The Effects of Cannabinoid on Patients With Non-GERD Related Non Cardiac Chest Pain: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effects of Cannabinoid on Patients With Non-GERD Related Non Cardiac Chest Pain (NCT01598207), a randomized phase 4 study. The primary outcome is Frequency of Chest Pain Episodes.

2. Clinical Question

3. Trial Design

The trial is registered as NCT01598207 and is listed as phase 4, randomized, double-masked, and parallel. Its status is completed. The registry record lists a start date of 2011-02 and a primary completion date of 2014-05. The listed sponsor is Yehudith Assouline-Dayan.

The protocol summary describes a planned study of 40 subjects with noncardiac, non-reflux chest pain, assigned to dronabinol or placebo for 4 weeks. The listed dose is 5 mg Bid. The enrollment recorded for the trial is 13. The record does not explain the relationship between the planned study size and the recorded enrollment, so the reason they differ is not reported in the registry record.

The listed intervention names are Marinol and Placebo. The posted primary outcome results give a group size of 6.0 for Marinol and 6.0 for placebo. Those outcome group sizes are not the same as the recorded enrollment, and the registry record does not explain the difference. They should be read as the group sizes attached to the posted primary outcome, not as a complete account of enrollment or participant flow.

The primary outcome timeframe is Baseline and 1 month. The protocol summary describes assessment at baseline and 4 weeks, using a symptom diary and impedance planimetry. The summary text ends before the full primary outcome description is complete. Further details about conduct, visit schedules, allocation concealment, treatment adherence, and participant flow are not reported in the registry record.

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 Frequency of Chest Pain Episodes, measured over Baseline and 1 month.

The primary outcome is titled “Frequency of Chest Pain Episodes.” Its unit is participants, and the posted values are counts. The description states that the measure is the number of people still experiencing the same amount of chest pain during treatment as previously without treatment. Thus, the registry wording appears to classify participants according to whether their chest pain remained at the same amount, rather than reporting the number of episodes each participant experienced.

The distinction matters for interpretation. A count of participants does not show how often an individual experienced pain, how intense episodes were, or how long they lasted. The title and description do not fully align: the title refers to episode frequency, while the description refers to people continuing to experience the same amount of pain. The registry record does not provide a fuller operational definition or explain how the count was derived.

Comparing a clearly defined outcome between randomized groups can help describe how the outcome differed across assigned treatments. Here, the posted result is a count in each arm, but a statistical comparison and uncertainty estimates are not reported in the registry record. The endpoint is accompanied by a stated timeframe of baseline and 1 month; the protocol summary describes assessment at baseline and 4 weeks. The registry record does not give further detail about the rules used to classify participants or handle incomplete measurements.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry record classifies the primary outcome as binary and gives its unit as participants. In general, a binary outcome places each participant into one of two categories, such as meeting or not meeting a defined outcome condition. Group results can then be reported as counts of participants in a category. A count alone is not a complete description of the analysis: interpretation also depends on the outcome definition, the number of participants with usable measurements, and the method used to compare groups.

What do the posted counts represent?

The primary outcome description refers to the number of people still experiencing the same amount of chest pain during treatment as previously without treatment. The posted values are 1.0 for Marinol and 3.0 for placebo, with a group size of 6.0 attached to each. The meaning of the category is not fully specified beyond that description. The title, “Frequency of Chest Pain Episodes,” could suggest a count of episodes, but the unit and description instead point to a count of participants. The registry record does not explain this wording difference. The safest reading is to treat the reported figures as participant counts, not as episode counts or a direct measure of symptom intensity.

Why does a confidence interval matter?

In general, a confidence interval expresses the uncertainty around an estimated effect using the data and an analysis method. It helps readers distinguish a point estimate from the range of effect sizes that remain compatible with the observed data under that method. The registry record does not report a confidence interval for this comparison. Without one, the precision of the group contrast cannot be assessed from the posted primary outcome results. A confidence interval would not remove limitations in outcome definition or missing data, but it would communicate statistical uncertainty more directly than raw counts alone.

What can a significance test establish?

In general, a significance test evaluates data against a specified statistical model and null hypothesis. Its result depends on the analysis method, assumptions, and analysis population. A p-value does not measure the size or clinical importance of an effect, and it does not by itself show that a result is reproducible. No primary outcome p-value or statistical test is reported in the registry record. The record also lists 0 analyses, so there is no posted analysis result to use as a sponsor's inferential conclusion. No test should be inferred from the reported counts.

What does randomization contribute?

In general, random assignment is intended to make treatment groups comparable with respect to measured and unmeasured characteristics, on average. It does not guarantee identical group composition, especially in a small study, and it does not resolve problems in outcome measurement or incomplete follow-up. The trial is registered as randomized, but the method used to generate or conceal the allocation is not reported in the registry record. The posted results therefore identify the design as randomized without documenting those implementation details.

