Study of the Effects of Motivational Enhancement Therapy on Alcohol Use in Chronic Hepatitis C Patients: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of the Effects of Motivational Enhancement Therapy on Alcohol Use in Chronic Hepatitis C Patients (NCT00596960), a randomized na study. The primary outcome is The Number of Alcohol Drinks Per Week (as Measured by the Time Line Follow Back Procedure) at the 6 Month Follow-up..

2. Clinical Question

3. Trial Design

This was a randomized, single-masked, parallel-group behavioral trial of motivational enhancement therapy and health education. It was registered as completed, with enrollment of 139. The recorded start was 2008-11 and the primary completion was 2012-06. The registry lists the phase as NA, which is consistent with the behavioral nature of the interventions rather than a drug-phase description. The sponsor was the US Department of Veterans Affairs.

The study concerned veterans with chronic hepatitis C who were drinking and had alcohol disorders. Its stated purpose was to determine whether MET reduced alcohol use in this population. The registry’s hypothesis concerned both weekly standard drinks and the percentage of days abstinent. The primary outcome posted for the six-month follow-up is the number of alcohol drinks per week, measured by the Time Line Follow Back procedure. A secondary outcome is heavy drinking days, defined in the outcome title as days with greater than or equal to 4 drinks.

Primary outcome results are reported for Arm 1 and Arm 2, with 70 and 68 participants, respectively. The control code corresponds to Arm 1. Although the registry also names the two intervention descriptions, it does not explicitly connect those descriptions to the outcome arm labels. The reported arm comparison can therefore be described numerically, but the registry record does not support an unambiguous assignment of each numerical result to MET or health education.

The record does not report the original sample-size justification, the trial’s planned statistical analysis, or who was masked. It lists three outcome measures and zero posted analyses for the primary outcome, while one secondary outcome is posted without reported analyses. These omissions limit assessment of the intended analysis and of how the reported summaries relate to the full protocol.

4. Participant Flow and Accounting

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

Overall Study

Reasons for not completing this period:

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 The Number of Alcohol Drinks Per Week (as Measured by the Time Line Follow Back Procedure) at the 6 Month Follow-up., measured over 6-months.

The primary endpoint is the mean number of standard alcohol drinks per week at the six-month follow-up. The registry says drinking was measured with the Time Line Follow Back procedure and describes the standard-drink definition as 14 oz. of alcohol or 12 oz of regular beer, 5 oz of regular wine, or 1.5 oz of distilled spirits. The outcome description also says that drinking was measured for a 30 a day time frame at baseline, 3 months, and 6-months; the exact wording is not further clarified in the registry record.

Weekly drinks provide a continuous measure of alcohol consumption, so the groups can be described by their means and standard deviations, and compared by a mean difference. A lower group mean would represent fewer drinks on average during the measurement period, but a group mean does not describe every participant’s drinking pattern. It can be affected by large values, especially when the standard deviation is substantial relative to the mean.

The six-month measure addresses the study’s stated aim of assessing alcohol use after the interventions. The record’s hypothesis also refers to percentage of days abstinent, but that result is not among the posted outcomes. The distinction matters: weekly consumption and abstinent-day percentage capture related but not identical features of drinking, and one cannot stand in for the other.

7. Results Posted in the Registry

• Arm 2: mean 21.41 versus 14.88 on control; difference 6.53 (95% CI -3.04 to 16.10), standardized effect d = 0.23; z-test p = 0.181.

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.

Heavy Drinking Days (Greater or Equal to 4 Drinks)

• 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:
  • Arm 2: mean 7.38 versus 5.10 on control; difference 2.28 (95% CI -0.67 to 5.23), standardized effect d = 0.26; z-test p = 0.130.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 2 and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary endpoint is heavy drinking days, defined in its title as days with greater than or equal to 4 drinks. At six months, its group means are higher in Arm 2 than Arm 1, and its reported mean difference is positive. The confidence interval includes zero, and its unadjusted p-value is 0.13. Thus, as with the primary endpoint, the point estimate has a direction but the posted comparison does not precisely establish a difference in that direction. The arm descriptions are not explicitly connected to the result labels, so this numerical pattern cannot be assigned confidently to MET versus health education.

The secondary pattern is broadly consistent with the primary numerical pattern: both posted mean comparisons are higher in Arm 2 than Arm 1, and both intervals include zero. This similarity is descriptive, not proof that the endpoints provide independent confirmation. Weekly drinks and heavy drinking days measure related aspects of alcohol use, and their participant-level values are likely to be connected, although the registry does not report their correlation or joint analysis. The secondary result therefore adds context, but it does not remove the uncertainty in the primary result.

