in 2015-01, had primary completion in 2015-10, and is recorded as completed. Its phase is listed as NA. The registry enrollment was 152.

The two behavioral interventions were Motivational Text Messages and Control. The intervention was intended as an adjunct to varenicline in primary care, according to the study title and brief description. The record does not give fuller descriptions of either arm. It also does not specify who was masked, how randomization was implemented, whether allocation was concealed, or the planned duration and frequency of messaging. Those design details are not reported in the registry record.

The main outcome was a binary count: participants with point-prevalence 7-day tobacco abstinence at 12 weeks after the target quit day, biochemically validated by exhaled CO below 10ppm at Visit 3. The reported arm counts were 23 among 74 in the motivational-text arm and 23 among 76 in control. The record lists three secondary outcomes: continuous lapse-free abstinence from 4 weeks to 12 weeks, time in days to relapse after the target quit day, and total score on the Positive Smoking Cessation Activities Measure. The outcome records give different analysis counts for some secondary measures; the reasons are not reported.

The brief description says the study evaluated feasibility and short-term cessation outcomes. It does not provide a specific feasibility outcome among the posted results summarized in the record. The original sample-size rationale, the intended primary analysis model, the analysis population, and any planned interim analyses are not reported in the registry record. Therefore, the posted comparison should be read as the available outcome summary, not as a complete account of every protocol decision.

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 Point Prevalence of 7-day Tobacco Abstinence Biochemically Validated by Exhaled CO < 10ppm at Visit 3 (12 Weeks After Target Quit Day), measured over 12 weeks.

The primary endpoint counted participants with point-prevalence tobacco abstinence at 12 weeks after the target quit day. To meet the recorded definition, a participant had to report no tobacco use during the previous 7 days and have abstinence biochemically validated by exhaled carbon monoxide below 10ppm at Visit 3. The outcome was therefore reported as a count of participants, with each arm’s count interpreted in relation to its analysis group.

In general, point-prevalence abstinence captures a defined recent period rather than continuous abstinence throughout the entire follow-up. It can provide a snapshot of recent smoking status at a specified visit. Biochemical validation is used in general to supplement self-report with an objective measure related to recent smoking. The registry’s definition ties this validation to the stated exhaled CO cutoff and Visit 3; additional collection or adjudication procedures are not reported in the registry record.

This endpoint differs from the listed continuous lapse-free abstinence outcome, which covers the interval from 4 weeks to 12 weeks, and from time to relapse. Those outcomes address other aspects of cessation over follow-up. The primary count alone does not describe abstinence at every point in the study, the timing of lapses, or participants’ experience of the intervention. Its interpretation is specific to the recorded 7-day period and visit-based validation.

7. Results Posted in the Registry

• Motivational Text Messages: 31.1% (23/74) versus 30.3% (23/76) on control; risk difference 0.8 percentage points (95% CI -13.9 to 15.6), risk ratio 1.03 (0.63–1.66); unadjusted two-proportion z-test p = 0.914.

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.

Continuous Lapse-free Tobacco Abstinence From 4 Weeks to 12 Weeks, Biochemically Validated at Visit 2 and Visit 3.

• 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:
  • Motivational Text Messages: 8.1% (6/74) versus 11.8% (9/76) on control; risk difference -3.7 percentage points (95% CI -13.3 to 5.8), risk ratio 0.68 (0.26–1.83); unadjusted two-proportion z-test p = 0.446.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Motivational Text Messages and the control. The interval gives the range of effects that remain compatible with the data.

Time (in Days) to Relapse After the Target Quit Day

• 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:
  • Motivational Text Messages: mean 16.00 versus 16.50 on control; difference -0.50 (95% CI -10.02 to 9.02), standardized effect d = -0.02; z-test p = 0.918.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Motivational Text Messages and the control. The interval gives the range of effects that remain compatible with the data.