How should planning calculations be read?

General sample-size calculations estimate how much information a future study might need under stated assumptions. The registry record describes a planning illustration based on the observed effect, a two-sided significance level of 0.05, equal allocation, and a normal approximation; the effect to detect is expressed as a stated fraction of the observed effect. Such calculations are planning illustrations, not observed power and not evidence that the trial had a particular probability of detecting an effect. They depend on assumptions about the effect and analysis method. The registry record does not report the trial's own sample-size justification, so the planning illustration should not be mistaken for the rationale used to set the original enrollment target.

Why do analysis choices matter?

For a binary outcome, a comparison can use different methods, and those methods may differ in their assumptions and uncertainty estimates. The choice can depend on the number of observations, the distribution of outcomes, and the study design. General statistical practice calls for a method suited to the data and a clear statement of the comparison being estimated. No such method or treatment-effect estimate is reported in the registry record. It is therefore not possible to determine whether the posted counts were analyzed with a model, a direct group comparison, or another approach.

In general, over-dispersion is a concern when observed variability exceeds what a chosen model expects; accounting for it can affect uncertainty estimates. It is not possible to assess that issue from these posted binary counts, and the registry record does not report a model or dispersion assessment. Similarly, there is no reported adjusted analysis, covariate set, or sensitivity analysis. General explanations of these methods should not be read as a claim that they were used in this trial.

The number of secondary outcomes and the absence of posted analyses also matter for interpretation. When multiple outcomes are examined, the chance of finding an apparently notable result can increase if no prespecified approach accounts for multiplicity. The registry record lists 6 secondary outcomes, but a multiplicity strategy and outcome hierarchy are not reported. No conclusion about whether adjustments were made can be drawn from the record. The record supports a descriptive reading of the arm counts, while leaving the inferential methods and their assumptions undocumented.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Marinol", "Placebo")
n      <- c(6, 6)
events <- c(1, 3)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Marinol  6  1  16.7  0.4  64.1  3.0  56.4  3.7  57.9
ARM  Placebo  6  3  50.0  11.8  88.2  18.8  81.2  18.4  81.6

11. Multiplicity, Missing Data and Analysis Populations

The registry record lists 7 outcome measures, comprising the primary outcome and 6 secondary outcomes. It lists 0 analyses. The planned order of interpretation, any distinction between confirmatory and exploratory outcomes, and any adjustment for multiplicity are not reported in the registry record. In general, examining multiple outcomes without an appropriate prespecified strategy can increase the chance of a misleading isolated finding. There is not enough information to determine whether or how this issue was addressed.

Missing-data methods are not reported in the registry record. The record does not say how incomplete outcome measurements were handled, whether participants with missing measurements were excluded, or whether any imputation or sensitivity analysis was performed. The group sizes attached to the primary outcome are 6.0 for Marinol and 6.0 for placebo, while enrollment is recorded as 13. The registry record does not explain that relationship or report participant flow by outcome. It is therefore not possible to assess whether the posted outcome counts include all enrolled participants or how missing observations might affect interpretation.

The analysis population is also not reported in the registry record. There is no statement identifying an intention-to-treat, per-protocol, or other population for the primary comparison. The record does not report a prespecified statistical analysis plan or explain how deviations from the assigned treatment, if any, were handled. These omissions limit reproducibility and make it difficult to judge whether the posted result corresponds to the randomized comparison or to a selected subset of participants.

12. 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 5% reporting threshold.

Most frequent non-serious adverse event terms

The serious adverse event figures are reported separately from the primary outcome. In the Marinol group, 0 serious adverse events are recorded among 7 participants at risk. In the placebo group, 0 serious adverse events are recorded among 6 participants at risk. These are the registry's posted counts; they do not establish that the risk of serious adverse events is identical between groups. With no comparative analysis or uncertainty estimates reported, the precision of the safety comparison cannot be assessed.

The record also lists 1 other adverse event among 7 participants at risk in the Marinol group and 1 among 6 participants at risk in the placebo group. The record does not provide further detail in the listed group summaries about event timing, severity, relatedness, or whether participants experienced more than one event. The list of top serious event terms is empty. Death counts are not reported in the registry record.

The safety risk counts are not the same as the primary outcome group sizes, which are 6.0 in each arm. The registry record does not explain why the denominators differ. These safety figures should be read as the specific counts recorded for the safety outcomes, not substituted for the primary outcome denominators or treated as a complete assessment of all possible harms.

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

The registry record documents a randomized, double-masked, parallel comparison of Marinol and placebo in a phase 4 trial focused on noncardiac, non-reflux chest pain. The primary outcome is reported as participant counts: 1.0 for Marinol and 3.0 for placebo, with a group size of 6.0 attached to each. The record's description refers to participants still experiencing the same amount of chest pain, while the outcome title refers to episode frequency. This difference in wording limits certainty about exactly what the count captures.

