Extended-release Naltrexone and Care Management for Alcohol Dependent Frequent Emergency Department Users: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Extended-release Naltrexone and Care Management for Alcohol Dependent Frequent Emergency Department Users (NCT02445339), a randomized phase 4 study. The primary outcome is Number of Heavy Drinking Days.

2. Clinical Question

3. Trial Design

This was a Phase IV, randomized, open-label, non-placebo-controlled, parallel-group study. The registry lists an enrollment of 50 and a completed status. The study start is recorded as 2015-07, and the primary completion date as 2019-02-08. NYU Langone Health is listed as the sponsor.

Participants were assigned to XR-NTX plus care management or standard care. The trial compared the combined intervention with standard care; it was not designed, as described in the registry, to separate the effects of naltrexone from those of care management. Randomization is stated, but the method used to generate or conceal assignments is not reported in the registry record. The allocation ratio is also not reported.

The primary result is for the number of heavy drinking days at Month 3, based on self-report. The posted arm summaries include 13.0 participants in the intervention group and 10.0 in the standard care group for this endpoint. Other posted results include heavy drinking days at Month 6, SIP-2R scores at Month 3, and CDT levels at Month 3. Their endpoint-specific participant counts are shown with the results. The registry record does not explain how these counts relate to the overall enrollment or whether they reflect missing observations, exclusions, or another analysis-population definition.

The summary describes the study as an initial phase intended to inform how to implement and rigorously test the approach before planning a larger effectiveness trial. It says the investigators aimed to assess feasibility and explore effects on several health outcomes. The original statistical analysis plan, the trial’s own sample-size assumptions, and details of any interim analyses are not reported in the registry record. The study is open-label, and the registry identifies no placebo group.

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 Number of Heavy Drinking Days, measured over Month 3.

The primary endpoint is the mean number of heavy drinking days at Month 3, measured by self-report. It represents a count of days described as heavy drinking within the endpoint’s assessment period. The registry record does not define the heavy-drinking threshold, specify the exact recall window, or provide the questionnaire wording. Those details should therefore not be inferred from the endpoint name alone.

Drinking days are a direct behavioral outcome relevant to the study’s stated interest in drinking and its consequences. A mean summarizes the group’s reported number of days, while the standard deviation describes how much participant-level values vary around that mean. The posted summary reports the endpoint as a mean with a standard deviation in each arm, alongside a mean difference, confidence interval, and unadjusted p-value.

The endpoint is self-reported, so it reflects participants’ reports rather than an objective day-by-day measurement. In general, self-report can be informative for behaviors that may not be captured by routine clinical records, but recall and reporting can affect measurement. The open-label design also means participants knew their assigned group; whether that knowledge influenced reporting cannot be established from these summary results.

The Month 3 endpoint is one part of a broader feasibility-oriented study. It does not, on its own, capture healthcare use, engagement, expenditures, quality of life, or all consequences of drinking. Those outcomes were among the study’s stated areas of interest, but the registry record does not report a formal analysis of the full set of aims.

7. Results Posted in the Registry

• Intervention Arm: XR-NTX+CM: mean 62.00 versus 0.00 on control; difference 62.00 (95% CI 56.89 to 67.11), standardized effect d = 8.73; z-test p = <0.001.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Number of Heavy Drinking Days

• 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:
  • Intervention Arm: XR-NTX+CM: mean 32.00 versus 25.00 on control; difference 7.00 (95% CI 0.04 to 13.96), standardized effect d = 0.81; z-test p = 0.049.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Intervention Arm: XR-NTX+CM than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Short Inventory of Problems Related to Alcohol (SIP-2R) Score

• 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:
  • Intervention Arm: XR-NTX+CM: mean 25.40 versus 24.90 on control; difference 0.50 (95% CI -9.51 to 10.51), standardized effect d = 0.04; z-test p = 0.922.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention Arm: XR-NTX+CM and the control. The interval gives the range of effects that remain compatible with the data.

Carbohydrate-deficient Transferrin (CDT) Levels

• 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:
  • Intervention Arm: XR-NTX+CM: mean 5.40 versus 2.80 on control; difference 2.60 (95% CI -0.44 to 5.64), standardized effect d = 0.66; z-test p = 0.094.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention Arm: XR-NTX+CM and the control. The interval gives the range of effects that remain compatible with the data.

Across the posted secondary endpoints, the results are not uniformly aligned in strength or precision. Heavy drinking days at Month 6 show a positive mean difference in the same direction as the primary Month 3 comparison. The SIP-2R score difference is close to zero relative to its reported uncertainty, while the CDT comparison has an interval that includes zero. These outcomes measure different aspects of drinking, alcohol-related problems, and a biomarker; they need not move together, and agreement across them cannot be assumed.