Unadjusted secondary findings generally carry less inferential weight when a study considers multiple outcomes or comparisons. Testing several outcomes can increase the chance that at least one appears notable by chance. A prespecified hierarchy or multiplicity adjustment can address that issue, but the registry record does not report such a plan or adjustment. The secondary outcome is not a substitute for the primary endpoint, and its result should be treated as supportive description rather than decisive evidence. The record also names a hypothesis about percentage of days abstinent, but does not post that outcome among the available results.

The record lists one secondary outcome and no reported analyses for it. It does not explain whether the outcome was prespecified in the same form, whether other outcomes were assessed but not posted, or how missing measurements were handled. Those uncertainties make the overall secondary evidence incomplete. Interpretation should rest on the posted estimates and their intervals, without elevating an unadjusted secondary result above the primary comparison.

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

• Heavy Drinking Days (Greater or Equal to 4 Drinks)

9. Statistical Interpretation

10. Statistical Methods Explained

The registry posts continuous outcomes as group means with standard deviations. A mean is the arithmetic average of the observed values in a group. A standard deviation describes how dispersed those values are around the mean: larger values indicate more variability among participants. Means can be useful for summarizing consumption, but they can conceal highly varied patterns, particularly when some observations are far from the average. Here, the reported standard deviations are substantial relative to the means, so the averages should not be treated as descriptions of a typical individual’s drinking.

The primary comparison is a mean difference. It is stated as Arm 2 minus Arm 1, with Arm 1 designated as the control group. The estimate of 6.53 is therefore the posted difference in weekly drinks between those group means. A positive value indicates that the Arm 2 mean is higher than the Arm 1 mean; it does not, by itself, identify which named intervention produced either mean. The outcome record does not explicitly link its arm labels to the named intervention descriptions.

A confidence interval gives a range of values compatible with the data and the statistical procedure used to construct it. It conveys uncertainty in the estimated group difference, rather than showing the range of individual participants’ outcomes. If an interval contains zero, the data are compatible with no mean difference as well as with differences on either side of zero. The primary interval extends from -3.043 to 16.1, so it includes zero and allows both a negative and a positive contrast. This is one reason the point estimate should not be interpreted as a precise estimate of a directional effect.

The unadjusted p-value is 0.181. A p-value describes how unusual data at least as incompatible with a null hypothesis of no difference would be under the assumptions of the test. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of a difference. The registry does not report the trial’s original analysis plan or a model-based analysis. The displayed value is therefore best understood as an unadjusted comparison rather than as evidence about analyses that are not reported.

Why can variability matter?

When outcomes vary substantially among participants, a group mean may be estimated less precisely than it would be with less variability, all else equal. Large variation also makes it harder to distinguish a group difference from noise in a sample. Alcohol consumption can vary across people and over time; the registry’s summaries do not show the distribution of values, so the extent or shape of that variation cannot be assessed beyond the reported standard deviations. General statistical principle: skewed or unusually dispersed continuous data can make mean-based summaries less representative, and the registry does not report distribution checks or alternative analyses.

The secondary continuous endpoint, heavy drinking days, is summarized in the same general way: group means, standard deviations, a mean difference, an interval, and an unadjusted p-value. Its comparison also has an interval spanning zero. These are secondary results and should not be treated as independent confirmations of the primary endpoint. Their interpretation depends on the study’s outcome hierarchy, multiplicity plan, and analysis choices, none of which are reported in the registry record.

What does randomization contribute?

Random allocation is intended to create groups that are comparable on average at the time of assignment, including with respect to measured and unmeasured characteristics. It supports a causal comparison when allocation is implemented as intended, outcomes are ascertained appropriately, and participants are analyzed in a suitable way. The registry identifies the allocation as randomized, but does not report the sequence-generation method, allocation concealment, or the analysis population. Those details are not reported in the registry record, so the summaries alone cannot confirm how these safeguards were implemented.

The parallel model means participants were assigned to one group rather than being described as crossing between interventions. Single masking is recorded, but the registry does not identify who was masked. The record also does not report whether outcome assessment was masked or whether participants and intervention staff knew their assignment. These distinctions can matter for behavioral interventions and self-reported alcohol-use measures, but no specific masking arrangement can be inferred.