Total Score on the Positive Smoking Cessation Activities Measure

• 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:
  • Motivational Text Messages: mean 10.50 versus 9.10 on control; difference 1.40 (95% CI -0.02 to 2.82), standardized effect d = 0.35; z-test p = 0.053.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Motivational Text Messages and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes address different features of cessation and participant activity, so their pattern is not a single unified measure. Continuous lapse-free abstinence extends across a longer interval than the primary point-prevalence endpoint. Time to relapse concerns when relapse occurs, while the activity measure concerns reported cessation-related activities. The registry summaries therefore complement the primary endpoint rather than repeat it.

Across these measures, the directions are mixed: the count for continuous lapse-free abstinence is lower in the motivational-text arm, the mean activity score is higher, and the mean time to relapse is similar. That pattern does not supply a consistent secondary signal that can be substituted for the primary outcome. Nor does an outcome’s direction alone establish that the arms differ; uncertainty and the outcome definition matter. Each comparison has its own interval, measurement scale, and available analysis count.

These comparisons carry less weight than a prespecified primary result when their planned status and analysis procedures are not documented. The registry lists the secondary outcomes but does not report analyses for them. It does not say whether these comparisons were confirmatory, whether multiplicity was addressed, or how missing measurements were handled. When several outcomes are examined, chance alone can produce apparently notable findings; in general, multiplicity procedures help control the risk of overstating such signals. Without a reported strategy, secondary findings are most appropriately treated as descriptive and hypothesis-generating.

The secondary outcomes do not overturn the primary result. Instead, they show why an endpoint-specific interpretation is important: recent abstinence, sustained lapse-free abstinence, relapse timing, and activity scores are related but not interchangeable. The posted results can motivate questions for future research, but the registry summary alone does not establish which outcome should be considered most important beyond its designation of the primary endpoint.

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

• Continuous Lapse-free Tobacco Abstinence From 4 Weeks to 12 Weeks, Biochemically Validated at Visit 2 and Visit 3.
• Time (in Days) to Relapse After the Target Quit Day
• Total Score on the Positive Smoking Cessation Activities Measure

9. Statistical Interpretation

10. Statistical Methods Explained

What does the risk difference express?

For a binary outcome, a risk is the proportion of participants in an arm who meet the outcome definition. A risk difference expresses the contrast between the arms on that proportion scale. The reported risk difference of 0.008 compares motivational text messages with control for the primary abstinence outcome. A value near zero indicates a small estimated contrast on this scale, while a positive or negative value indicates the direction of the comparison as coded. The estimate does not by itself show how certain that contrast is; the confidence interval supplies information about its precision.

The record also gives a risk ratio and an odds ratio. A risk ratio compares the two arm risks as a ratio, while an odds ratio compares the odds of the outcome. These measures use different scales and can appear numerically different even when they summarize the same underlying binary results. They should be interpreted with their confidence intervals and the event definition, rather than as separate replications of the finding.

What does a confidence interval contribute?

In general, a confidence interval describes the range of effect estimates reasonably compatible with the data under the statistical method used. It reflects sampling uncertainty, not all sources of uncertainty. It does not account automatically for bias, incomplete outcome ascertainment, differences in how participants were treated, or unreported analytic choices. For the primary risk difference, the interval extends from -0.139 to 0.156. Its span conveys that the data are compatible with contrasts on either side of zero, rather than tightly identifying one value.

The registry record gives the primary unadjusted p-value as 0.914. In general, a p-value assesses how unusual data at least as incompatible with a null model would be if that model and the test assumptions were correct. It is not a measure of effect size, the chance that an intervention has no effect, or the probability that results will replicate. The p-value and interval answer related but different questions; reading them together keeps attention on both direction and precision.

How should the secondary measures be understood?

The secondary binary endpoint counts participants with continuous lapse-free tobacco abstinence from 4 weeks to 12 weeks, biochemically validated at Visit 2 and Visit 3. The mean difference is used for the two continuous measures: time in days to relapse and total score on the Positive Smoking Cessation Activities Measure. A mean difference compares arm averages in the original measurement units. For time to relapse, the record reports a mean and standard deviation in days. In general, a standard deviation describes variation among participant measurements; it is not the uncertainty around the mean difference. The confidence interval around the difference addresses uncertainty in the comparison.