The Month 3 primary result is therefore not accompanied by a consistent pattern of clearly separated group means across all the posted secondary measures. That does not negate the primary result, but it does make the overall evidence more exploratory. A single primary endpoint and several secondary endpoints answer different questions. The secondary results can help describe the range of observed patterns and inform further study, but they do not independently establish the primary finding or explain its mechanism.

The registry lists 14 secondary outcome measures, including repeated entries for some named outcomes, and the posted secondary summaries cover several outcome and time-point combinations. Testing several outcomes creates more opportunities for a nominally small p-value to occur by chance. The registry comparisons are unadjusted, and no multiplicity strategy is reported in the registry record. Consequently, secondary p-values should be interpreted with particular restraint, especially when considered alongside outcomes and time points that do not show the same pattern.

The record also lists no reported analyses for the secondary outcomes. It does not state which outcomes were prespecified as confirmatory, whether the displayed comparisons were exploratory, or how missing data and multiple assessments were handled. The appropriate overall reading is a set of descriptive signals that may guide future evaluation, rather than a collection of definitive tests. The secondary results add context to the primary comparison but do not remove uncertainty about design, measurement, or analysis.

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

• Number of Heavy Drinking Days
• Number of Heavy Drinking Days
• Short Inventory of Problems Related to Alcohol (SIP-2R) Score
• Short Inventory of Problems Related to Alcohol (SIP-2R) Score
• Short Inventory of Problems Related to Alcohol (SIP-2R) Score
• Carbohydrate-deficient Transferrin (CDT) Levels
• Carbohydrate-deficient Transferrin (CDT) Levels
• Carbohydrate-deficient Transferrin (CDT) Levels

9. Statistical Interpretation

10. Statistical Methods Explained

The registry posts group means and standard deviations, a mean difference, a confidence interval, and an unadjusted p-value for the primary continuous endpoint. It does not report a full statistical analysis plan. The explanations below describe the general meaning of these statistics; they are not claims about undocumented methods used by the investigators.

What does the mean difference describe?

A mean is the arithmetic average of the observations in a group. A mean difference compares the group averages, here the intervention group with the standard care group. The listed Month 3 difference of 62.0 is in the endpoint’s unit, days. The comparison is oriented as intervention minus standard care in the posted summary. It is a difference between group averages, not a statement about the experience of every participant.

The standard deviation describes the spread of observed values around a group mean. A smaller standard deviation indicates less variation in the observations; it does not measure uncertainty in the mean difference. The Month 3 standard care group has a reported standard deviation of 0.0. That makes the summary unusual and relevant to assessing how the comparison was calculated. The registry does not provide participant-level observations or explain the zero variation, so the reason and its implications for the underlying data cannot be determined.

What does a confidence interval convey?

In general, a confidence interval expresses uncertainty around an estimated quantity under the assumptions of the analysis. A narrower interval indicates greater statistical precision for that estimate, while a wider interval indicates more uncertainty. For a difference, an interval that excludes zero is consistent with a nonzero difference under the method used to construct it. This interpretation does not establish that the difference is causal, clinically important, or free of bias.

The primary comparison’s interval lies above zero. The intervals for the posted SIP-2R and CDT comparisons include zero, whereas the Month 6 heavy-drinking-days interval does not. These are descriptive readings of the posted intervals. The registry record does not identify the confidence-interval method, whether it accounts for any design features, or whether the comparisons were adjusted for baseline measurements or other variables.

How should a p-value be read?

In general, a p-value describes how incompatible the observed data are with a specified null model, assuming that model and the analysis assumptions hold. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. The primary p-value is listed as <0.001 and is explicitly unadjusted. The secondary p-values are also presented as unadjusted results. The registry does not report a multiplicity adjustment or a detailed account of the testing procedure.

A p-value is not a substitute for examining the estimated difference and its interval. Here, interpretation also depends on the posted group means, standard deviations, and endpoint counts. A small p-value cannot resolve uncertainty about measurement, missing data, selection into the analysis population, or the open-label comparison. Nor does a p-value establish that the combined intervention, rather than some other feature of the study or its participants, produced the observed result.

What can the reported design establish?

Random assignment can, in general, help make groups comparable at the time of allocation, but the registry record does not describe the randomization procedure, allocation concealment, or checks of baseline balance. The open-label design means treatment assignment was known. This may matter for self-reported outcomes and for care received after assignment; whether it did so is not reported. The intervention combines XR-NTX and care management, so the comparison cannot isolate the contribution of each component.

