Striatal Effective Connectivity to Predict Treatment Response in Cocaine Misuse: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Striatal Effective Connectivity to Predict Treatment Response in Cocaine Misuse (NCT02080819), a randomized phase 2 study. The primary outcome is Cocaine Treatment Outcome.

2. Clinical Question

3. Trial Design

The registry record describes a phase 2, randomized, double-masked, parallel trial. It lists 131 participants as enrolled and gives the status as completed. The listed study dates are a start in 2014-02 and primary completion on 2017-01-21. Cocaine dependence is the recorded condition, and Virginia Commonwealth University is the sponsor.

Three groups appear in the outcome information: healthy control, placebo, and medication. The healthy-control group is described as non drug using; placebo and medication are each described as BID for 7 weeks. The medication is levodopa/carbidopa 400/100 BID. Although the trial is identified as randomized and double-masked, details of how allocation and masking applied to each group are not reported in the registry record. The randomization procedure, allocation ratio, and specific masking arrangements are also not reported.

The primary outcome has summaries for 38 healthy controls, 9 placebo participants, and 11 medication participants. The record does not explain how these outcome group sizes relate to the total enrollment of 131, or whether they represent all enrolled participants, a particular analysis population, or participants with complete outcome data. The primary outcome timeframe is baseline to 12 weeks, whereas the intervention descriptions specify 7 weeks of treatment. Further details about outcome assessment timing are not reported.

The study description proposes investigating brain connectivity in the mechanism of response to dopaminergic medications. However, the posted primary outcome concerns positive urine drug screens, and no secondary outcomes or statistical analyses are posted. The registry record does not provide a fuller protocol description, a participant flow account, or details of follow-up beyond the stated outcome timeframe.

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 Cocaine Treatment Outcome, measured over Baseline to 12 weeks.

The primary outcome is titled “Cocaine Treatment Outcome.” It is described as a treatment effectiveness score based on the number of positive urine drug screens, with the timeframe stated as baseline to 12 weeks. The reported measure is a mean, with standard deviation as its measure of spread, and the unit is positive drug screens.

As a general statistical point, an outcome based on urine drug screens can represent an objective measurement of drug-screen results during a specified period. A count-based outcome may summarize repeated observations as a single score, but the registry record does not describe the testing schedule, the exact scoring rules, or how the baseline-to-12-week period was converted into each participant’s score. Those details are not reported in the registry record.

The posted outcome summaries give a mean of 13.0 and standard deviation of 9 for the medication group, and a mean of 14.0 and standard deviation of 15 for placebo. Healthy controls have a mean of 0.0 and standard deviation of 0.0. The posted comparison is medication versus healthy control, rather than medication versus placebo. The record does not explain the use of healthy controls as the comparator for the posted treatment contrast.

The study description emphasizes brain connectivity as a potential predictor of response, but the primary outcome itself is not a reported connectivity measure. Connectivity results, prediction performance, and a direct account of how the primary outcome was linked to connectivity are not reported in the registry record.

7. Results Posted in the Registry

• Medication: mean 13.00 versus 0.00 on control; difference 13.00 (95% CI 7.68 to 18.32), standardized effect d = 3.13; z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous and summarized by a mean and standard deviation. In general, a mean describes the arithmetic average of the recorded scores, while a standard deviation describes how dispersed individual scores are around that average. These summaries are descriptive: they do not show the shape of the score distribution, the presence of outliers, or how repeated urine-screen observations were assembled into a participant-level score. Those details are not reported in the registry record.

What does the mean difference represent?

The posted comparison reports a mean difference for medication versus healthy control. The medication mean is 13.0 and the healthy-control mean is 0.0; the reported difference is 13.0. The estimate is an unadjusted group contrast as presented in the record, not a contrast against placebo. In general, a mean difference expresses the separation between group averages in the outcome’s original units. Its interpretation depends on how groups were formed, how the measure was collected, and which population the analysis represents. The registry record does not provide an adjusted model, covariates, or an analysis-population definition.

What does a confidence interval add?

A confidence interval describes uncertainty around an estimate under the assumptions of the statistical procedure used. It communicates a range of estimates compatible with the data and method, rather than a guarantee about the true effect. The posted interval for the medication-versus-healthy-control mean difference runs from 7.681 to 18.32. The record does not name the procedure used to construct this interval, so its assumptions cannot be checked from the posted information alone.

How should the p-value be read?