Time until an event can sometimes be analyzed with methods that use the timing of events and account for incomplete follow-up. The registry record reports a mean difference and standard deviations for time to relapse, but does not report a time-to-event analysis or explain how observations without a recorded relapse were handled. The original analysis method is not reported in the registry record. Consequently, the posted summary cannot establish whether a survival-analysis approach, censoring procedure, or other adjustment was used.

Why does over-dispersion matter in general?

For count outcomes, a model may assume a particular relationship between the average count and its variability. Over-dispersion means that observed variability exceeds what that model expects. If present but ignored, standard errors and confidence intervals can be too narrow, making evidence appear more precise than it is. This is a general statistical issue for count models, not a reported feature of this trial. The primary outcome is recorded as a count of participants meeting a binary abstinence definition, and the registry record does not report an over-dispersion assessment or model-based analysis.

What is not specified about the analyses?

The registry record lists zero analyses and no reported analyses for the secondary outcomes. It includes unadjusted comparisons, but does not report the original statistical analysis plan, adjustments for baseline variables, the handling of missing outcome data, or the population used for analysis. It also does not report whether any alternative outcome definitions or sensitivity analyses were prespecified. These omissions matter because the interpretation of a numerical estimate depends partly on how the analysis was planned and conducted. The record supports describing the posted estimates and their stated uncertainty, but not reconstructing unreported analysis decisions.

11. Confidence Intervals and Precision

Precision concerns how narrowly the available data locate an effect, and the primary confidence interval indicates substantial uncertainty around the risk-difference estimate. The reported estimate is 0.008, with a 95% confidence interval from -0.139 to 0.156. The interval crosses zero, so the data are compatible with a small contrast in either direction as well as with larger contrasts within its limits. The interval is not evidence that all values in that range are equally likely; it expresses uncertainty under the statistical procedure.

The risk ratio is 1.027, with a 95% confidence interval from 0.635 to 1.662. The odds ratio is 1.039, with a 95% confidence interval from 0.519 to 2.081. These intervals also span their respective no-association values. Because ratio measures operate on a different scale from a risk difference, their intervals should be interpreted on their own terms, not compared by their numerical widths.

In general, intervals become more precise when information increases, although the amount of improvement depends on event frequency, variation, and analysis method. This trial’s primary outcome counts and arm sizes give context for why the estimate should not be treated as definitive. Precision is distinct from validity: a narrow interval would not remove possible bias, and a wide interval does not prove that an effect is absent. The registry record does not report the original precision target or a prespecified difference that the study was designed to rule in or rule out.

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 entries are illustrations based on the observed effect, not the original design assumptions for the trial. For binary and continuous outcomes, the displayed figures are participants per arm. For the time-to-event planning entries, figures are total events, as specified in the registry record’s planning assumptions. Thus a number in that time-to-event display is not a participant count per arm.

The calculations use a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. Each row considers detecting the stated fraction of the observed effect. The columns for 80% and 90% power describe, in plain language, the number of participants per arm expected to give the study a respective 80% or 90% chance of detecting the specified effect under those assumptions, if that effect is real. Power is not a guarantee that a result will be statistically significant, and the actual probability depends on the assumptions being appropriate.

Smaller effects require more participants to detect with the same planned power and significance level. For the primary endpoint, the planning entries range from 49,895 participants per arm for 80% power at 100% of the observed effect to 198,837 participants per arm for 80% power at 50% of the observed effect. The corresponding 90% power entries are 66,795 and 266,185. These are planning illustrations, not enrollment goals reported for this pilot and not observed power. The trial’s own original sample-size justification is not reported in the registry record.

Planning from an observed effect can be unstable, especially when a pilot estimate is imprecise. A future study might choose a meaningful target effect on substantive grounds rather than assume that the pilot estimate will recur. The displayed curve and entries are therefore best read as sensitivity to the chosen effect size under stated assumptions, not as a recommendation about a definitive trial.