What remains unknown about the analysis?

The registry lists zero primary analyses and no reported analyses for the posted secondary outcome. It does not report adjustment for baseline values, covariates, missing outcomes, or repeated measurements. It also does not report whether the six-month result was based on all randomized participants, only participants with observed outcomes, or another analysis set. Enrollment was 139, while the primary result counts are 70 and 68; the reason for the difference is not reported in the registry record. These omissions prevent evaluation of attrition handling and adherence to an analysis plan.

General statistical principle: in a randomized trial, an intention-to-treat analysis retains participants in the groups to which they were assigned, while other analysis populations may exclude or reclassify some participants. Missing outcome data can weaken the comparability created by randomization if the likelihood of missingness is related to assignment or outcome. No analysis population or missing-data approach is reported, so the summaries cannot be classified as intention-to-treat or otherwise.

The record reports no discrepancy between its comparison and the recalculated unadjusted result. That does not resolve the missing methodological details; it only means the posted comparison and the simple recalculation are not flagged as inconsistent. The statistical interpretation should remain anchored to the reported estimates and their uncertainty, rather than to assumptions about an undocumented plan.

11. Confidence Intervals and Precision

The primary mean difference is 6.53 drinks per week for Arm 2 compared with Arm 1. Its 95% confidence interval runs from -3.043 to 16.1. The interval includes zero, so the posted data are compatible with no mean difference. They are also compatible with a difference in either direction. The point estimate alone gives a single value, while the interval makes clear that the estimate is not precise enough to narrow the plausible contrast to one direction.

The interval is not a range expected to contain most participants’ drinking values. It concerns uncertainty in the group mean difference. Individual variation is reflected more directly by the standard deviations, which are 27.94 for Arm 1 and 29.39 for Arm 2. Those values indicate considerable spread around the group means. Neither the confidence interval nor the standard deviations reveal the detailed distribution of participants’ outcomes.

The unadjusted p-value of 0.181 is consistent with the interval’s inclusion of zero under the comparison’s statistical assumptions. It should not be read as proof of no effect, nor as a probability that the observed difference occurred by chance. The interval is more informative about the range of effect sizes compatible with the estimate, although its interpretation also depends on the unreported analysis details.

The registry record does not report an adjusted interval, a baseline-adjusted comparison, or a precision measure for the percentage of days abstinent mentioned in the study hypothesis. Arm-specific results also are not linked explicitly to the intervention descriptions. Consequently, the posted precision applies to the numerical comparison between the labeled groups, not to an unambiguous named-intervention contrast.

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, not total events. They are illustrations based on the observed effect, not the trial’s original design assumptions. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The planning effect is set to the stated fraction of the observed effect. The original trial’s sample-size justification and design assumptions are not reported in the registry record.

The 80% power column gives the estimated number of participants per arm for a design with an 80% chance of detecting the specified effect under the stated assumptions, if that effect is the true effect and the model assumptions hold. The 90% power column gives the corresponding per-arm number for a design with a 90% chance. Higher planned power generally requires more participants for the same target effect. The entries are shown for planning at 100%, 75%, and 50% of the observed effect. Smaller target effects need more participants because they are harder to distinguish from random variation.

For the primary outcome, the listed per-arm planning numbers rise as the targeted fraction of the observed effect gets smaller. The same relationship appears in the secondary outcome planning figures. These values depend on the assumptions above and should not be read as a reconstruction of the original trial plan. They are not observed power; observed power is not a useful substitute for interpreting the estimate and its confidence interval after a study has been completed. The trial’s own allocation and analysis details beyond randomization and equal outcome-arm counts are not described as planning assumptions in the registry record.

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 = 6.530; pooled standard deviation σ = 28.664.
2. n = 2 × (1.96 + 0.842)² × 28.664² / 6.530² = 302.5, rounded up to 303 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 <- 6.53                      # observed difference in means
sigma <- 28.6635066073468                     # 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(596960)
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 = 303 (80% power), 405 (90% power)
 75% of observed effect: n per arm = 538 (80% power), 720 (90% power)
 50% of observed effect: n per arm = 1,210 (80% power), 1,620 (90% power)
power.t.test: 303.4 
Simulated power at n = 303 per arm: 0.801 (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

Multiplicity arises when a trial evaluates multiple outcomes, time points, subgroup comparisons, or analyses. Even when each individual test uses a conventional significance threshold, considering many tests can increase the chance of at least one apparently notable result by chance. Methods such as a prespecified outcome hierarchy or a statistical adjustment can help control that risk. The registry names a primary endpoint and identifies a secondary endpoint, but does not report a multiplicity strategy or adjustment. It lists three outcome measures, while the posted results include the primary endpoint and one secondary endpoint. The status of the remaining outcome measure is not reported in the registry record.