The unadjusted p-value is <0.001. As a general concept, a p-value is calculated under a null hypothesis and a statistical model; it indicates how unusual data at least as incompatible with that null would be if the model and null were appropriate. It is not the probability that the null is true, and it does not measure the size or importance of a difference. The test, model, and any covariate adjustment are not reported in the registry record. The word “unadjusted” identifies the posted p-value as not adjusted for multiplicity, but does not establish what other modeling choices were made.

What is a standardized effect?

The comparison also reports a standardized effect size of 3.131. In general, standardization expresses a difference in relation to variability, so the result is not in the original outcome units. The record also reports a pooled standard deviation of 4.151 for this contrast. The healthy-control group’s mean and standard deviation are 0.0 and 0.0, respectively. These unusual features of the contrast warrant reading the standardized value in context rather than treating it as an independent confirmation of the outcome. The registry record does not explain how the pooled variability was chosen or provide the calculation method.

Why can over-dispersion matter?

As a general statistical point, over-dispersion occurs when observed variability is greater than a model expects. It can make standard errors too small and confidence intervals too narrow if a model fails to account for it. A count-based outcome such as positive drug screens may have distributional features that differ from a simple normal model, but the registry record does not report a distributional assessment, an over-dispersion check, or the model used. No conclusion about over-dispersion can be drawn from the posted summaries alone.

What remains unknown about the analysis?

The record lists one outcome measure and no posted analyses. It does not report whether the outcome analysis was prespecified, which test or model was used, whether there were baseline adjustments, how missing observations were handled, or whether the outcome was analyzed under an intention-to-treat or another population definition. It also does not report checks of model assumptions, treatment adherence, or sensitivity analyses. These are not details that can be reconstructed from group means and standard deviations.

The comparison values are presented as a simple, unadjusted contrast, but the registry record does not provide enough methods detail to characterize the sponsor’s full analysis. General statistical explanations above describe what these common summaries mean; they do not establish which procedures were used in this trial. Interpretation should remain anchored to the posted groups, outcome definition, and explicit limits of the record.

10. Confidence Intervals and Precision

The posted medication-versus-healthy-control mean difference is 13.0, with a confidence interval from 7.681 to 18.32. The interval describes uncertainty in this particular contrast, subject to the method used to construct it. In general, a narrower interval indicates greater precision for the estimated quantity, while a wider interval indicates more uncertainty. The registry record does not identify the interval method or provide the underlying participant-level data, so the interval’s assumptions cannot be independently assessed from the posted information.

The interval concerns medication versus healthy control, not medication versus placebo. That distinction matters as much for precision as for interpretation: uncertainty around one comparison does not provide an interval for a different comparison. The placebo group’s mean and standard deviation are posted, but no inferential contrast involving placebo is reported.

The outcome group sizes are 11 for medication, 9 for placebo, and 38 for healthy control. The medication group’s standard deviation is 9, the placebo group’s is 15, and the healthy-control group’s is 0.0. A zero spread in the healthy-control summary means the reported scores in that group have no variation in the posted summary, but the record does not explain the score distribution or its context. The small outcome-group counts, particularly for the treatment groups, limit how much can be learned about variability and the stability of the estimates from these summaries alone.

The total enrollment is 131, but the reason it differs from the group counts in the outcome summaries is not reported. No information is given about missing outcomes or the analysis population. Consequently, the interval’s precision for the reported contrast does not address potential uncertainty arising from participant inclusion, missing data, outcome construction, or the choice of comparator.

11. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total events. They are illustrations based on the observed medication-versus-healthy-control effect, with equal allocation between two arms, a two-sided significance level of 0.05, and a normal approximation. The assumed effect is set in turn to 100% of the observed effect, 75% of the observed effect, or 50% of the observed effect. These are planning assumptions for the illustration; the trial’s original sample-size assumptions are not reported in the registry record.

For planning at 100% of the observed effect, the figures are 2 participants per arm for 80% power and 3 participants per arm for 90% power. At 75% of the observed effect, the corresponding figures are 3 and 4 participants per arm. At 50% of the observed effect, they are 7 and 9 participants per arm. The 80% column describes the number per arm in the illustration when the calculation is designed for an 80% chance of detecting the assumed effect under its statistical assumptions. The 90% column describes the analogous calculation for a 90% chance.