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 = 0.303; treatment proportion p₁ = 0.311; average p̄ = 0.307.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6521 = 1.2782.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6521 = 0.5488.
4. n = (1.2782 + 0.5488)² / (0.0082)² = 49,894.7, rounded up to 49,895 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 <- 0.302631578947368                          # control proportion
p1 <- 0.310810810810811                          # 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(2367391)
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 = 49,895 (80% power), 66,795 (90% power)
 75% of observed effect: n per arm = 88,538 (80% power), 118,526 (90% power)
 50% of observed effect: n per arm = 198,837 (80% power), 266,185 (90% power)
power.prop.test: 49894.7 
Simulated power at n = 49,895 per arm: 0.797 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry record identifies a primary endpoint and lists three secondary outcomes. It does not report a multiplicity plan, such as a hierarchy among outcomes or an adjustment to account for testing several comparisons. In general, examining multiple outcomes increases the chance that at least one comparison will appear noteworthy by chance. This does not make the outcomes unusable, but it lowers the weight that should be placed on isolated secondary p-values when no correction or prespecified hierarchy is reported.

The record lists zero analyses and contains no reported analyses for the secondary outcomes. It also does not describe a statistical analysis plan, baseline adjustment, subgroup analyses, sensitivity analyses, interim analyses, or a primary analysis population. The registry summaries include unadjusted comparisons, but they do not establish whether these were the only analyses conducted or whether they match a prespecified plan. The original trial analysis plan is not reported in the registry record.

Missing-data handling is also not reported. The primary arm summaries give analysis counts of 74 and 76. The continuous lapse-free abstinence summaries also use 74 and 76, while the activity-score summaries use 60 and 62. The record does not explain why the analysis counts differ, whether missing measurements were excluded, or how any missing outcomes were classified. For time to relapse, the summary reports means and standard deviations but does not explain how participants without a recorded relapse were treated.

These gaps limit assessment of possible attrition bias and reproducibility. In general, a comparison based only on participants with observed outcomes can be biased if the availability of outcome data is related to the outcome or differs meaningfully between arms. That possibility cannot be evaluated from the posted record alone. The numbers should therefore be read as registry-reported summaries, with the analysis population and missingness procedures left unresolved.

15. 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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: development of diabetes (1.4%), gallbladder surgery (1.3%), abdominal pain (1.3%).

The registry reports serious adverse events among 1 participant in the motivational-text arm, with 74 at risk, and 2 participants in control, with 76 at risk. These are counts of participants affected, as recorded; they do not provide event timing, duration, severity details beyond the serious classification, or an assessment of whether an event was related to the intervention. Deaths are not reported in the registry record.

The record also lists the serious adverse event terms Development of Diabetes at 1.4%, Gallbladder Surgery at 1.3%, and Abdominal Pain at 1.3%. It does not identify an arm for these term percentages in the adverse-event summary, so they should not be attributed to a particular group. The arm summaries list 39 participants affected by other adverse events in the motivational-text arm and 33 in control; further detail about those events is not reported in the registry record.

In general, adverse-event counts describe what was recorded during a study, not necessarily what was caused by a treatment. Small group counts provide limited information about uncommon harms, and comparisons of these counts do not establish a causal safety difference. The record does not report event-collection methods, a safety analysis plan, or causality assessments.

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

The primary result describes the number of participants in each randomized arm who met the recorded 7-day, biochemically validated abstinence definition at 12 weeks. The observed counts were 23 in each arm, and the reported risk difference was close to zero. However, the confidence interval is broad and includes contrasts in both directions. The result is therefore an uncertain estimate, not proof that the arms have identical outcomes.

It also does not establish that motivational text messages are effective or ineffective. A nonsignificant unadjusted p-value does not prove no effect, just as an estimate on one side of zero does not prove benefit. The record does not give a clinically important threshold, an equivalence margin, or the original sample-size rationale. Without those, the analysis cannot establish that any remaining difference is too small to matter.

The study is described as a pilot focused on feasibility and short-term outcomes, but the posted primary result concerns abstinence at 12 weeks. The registry summary does not give detailed feasibility findings, intervention engagement, or implementation measures. The observed endpoint is also specific to recent abstinence at one visit; it does not establish sustained abstinence across the full follow-up or predict longer-term outcomes.