The record does not report the original statistical analysis plan, planned covariate adjustments, subgroup analyses, interim analyses, or a prespecified hierarchy for interpreting outcomes. Those details should not be inferred from the reported p-values. The primary comparison is labeled unadjusted, and the secondary comparison is also unadjusted. Their p-values do not indicate whether analyses were selected before or after outcomes were examined.

Missing-data handling is also not reported. The registry gives an enrollment of 139 and primary outcome counts of 70 in Arm 1 and 68 in Arm 2, but does not explain why those counts differ from the enrollment figure or whether participants lacked six-month measurements. The reason for the difference is not reported in the registry record. It is also not reported whether the primary means include all randomized participants, whether imputation was used, or whether any sensitivity analysis examined the effect of missing outcomes.

Analysis populations are not described. The registry does not say whether results were analyzed according to assigned group, according to intervention received, or using another population. General statistical principle: excluding participants after randomization can undermine the balance created by random allocation if exclusions are related to group or outcome. Without the analysis population and missing-data approach, it is not possible to judge that risk from the posted summaries alone.

The study is recorded as single-masked, but who was masked is not reported. Allocation concealment, sequence generation, outcome-assessor masking, and methods for maintaining masking are also not reported in the registry record. These are methodological uncertainties rather than evidence that a particular safeguard failed. They limit the detail available for evaluating the trial’s conduct and the robustness of its outcome comparisons.

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

Serious events with the highest arm-level rate: alcohol intoxication (5.8%), liver failure (4.3%), gi distress (4.3%), psychiatric symptoms (2.9%), fracture (1.4%).

The serious adverse event counts are reported for groups with 70 and 69 participants at risk. Serious adverse events affected 7 participants in one group and 14 in the other. Other adverse events affected 0 participants in each group. These are counts and denominators, not estimates of whether an intervention caused an event. The registry’s serious-event at-risk counts do not exactly match the primary outcome counts, and the reason for that difference is not reported in the registry record.

The registry lists serious-event terms with percentages: Alcohol intoxication, 5.8%; Liver failure, 4.3%; GI distress, 4.3%; psychiatric symptoms, 2.9%; fracture, 1.4%; and chest pain, 1.4%. The record does not specify in this list how those terms are distributed between arms, whether participants could have more than one listed event, or the ascertainment period for each term. They should therefore be read as reported event descriptions, not as arm-specific comparative risks.

Deaths are not reported in the adverse-event information. No conclusion about comparative safety can be drawn from these counts alone. The registry does not report an inferential comparison of adverse events or attribution of events to an intervention.

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

The posted results describe six-month alcohol-use summaries for two randomized groups. The primary mean difference is 6.53 drinks per week, with an interval from -3.043 to 16.1 and an unadjusted p-value of 0.181. This estimate points toward a higher mean in Arm 2 than Arm 1, but the confidence interval includes zero and values on both sides. The data therefore do not provide a precise estimate of the direction or magnitude of the group difference.

This is not the same as demonstrating that the groups are equivalent. Equivalence requires a prespecified margin defining what differences would be considered sufficiently small, and an analysis designed to assess that margin. No equivalence margin or equivalence analysis is reported in the registry record. Similarly, failure to obtain a small p-value does not establish that an intervention has no effect. The estimate and its uncertainty are the central features of the posted comparison.

The registry’s research question is about MET compared with health education for veterans with chronic hepatitis C and alcohol disorders. However, the outcome results use Arm 1 and Arm 2, and the record does not explicitly link those labels to the intervention descriptions. It also does not post a result for percentage of days abstinent, although that measure appears in the stated hypothesis. Consequently, the posted outcomes do not fully answer every part of the stated research question.

The reported results do not establish what happened to every participant. Group means and standard deviations do not reveal individual changes, and no baseline-adjusted or repeated-measures analysis is reported. The registry record does not describe the analysis population or missing-data approach. The enrollment count also differs from the primary outcome counts, without an explanation. These limitations affect how confidently the observed summaries can be related to the randomized comparison.