The registry identifies a parallel-group comparison but does not report a detailed model, covariate adjustment, missing-data method, or analysis population. It also does not provide an explanation for why the primary endpoint summaries are based on 13.0 and 10.0 participants when total enrollment is 50. Without those details, readers can describe the posted summaries and their uncertainty, but cannot reconstruct or fully audit the analysis from the registry alone.

What does over-dispersion mean in general?

For count outcomes, over-dispersion means that observed variability is greater than a chosen count model expects. When present, it can make standard errors and p-values from a poorly matched model misleading. This is a general issue for count data, not a finding established for this trial. The record reports means and standard deviations but does not identify a count model, describe a check for over-dispersion, or provide participant-level data with which to assess it.

The primary outcome is expressed as a number of days, but the registry’s summary statistic is a mean with a standard deviation. Readers should not infer from that presentation that a particular count-distribution model was fitted. Whether an alternative model, transformation, or robust method was considered is not reported in the registry record.

What are standardized effects and planning calculations?

A standardized effect expresses a difference relative to a measure of variability, allowing comparisons on a scale without the original endpoint unit. The registry lists such an effect estimate with the primary comparison, but does not report a protocol rationale for its use. Standardized effects can be sensitive to how variability is estimated, particularly when one group has a reported standard deviation of 0.0. The listed planning values should therefore be read as calculations based on the observed summaries and stated assumptions, not as evidence that the trial was designed around those values.

In general, a power calculation asks how many participants would be needed, under specified assumptions, to have a chosen probability of detecting a specified effect using a chosen test. It is a planning tool, not a measure of how likely the observed result is to be true. The registry’s planning illustration uses the observed effect and a normal approximation. It is separate from the trial’s original design rationale, which is not reported in the registry record. The small-study summaries, especially the primary zero standard deviation in one group, make it important not to treat those illustrations as a substitute for a prospective design and analysis plan.

11. Confidence Intervals and Precision

The primary mean difference is 62.0 days, with a 95% confidence interval from 56.89 to 67.11. This interval is entirely above zero and is the registry’s expression of statistical precision for the posted comparison. Its span should be considered alongside the endpoint-specific counts, 13.0 and 10.0, and the unusual standard care summary of mean 0.0 and standard deviation 0.0. The interval alone cannot show whether the data were complete, whether the measurement was unbiased, or whether the analysis assumptions were appropriate.

The reported secondary intervals give a less uniform picture. The Month 6 heavy-drinking-days interval runs from 0.040 to 13.96, while the SIP-2R interval runs from -9.507 to 10.51 and the CDT interval from -0.444 to 5.644. The latter two include zero; the Month 6 interval does not. These intervals describe uncertainty in separate endpoint comparisons and do not establish that an outcome is important or that a treatment caused a difference. The registry does not report whether the intervals account for examining multiple outcomes.

Precision is distinct from validity. A confidence interval is calculated within an analysis framework and does not automatically account for open-label measurement, missing observations, selection into an endpoint analysis, or other sources of bias. The registry does not report enough methodological detail to evaluate how those issues were handled. In this small, exploratory study, the intervals should therefore be read as uncertainty around the posted comparisons, not as a complete summary of all uncertainty about the results.

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 sample-size table and curve are planning illustrations based on the posted observed effects, not the trial’s original design calculations. Because the outcomes shown are continuous measures, the figures are participants per arm, not total event counts. The listed planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The trial’s own design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the planned number of participants per arm for a calculation with an 80% probability of detecting the target effect, if the assumptions hold. The 90% column describes the corresponding calculation using a 90% probability. These are prospective design concepts: they do not tell us the probability that the posted finding is true. This is not observed power.

The table varies the target from 100% of the observed effect to 75% and 50% of that effect. A smaller target effect generally requires more participants to detect, which is why the planning figures increase as the assumed fraction falls for the posted secondary endpoints. For the primary comparison, The table shows 1 participant per arm for 80% power and 1 participant per arm for 90% power at each of the 100% and 75% effect levels; for 50% of the observed effect it lists 1 and 2, respectively. Those unusually small illustrations reflect the very large observed primary difference relative to the reported variability, including a standard care standard deviation of 0.0. They should not be interpreted as a recommended design without a prospective justification and further assessment of assumptions.

The calculations do not repair limitations in the observed data or establish that the observed effect will recur. In particular, the original protocol’s assumptions are not reported, and the planning illustration uses the observed effect rather than an independently specified target. The table is useful for seeing how required enrollment changes under its stated assumptions, but it is not a record of the trial’s enrollment decision.