The result should be understood within this trial’s setting: motivational messages as an adjunct to varenicline in primary care, compared with a control whose details are not reported. The registry record does not provide enough information to determine how the result would generalize to other populations, message programs, or clinical contexts. It is a description of the posted trial data and their precision, not medical advice or a treatment recommendation.

17. Why This Trial Matters Statistically

This trial is statistically instructive because its primary endpoint is easy to summarize as counts, but the comparison still requires attention to denominators and uncertainty. Equal observed event counts do not by themselves imply equal arm risks when arm sizes differ. The risk difference and its confidence interval offer a more complete view than the counts alone, while the ratio measures express the comparison on alternative scales.

The result also illustrates the distinction between absence of strong evidence for a difference and evidence that two approaches are equivalent. A wide interval can contain both potentially important contrasts and values near no difference. A small pilot can be useful for describing procedures and generating estimates, yet it may not deliver precise comparative evidence. The registry record does not report a design target that would resolve that uncertainty.

The secondary outcomes underscore why outcome definitions and analysis plans matter. Point-prevalence abstinence, continuous lapse-free abstinence, relapse timing, and activity scores are related but not interchangeable. Several outcomes create opportunities for selective emphasis, so prespecification and multiplicity handling are important for confirmatory interpretation. Those procedures are not reported in this record.

Finally, the planning illustrations make clear how strongly sample-size requirements depend on the effect chosen for detection. They are useful for understanding design trade-offs under explicit assumptions, but they are not a substitute for the trial’s original rationale and do not measure the power observed after completion. The study offers a practical example of interpreting effect estimates, confidence intervals, secondary outcomes, and planning assumptions without overclaiming from a pilot result.

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.

The registry record leaves several trial-specific details unresolved. It does not describe the control condition beyond its label, the messaging schedule, intervention adherence, the exact randomization procedure, or who was masked. These omissions make it difficult to assess how the intervention was delivered and how closely the contrast matches other settings.

The primary comparison has considerable uncertainty, and the original sample-size justification is not reported. The posted planning illustrations use the observed effect and stated assumptions; they do not show what effect the trial was designed to detect. The record does not state a minimally important difference or an equivalence margin. Consequently, the primary result cannot settle whether a clinically meaningful contrast was ruled out.

Analysis details are limited. The registry lists zero analyses and no reported secondary analyses. It does not specify the analysis population, missing-data procedures, covariate adjustment, sensitivity analyses, interim monitoring, or multiplicity strategy. The activity-score analysis counts are smaller than those for the primary endpoint, but the reason is not reported. The handling of participants without a recorded relapse is also unclear.

There is no detailed participant flow or baseline description in the record summarized for these results. Thus, the extent to which participants were retained and the comparability of groups at baseline cannot be assessed from this information. The safety summary gives small serious-event counts but not event relationships or collection methods. Finally, the study focuses on short-term outcomes through 12 weeks; longer-term outcomes are not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Penn State TXT2Quit Study — NCT02367391.
• Registry record last updated 2017-06-15; status last verified 2017-05.
• Results first posted 2017-03-08.
• 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

NCT02367391, the Penn State TXT2Quit Study, was a completed randomized, single-masked, parallel pilot trial sponsored by Milton S. Hershey Medical Center. It enrolled 152 participants and evaluated motivational text messages as an adjunct to varenicline in primary care, compared with a behavioral control.

The primary outcome was biochemically validated 7-day tobacco abstinence at 12 weeks after the target quit day. There were 23 participants meeting the endpoint in each arm. The reported risk difference was 0.008, with a 95% confidence interval from -0.139 to 0.156 and an unadjusted p-value of 0.914. The interval indicates substantial uncertainty about the contrast.

The registry also lists secondary outcomes for continuous lapse-free abstinence, time to relapse, and cessation-activity score. Analysis plans, missing-data procedures, multiplicity handling, and the original sample-size justification are not reported in the registry record. The posted summaries should therefore be interpreted as descriptive estimates with important analytic details unresolved.