These figures describe the registered result, but the registry record does not report a statistical comparison, confidence interval, p-value, or analysis method. The values therefore do not show how precise the apparent group contrast is or whether it is statistically distinguishable from chance variation. Nor do they quantify changes in episode frequency, intensity, duration, or sensory thresholds. Although the registry lists several secondary outcomes, their results and analyses are not included in the information recorded.

The trial's enrollment is listed as 13, while the primary outcome group sizes are 6.0 for each arm. The record does not explain this difference, identify the analysis population, or describe missing-data handling. As a result, the posted counts cannot be assumed to represent every enrolled participant. The record also does not provide enough information to assess the robustness of the findings to alternative analytic choices.

These limitations mean the result should be read as a small set of descriptive counts rather than as a definitive estimate of a treatment effect. It does not establish that the treatments differ, that they are equivalent, or that the observed counts would recur in another study. The posted information is useful for understanding what the registry records, but broader conclusions would require clearer endpoint definitions, complete outcome reporting, and a documented analysis with measures of uncertainty.

14. Why This Trial Matters Statistically

This trial illustrates why statistical interpretation depends on more than a pair of outcome values. The posted primary results are straightforward counts, but the endpoint title and its description do not clearly identify the same quantity. A count of participants said to remain at the same amount of chest pain is not interchangeable with a count of episodes. Clear endpoint definitions are essential because they determine what the results mean and how a valid comparison should be conducted.

The record also illustrates the difference between descriptive results and inferential evidence. The arm-specific counts describe the posted outcomes, while the absence of a statistical analysis, confidence interval, and p-value leaves precision and comparative uncertainty unresolved. Statistical interpretation should not turn a numerical contrast into a conclusion about a treatment effect when the comparison method and its uncertainty are not documented.

The enrollment and outcome group sizes raise a further reporting issue. Enrollment is recorded as 13, while each primary outcome group size is 6.0. Without participant flow or missing-data information, readers cannot determine how those figures are related. This is relevant because exclusions or incomplete observations can affect both the representativeness of the analyzed participants and the validity of a randomized comparison.

Finally, the registry lists multiple outcomes but no analyses. That makes the treatment of multiplicity and the intended analysis hierarchy unclear. The record is valuable as a description of trial design and posted counts, while also demonstrating why transparent outcome definitions, analysis plans, participant flow, and uncertainty estimates are important to statistical reporting.

15. 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 trial-specific limitations constrain interpretation. The primary outcome title refers to frequency of chest pain episodes, but its description refers to the number of people still experiencing the same amount of pain during treatment as previously without treatment. The record does not define the classification rule or reconcile this difference. The reported values are participant counts, so they do not provide a direct summary of episode frequency, intensity, or duration.

The recorded enrollment is 13, whereas the primary outcome results give group sizes of 6.0 for Marinol and 6.0 for placebo. The registry record does not explain the discrepancy, provide participant flow, or identify the analysis population. Missing-data handling and treatment adherence are not reported. As a result, the completeness and representativeness of the outcome counts cannot be assessed.

The protocol summary describes a planned enrollment of 40, while the recorded enrollment is 13. No explanation for the difference or sample-size justification is reported in the registry record. The planning illustration described in the record is based on the observed effect and should not be confused with the original trial design rationale or with observed power.

The record does not provide a statistical analysis, effect estimate, confidence interval, or p-value. It lists 6 secondary outcomes but does not report their analysis results or a multiplicity strategy. Details of randomization, masking implementation, allocation concealment, and the full endpoint procedures are also not reported in the registry record. These limitations make the posted counts descriptive and leave key aspects of precision, reproducibility, and bias assessment unresolved.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: The Effects of Cannabinoid on Patients With Non-GERD Related Non Cardiac Chest Pain — NCT01598207.
• Registry record last updated 2017-04-28; status last verified 2017-04.
• Results first posted 2017-04-28.
• 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.

19. Record Summary

NCT01598207 is listed as a completed phase 4 randomized, double-masked, parallel trial of Marinol versus placebo for noncardiac, non-reflux chest pain. The registry record gives enrollment as 13, a start date of 2011-02, and a primary completion date of 2014-05. The protocol summary describes dronabinol at 5 mg Bid for 4 weeks and a planned enrollment of 40.

The primary outcome is titled “Frequency of Chest Pain Episodes,” with a timeframe of baseline and 1 month. Its description refers to participants still experiencing the same amount of chest pain. The posted values are 1.0 participants for Marinol and 3.0 participants for placebo, with a group size of 6.0 in each arm. No statistical comparison or uncertainty estimate is reported in the registry record. The record lists 6 secondary outcomes and 0 analyses. Serious adverse event counts are 0 in each arm; other adverse event counts are 1 in each arm. Important details about missing data, analysis populations, and multiplicity are not reported in the registry record.