Smaller effects are harder to distinguish from random variation, so planning for a smaller fraction of the observed effect requires more participants per arm in these calculations. The low illustrative counts depend on using a very large observed contrast between medication and healthy controls; they should not be taken as a recommendation or as evidence that the original trial was adequately sized. This is not observed power. It is a planning illustration, and the contrast on which it is based is not a medication-versus-placebo comparison.

12. How the Sample Size Is Derived

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

Formula

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

Worked calculation for this trial

1. Observed difference Δ = 13.000; pooled standard deviation σ = 4.151.
2. n = 2 × (1.96 + 0.842)² × 4.151² / 13.000² = 1.6, rounded up to 2 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 <- 13                      # observed difference in means
sigma <- 4.15139043612998                     # 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(2080819)
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 = 2 (80% power), 3 (90% power)
 75% of observed effect: n per arm = 3 (80% power), 4 (90% power)
 50% of observed effect: n per arm = 7 (80% power), 9 (90% power)
power.t.test: 2.9 
Simulated power at n = 2 per arm: 0.407 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry record lists one outcome measure and no posted secondary outcomes. It also reports no posted analyses. The unadjusted p-value for the medication-versus-healthy-control comparison is <0.001, but the record does not report whether the study examined additional outcomes or analyses that are not posted. It does not describe a multiplicity plan or adjustment procedure.

In general, multiplicity arises when several hypotheses are tested; the chance of at least one apparently notable result can increase as the number of tests grows. Adjustment methods can account for a defined set of tests, but the tests and any adjustment choices need to be specified to interpret such a procedure. Since the registry record does not report the analysis plan or a complete set of analyses, it is not possible to determine how multiplicity was handled beyond the p-value being labeled unadjusted.

Missing-data handling is also not reported. The record does not say whether all participants had an outcome measurement at baseline and 12 weeks, how incomplete urine-screen records were treated, or whether any imputation or sensitivity analysis was used. The outcome summaries cover 38 healthy controls, 9 placebo participants, and 11 medication participants, while total enrollment is 131. No participant flow or explanation of these counts is given, so the extent and consequences of missing outcome information cannot be assessed.

Likewise, no analysis population is identified. The record does not state whether results were based on all randomized participants, participants who began treatment, participants who completed treatment, or another defined group. It does not report adherence or exclusions from the outcome analysis. These omissions prevent a clear assessment of how the posted summaries relate to randomization and the enrolled population. The record does not describe a prespecified analysis plan, so whether the posted contrast was planned in advance is not reported in the registry record.

14. 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 2% reporting threshold.

The adverse-event summaries list 38 healthy controls, 9 placebo participants, and 11 medication participants at risk. For each of these groups, the posted serious adverse event count is 0, the other adverse event count is 0, and deaths are 0. No serious adverse event terms are listed.

These are counts for the groups and at-risk numbers reported in the registry record. They do not establish that every enrolled participant was represented in these safety summaries: total enrollment is 131, and the record does not explain the relationship between enrollment and the listed group counts. The duration or method of adverse-event collection is not described beyond the registry’s safety entries.

In general, a zero count in a posted group means that no events of that category are recorded for that group in the reported summary. It does not, by itself, demonstrate that an event is impossible or establish comparative safety. The registry record does not provide a statistical comparison of safety between medication and placebo, definitions of the adverse-event categories, or further event ascertainment details.

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

The posted results describe the primary outcome as a mean number of positive urine drug screens from baseline to 12 weeks. The medication group’s mean is 13.0, and the healthy-control group’s mean is 0.0. The reported mean difference is 13.0, with a confidence interval from 7.681 to 18.32 and an unadjusted p-value of <0.001. These statistics describe the recorded medication-versus-healthy-control contrast and its reported uncertainty.

They do not provide a medication-versus-placebo treatment effect. Although the placebo group has a posted mean of 14.0 and standard deviation of 15, the registry record does not report an inferential comparison between placebo and medication. Healthy controls are described as non drug using, so this contrast should not be treated as an estimate of the difference between two randomized treatment options.

The trial’s description centers on brain connectivity as a possible predictor of treatment response. The posted primary outcome and comparison do not show whether connectivity predicts response. No connectivity measure, predictive model performance, or analysis linking connectivity to outcome is reported in the registry record. Nor does the record report a secondary outcome that would answer that predictive question.

In general, a statistically precise estimate of one group contrast answers only the question defined by that contrast. It cannot substitute for an unreported comparison, resolve uncertainty about participant inclusion, or establish the validity of a prediction model. Here, the group sizes in the outcome summaries are 38, 9, and 11, while enrollment is 131; the record does not explain the difference. Missing-data handling and the analysis population are not reported, which further limits interpretation of how the summaries represent the enrolled trial population.