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 = 62.000; pooled standard deviation σ = 7.106.
2. n = 2 × (1.96 + 0.842)² × 7.106² / 62.000² = 0.2, rounded up to 1 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 <- 62                      # observed difference in means
sigma <- 7.10573209257347                     # 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(2445339)
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 = 1 (80% power), 1 (90% power)
 75% of observed effect: n per arm = 1 (80% power), 1 (90% power)
 50% of observed effect: n per arm = 1 (80% power), 2 (90% power)
power.t.test: 1.7 
Simulated power at n = 1 per arm: NA (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a multiplicity plan. This matters because the study includes a primary outcome, multiple secondary outcomes, and more than one assessment time for some measures. When several hypotheses are tested, the chance of obtaining at least one apparently notable result can increase. In general, investigators may address this through prespecified testing hierarchies, adjusted thresholds, or other procedures. Whether any such approach was planned or used is not reported in the registry record. The listed comparison p-values are unadjusted.

The record reports 15 outcome measures and lists 14 secondary outcome measures. Some outcome names appear more than once, consistent with results at different time points, but the registry does not provide a complete analysis plan that explains how all assessments fit together. It also lists 0 reported analyses. The posted summaries and comparisons can be described, but the record does not identify a confirmatory testing sequence or explain how secondary findings should be treated relative to the primary endpoint.

Missing-data handling is not reported in the registry record. The primary endpoint summaries include 13.0 participants in the intervention arm and 10.0 in standard care, whereas enrollment is 50. The safety section gives a different at-risk count. These registry entries do not explain why the endpoint counts differ from enrollment, whether participants lacked a Month 3 measurement, or whether any observations were excluded. The registry also does not describe imputation, complete-case analysis, sensitivity analyses, or follow-up rates. It would be inappropriate to assume which approach was used.

The analysis populations are not reported in the registry record. It is not stated whether results use all randomized participants, participants who received assigned care, or another group. The record does not describe deviations from assigned treatment, adherence, crossover, or exclusions. Nor does it report an analysis adjustment for baseline endpoint values or other characteristics. These omissions limit the ability to assess how the posted comparisons relate to the randomized groups and how robust they might be to alternative analysis choices.

The registry summary names patient-level characteristics of interest, but does not report analyses of associations between those characteristics and effectiveness. It also does not report interim analyses or the trial’s complete statistical analysis plan. These gaps do not change the reported figures, but they constrain interpretation of the inferential results, especially the unadjusted secondary comparisons.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The safety section reports 25 participants at risk in each arm. For both the serious and other adverse-event categories, it reports 0 affected participants in the XR-NTX plus care management arm and 0 in the standard care arm. It also reports 0 deaths in each arm. No serious adverse-event terms are listed.

These are the figures recorded in the registry and should be read within the safety reporting categories used there. They do not show that adverse events are impossible, nor do zero recorded events establish that the groups have identical safety profiles. The registry record does not provide event narratives, exposure duration, definitions, severity grades, or details about how events were collected. It also does not explain how the safety at-risk count of 25 per arm relates to the smaller endpoint-specific analysis counts.

These safety summaries are separate from the efficacy comparisons and should not be used to infer a treatment benefit. The posted figures describe what was recorded in the registry’s safety section; they cannot by themselves establish the completeness of event ascertainment or characterize risks outside this study.

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

The posted primary result is a large difference in mean self-reported heavy drinking days at Month 3 between the XR-NTX plus care management arm and standard care. The registry’s confidence interval lies above zero, and its unadjusted p-value is <0.001. Those results indicate a clear statistical separation in the posted summaries under the analysis represented by the registry comparison. They do not establish that the combined intervention caused the separation, that the result would recur in a larger study, or that it represents a particular clinical benefit.

The study was randomized, which is relevant to interpreting a treatment comparison, but the registry record does not describe the randomization process or the analysis population. It was also open-label and non-placebo-controlled, and the primary endpoint was self-reported. Those features do not make the reported data unusable, but they are important when considering possible differences in reporting, care, and follow-up. The record does not provide individual-level data or details sufficient to assess those possibilities.

The primary comparison also has an unusual standard care summary: mean 0.0 and standard deviation 0.0. The registry does not explain this pattern. The endpoint summaries are based on 13.0 intervention participants and 10.0 standard care participants, against an overall enrollment of 50, and the record does not explain the difference. These details make it especially important to treat the result as exploratory rather than as a definitive estimate for a broader population.