The serious adverse event counts describe events recorded in groups at risk, but the available information does not establish causality or support a precise between-group safety comparison. Overall, the registry supports a cautious reading of the posted group summaries and their uncertainty, not a clinical recommendation or a definitive statement that either intervention is beneficial, ineffective, or equivalent.

17. Why This Trial Matters Statistically

This trial illustrates why a point estimate and its uncertainty need to be read together. The primary mean difference is positive, but its confidence interval includes zero and extends across values in both directions. A reader who focuses only on the point estimate could overstate the certainty of the result; a reader who focuses only on the p-value could incorrectly treat the result as proof of no difference. The interval gives a more direct account of how much uncertainty remains.

It also shows why variability matters for continuous behavioral outcomes. The standard deviations are large relative to the group means, indicating considerable variation in weekly drinking. That spread limits what can be inferred about individual experiences from group averages. It also helps explain why a modest observed contrast can be imprecisely estimated in a trial of this size, although the registry record does not provide the original design assumptions needed to assess that point against the planned target.

The registry’s planning illustrations show how the number of participants needed depends on the effect a future study aims to detect. Planning for a smaller fraction of the observed effect requires more participants per arm under the stated assumptions. Such illustrations can inform design thinking, but they are not the trial’s original sample-size justification and do not establish what power the completed trial had.

Finally, the record demonstrates that interpretation depends on transparent reporting as well as numerical results. Arm-to-intervention mapping, analysis populations, missing-data handling, the multiplicity plan, and the original statistical analysis are not reported. Those omissions do not invalidate the posted estimates, but they constrain how fully researchers can evaluate their robustness and relation to the stated hypothesis.

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 specific to this record constrain interpretation. First, the outcome results are reported under Arm 1 and Arm 2, but the registry does not explicitly connect those labels to the MET and health education descriptions. The control code is associated with Arm 1, yet this does not resolve the mapping between the numerical arm results and named interventions. The arm comparison can be described, but a named-intervention interpretation remains uncertain.

Second, the stated hypothesis includes both weekly drinks and percentage of days abstinent, while the posted outcomes include weekly drinks and heavy drinking days. A percentage-of-days-abstinent result is not reported in the registry record. The posted endpoints therefore do not cover every element of the stated hypothesis. The registry lists three outcome measures but provides only the primary outcome and one secondary outcome in the results.

Third, the trial enrolled 139 participants, while primary outcome results report 70 and 68 participants in the two arms. The reason for this difference is not reported in the registry record. The adverse-event groups at risk are 70 and 69, also differing from the primary outcome counts. The record does not explain these denominators or report how missing outcomes were handled. This makes it difficult to evaluate the completeness of follow-up and the analysis population.

Fourth, the registry does not report the original sample-size justification, the planned statistical analysis, a multiplicity strategy, or whether baseline drinking was accounted for. Although the trial is recorded as single-masked, the masked parties are not identified. The sequence-generation and allocation-concealment methods are also not reported. These absences leave important design and analysis details unresolved.

Finally, the primary outcome standard deviations indicate substantial variation, while the registry does not provide distributions or individual-level results. Group summaries cannot show the range of participant trajectories. These limitations are distinct from the uncertainty already expressed by the confidence interval and should be considered when interpreting the numerical estimates.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Study of the Effects of Motivational Enhancement Therapy on Alcohol Use in Chronic Hepatitis C Patients — NCT00596960.
• Registry record last updated 2014-11-28; status last verified 2014-11.
• Results first posted 2014-11-28.
• 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

NCT00596960 is a completed randomized, single-masked, parallel behavioral trial sponsored by the US Department of Veterans Affairs. It enrolled 139 participants and compared motivational enhancement therapy with health education for veterans with chronic hepatitis C and alcohol disorders. The recorded study dates are 2008-11 to primary completion in 2012-06.

The primary outcome was mean standard alcohol drinks per week at six months, measured using the Time Line Follow Back procedure. The posted mean difference for Arm 2 compared with control Arm 1 was 6.53, with a 95% confidence interval from -3.043 to 16.1 and an unadjusted p-value of 0.181. Heavy drinking days was the posted secondary outcome; its mean difference was 2.28, with a 95% confidence interval from -0.675 to 5.235 and an unadjusted p-value of 0.13.

The arm descriptions are not explicitly linked to the outcome labels. The record does not report the original analysis plan, sample-size justification, analysis population, missing-data approach, or multiplicity strategy. Serious adverse events affected 7 and 14 participants in groups with 70 and 69 at risk, respectively; the registry does not report deaths.