The safety entries report zero serious adverse events, other adverse events, and deaths in the listed groups. Those counts are limited to the posted safety summaries and do not establish the absence of risk. The registry information is therefore best read as descriptive reporting of the specified outcome and safety counts, not as a complete account of treatment efficacy, prediction, or comparative safety.

16. Why This Trial Matters Statistically

This trial is statistically notable because its stated research aim concerns prediction from brain connectivity, while the posted primary outcome is a count-based treatment outcome and the posted contrast is medication versus healthy controls. A prediction question and a group-mean comparison are different statistical questions. To assess prediction, readers would need results showing how connectivity relates to treatment response and how well a model predicts outcomes; those results are not reported in the registry record.

The comparator also shapes the meaning of the reported estimate. Healthy controls are described as non drug using, while placebo and medication are the listed treatment groups. The medication-versus-healthy-control mean difference is not an estimate of medication relative to placebo. Although placebo outcome summaries are posted, an inferential contrast between the two treatment groups is not.

The record illustrates why estimates, uncertainty, and study structure must be considered together. The confidence interval quantifies uncertainty for the reported contrast, but it cannot answer a different comparator question. The small outcome-group counts for medication and placebo, the zero spread in healthy controls, and the unexplained gap between total enrollment and the outcome group counts all affect what can be inferred from the posted summaries. Details on missing outcomes and analysis populations would be needed to clarify how the results relate to enrollment and randomization.

Finally, large planning illustrations based on an observed contrast can look deceptively definitive when the contrast is not the central treatment comparison. The posted planning figures are not the trial’s original sample-size justification and do not answer whether the trial was designed to assess connectivity prediction. This record demonstrates the importance of matching statistical summaries to the scientific question, comparator, and analysis actually reported.

17. Limitations

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

The most important trial-specific limitation in interpreting these results is the comparator used for the posted mean difference. The reported contrast is medication versus healthy control, although a placebo group is also listed. The healthy controls are described as non drug using, and the record does not explain why they are the comparator for the posted treatment result. A medication-versus-placebo estimate is not reported, so the posted contrast cannot be used as a substitute for one.

The study description focuses on brain connectivity and treatment response, but the posted outcome is the number of positive urine drug screens. No connectivity results or analyses of predictive performance are reported. The registry record therefore does not allow assessment of the central prediction aim from the outcome results that are posted.

There is also an unexplained difference between enrollment of 131 and the outcome groups of 38, 9, and 11. The record does not say whether these values reflect missing data, exclusions, a selected analysis population, or another reason. Missing-data methods, participant flow, and analysis-population definitions are not reported. The outcome timeframe is baseline to 12 weeks, while treatment is described as lasting 7 weeks; further timing and measurement details are not given.

The registry record does not report the original sample-size justification, the statistical test or model, adjustment for baseline values, multiplicity procedures, or whether the posted analysis was prespecified. It provides no secondary outcomes or posted analyses beyond the outcome summary and listed comparison. Safety reporting is limited to the counts recorded for the listed groups, without further information about ascertainment or follow-up. These omissions constrain the conclusions that can be drawn from the record; they do not establish what analyses or procedures may have been conducted but not reported.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Striatal Effective Connectivity to Predict Treatment Response in Cocaine Misuse — NCT02080819.
• Registry record last updated 2018-04-12; status last verified 2018-03.
• Results first posted 2018-04-12.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

NCT02080819 is a completed phase 2, randomized, double-masked, parallel trial sponsored by Virginia Commonwealth University. The record lists 131 enrolled participants and cocaine dependence as the condition. Its description proposes studying brain connectivity in relation to response to dopaminergic medications in cocaine dependence.

The listed groups are healthy control, placebo, and levodopa/carbidopa 400/100 BID. Placebo and medication are each described as BID for 7 weeks. The primary outcome is a mean treatment effectiveness score based on positive urine drug screens, with a baseline-to-12-week timeframe.

The posted comparison is medication versus healthy control: mean difference 13.0, confidence interval from 7.681 to 18.32, and unadjusted p-value <0.001. The record also lists placebo outcome summaries, but no medication-versus-placebo inferential contrast. No secondary outcomes or analyses are posted. The relationship between total enrollment and the outcome group counts, as well as missing-data handling and analysis populations, is not reported in the registry record.