The intervention is a combination of XR-NTX and care management, so this trial does not isolate the effect of either component. Nor does a result for heavy drinking days answer every stated question about healthcare utilization, engagement, expenditures, drinking consequences, and quality of life. The study summary describes a feasibility-oriented phase intended to inform planning for a larger effectiveness trial. The appropriate meaning is therefore bounded: the posted data show a striking primary endpoint comparison in this study, while the design and reporting gaps leave important uncertainty about its interpretation and generalizability.

17. Why This Trial Matters Statistically

This trial is statistically instructive because its primary result is striking while its data summaries raise questions that cannot be resolved from the registry alone. A very large estimated group difference can produce extremely small planning figures when calculations are based on the observed effect. Those planning figures are not evidence that a definitive study needs only a very small enrollment. They illustrate how strongly sample-size calculations depend on the effect size and variability assumed.

The reported standard care mean and standard deviation of 0.0 show why variability deserves attention when interpreting a mean comparison and translating an observed effect into a future design. General planning principles require assumptions that are credible for the target population and outcome, not simply a direct reuse of an unusually large result from a small study. The registry’s own design justification is not reported, so the displayed planning calculations should be kept separate from the original trial design.

The record also highlights the difference between a feasibility-oriented study and a confirmatory effectiveness trial. The stated goal includes learning how to initiate and continue care and how to assess outcomes, as well as exploring health outcomes. That context supports cautious use of the posted estimates: they can inform questions for subsequent research, but the registry does not report the methods needed to treat the comparisons as a complete confirmatory analysis.

Finally, the combination of randomized allocation and open-label, self-reported outcome measurement offers a useful reminder that randomization does not remove every source of uncertainty. Measurement, follow-up, analysis populations, missing data, and multiplicity all matter. Here, several of those details are not reported in the registry record. Reading estimates together with their precision and reporting context is more informative than relying on a p-value alone.

18. Limitations

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

Several limitations are specific to the posted record and study design. The trial enrolled 50 participants, while the primary endpoint summaries include 13.0 participants in the intervention arm and 10.0 in standard care. The registry does not explain the difference between enrollment and these analysis counts, provide follow-up completeness, or state how missing observations were handled. This makes it difficult to assess whether the endpoint summaries represent the randomized groups.

The primary outcome was self-reported, and the trial was open-label. Participants knew their assignment, and the record does not describe procedures intended to reduce reporting or assessment bias. The intervention also combines extended-release naltrexone with care management, so the comparison cannot identify which component accounts for any observed group difference. The standard care description is brief, and further details about care received are not reported in the registry record.

The standard care group’s Month 3 primary mean and standard deviation are both 0.0. The registry does not explain this result or provide participant-level data that would allow readers to inspect its distribution. The posted confidence interval and p-value therefore cannot be fully assessed against the underlying observations or a detailed analysis method.

The registry record does not report the randomization procedure, allocation concealment, baseline balance, a full statistical analysis plan, the analysis population, or the approach to multiple comparisons. It does not describe whether analyses were adjusted for baseline values, or whether sensitivity analyses were conducted. The primary time point is Month 3, while secondary outcomes include later or different assessments; the record does not provide a comprehensive account of follow-up or outcome collection.

Finally, this was a single completed study described as an early step toward planning a larger effectiveness trial. The record does not report enough about eligibility and participant characteristics to judge how broadly the findings apply to other populations or care settings. These limitations do not negate the posted results, but they constrain what can be concluded from them.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Extended-release Naltrexone and Care Management for Alcohol Dependent Frequent Emergency Department Users — NCT02445339.
• Registry record last updated 2022-05-11; status last verified 2022-04.
• Results first posted 2022-05-11.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry describes a completed Phase IV randomized, open-label, non-placebo-controlled parallel-group study sponsored by NYU Langone Health, with an enrollment of 50. It compared extended-release naltrexone plus care management with standard care for frequent emergency-department users with alcohol dependence.

The primary endpoint was self-reported mean heavy drinking days at Month 3. The posted comparison reports a mean difference of 62.0 days, a 95% confidence interval from 56.89 to 67.11, and an unadjusted p-value of <0.001. The standard care group’s reported mean and standard deviation are both 0.0. The endpoint-specific counts are 13.0 and 10.0, and the registry does not explain how these relate to total enrollment.

The registry also posts secondary outcome summaries and zero reported serious adverse events, other adverse events, and deaths in both safety groups. Details of missing-data handling, analysis populations, multiplicity, and the original sample-size justification are not reported in the registry record. The study summary frames the work as assessing feasibility and exploring outcomes ahead of a larger trial.