Purple Grape Juice in Improving Vascular Health in Childhood Cancer Survivors: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Purple Grape Juice in Improving Vascular Health in Childhood Cancer Survivors (NCT01043939), a randomized phase 1 study. The primary outcome is Change in Endothelial Function (Reactive Hyperemia Peripheral Arterial Tonometry (RH-PAT) Index Score).

2. Clinical Question

The study rationale in the registry concerns cardiovascular risk among childhood cancer survivors and the possibility that purple grape juice could affect oxidative stress and vascular health. This trial was a phase 1 pilot study, rather than a report of a long-term clinical outcome. Its primary endpoint was a vascular-function measure, while the registry also lists oxidized LDL, myeloperoxidase, and high-sensitivity C-reactive protein as secondary outcomes.

The question therefore concerns a short-term difference in a measured vascular-function outcome between juice conditions in this study population. It is not a comparison of long-term cardiovascular events, and the registry record does not report such outcomes as the primary endpoint.

3. Trial Design

The registry identifies this as a phase 1, randomized, open-label crossover trial sponsored by the University of Minnesota. Enrollment was 24, and the study status is completed. The record lists a start date of 2009-11 and a primary completion date of 2010-10. It describes the study as a pilot evaluation of purple grape juice and vascular health in childhood cancer survivors.

In a crossover design, participants receive more than one intervention condition in a planned sequence, so comparisons can be made across conditions within the study rather than assigning each participant to only one condition throughout. Here, the registry describes two randomized sequences: purple grape juice first followed by apple juice, or apple juice first followed by purple grape juice. Both sequences include a 4 week run-in, an initial 4-week juice period, a 4 week washout, and a later 4-week juice period. The registry labels the later period as week 12.

The schedule identifies the amount and frequency for each juice: 6 ounces twice daily. The listed washout separates the two juice periods, but the registry does not explain the rationale for its duration or report whether the analysis accounted for possible period or carryover effects. Those details are not reported in the registry record.

Masking is listed as none. This means the record does not describe the trial as blinded; it does not, by itself, establish whether awareness of treatment affected measurement or participant behavior. The registry lists a mixed models analysis for the primary comparison. Further model specification, including terms for sequence, period, or treatment-by-period effects, is not reported in the registry record.

The primary outcome was assessed as change in the RH-PAT index score over 4 weeks. The primary analysis population is listed as intent-to-treat, but the record does not provide a detailed description of how that population was defined or how missing outcome measurements were handled. The registry also does not report the original sample-size justification or a detailed prespecified statistical analysis plan.

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.

Before assignment: 30 recruited; 6 drop-outs during 4 week run-in period, prior to randomization due to now-show for first clinic visit or concerns regarding time, compliance, or blood draws.

First Intervention

Washout Period

Second Intervention

Analysis population for the primary outcome, as defined in the registry: Intent-to-Treat analysis

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 Change in Endothelial Function (Reactive Hyperemia Peripheral Arterial Tonometry (RH-PAT) Index Score), measured over 4 weeks (change since baseline).

The primary endpoint is change in endothelial function measured with the reactive hyperemia peripheral arterial tonometry index, or RH-PAT index. The registry describes it as change since baseline over 4 weeks and reports the comparison as a difference of least-squares means. It is a continuous measure, expressed in units on a scale, rather than a count of clinical events.

The measurement uses probes on the index fingers of both hands and a blood pressure cuff on one arm. After a 5 minute occlusion period, pulse volume measurements are used to calculate a ratio comparing the hyperemic response with the baseline pulse amplitude, corrected using the control finger. The resulting RH-PAT index is used as an indicator of endothelial function. The registry states that higher scores indicate better endothelial function and that lower scores reflect worse endothelial function.

This endpoint is relevant to the trial’s stated vascular-health question because it measures a physiological response associated with vascular function. It can detect a change in that measured response over the stated assessment period. It is not itself a measure of cardiovascular disease events, long-term health, or overall clinical benefit. The registry’s description says that a positive difference of least-squares means is suggestive of an improvement, so interpretation must also keep the comparison’s direction clear: a contrast defined as apple juice minus purple grape juice has the opposite sign from a contrast defined in the reverse order.

7. Results Posted in the Registry

• Apple Juice: mean 0.22 versus 0.06 on control; difference 0.16 (95% CI -0.09 to 0.41), standardized effect d = 0.36; z-test p = 0.214.

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.

Change in Oxidized LDL

• 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 errors.
• Result:
  • Apple Juice: mean 1.57 versus 4.66 on control; difference -3.09 (95% CI -8.70 to 2.52), standardized effect d = -0.31; z-test p = 0.281.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Apple Juice and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists three secondary outcomes: change in oxidized LDL, change in myeloperoxidase, and change in high-sensitivity C-reactive protein. A result is posted for oxidized LDL; outcome results for myeloperoxidase and high-sensitivity C-reactive protein are not reported in the registry record. As a result, the record does not support a complete assessment of whether the secondary outcomes show a consistent pattern across all listed measures.

The posted oxidized-LDL comparison is also uncertain: its confidence interval includes zero, and its unadjusted p-value does not provide clear evidence of a between-condition difference. This broadly accords with the primary result in the limited sense that neither posted comparison resolves a condition difference. It does not establish that the primary and secondary outcomes are measuring the same process or that their results should be expected to match.

Secondary outcomes generally provide supporting or exploratory information alongside a primary endpoint. When several outcomes are examined, the chance of observing an apparently notable result by chance can increase if each is tested separately without adjustment. The registry record does not report whether secondary-outcome analyses were adjusted for multiplicity, or whether a hierarchy or other prespecified testing strategy was used. Unadjusted secondary results therefore carry less weight than a prespecified primary analysis and should be treated as exploratory rather than conclusive.

The registry’s list of outcomes is not a substitute for complete results. Without posted results for two listed secondary measures, readers cannot evaluate whether those measures reinforce, complicate, or differ from the available comparisons. The absence of those results in the record should not be interpreted as evidence that there was no change or no difference.

Overall, the available secondary information does not materially settle the primary question. It offers limited additional context, with incomplete outcome reporting and no reported multiplicity strategy. Conclusions should remain anchored to the primary endpoint and its uncertainty, while recognizing that the secondary findings are not a comprehensive account of all listed measures.

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

• Change in Oxidized LDL
• Change in Myeloperoxidase (MPO)
• Change in High Sensitivity C-Reactive Protein (Hs-CRP)

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports continuous outcomes as least-squares means with standard errors and describes the primary comparison as a difference of least-squares means from a mixed models analysis. Statistical methods help distinguish the estimated size and direction of a difference from the uncertainty around that estimate. They do not remove the need to consider the design, the outcome definition, and the amount of information in the data.

What does a least-squares mean represent?

A least-squares mean is a model-based estimate of a group mean. In a model with relevant terms, it can represent a mean adjusted for those terms rather than a simple arithmetic average. The registry names the least-squares-mean contrast and the mixed-model method, but it does not provide the model formula, covariates, or the factors included in the model. It is therefore not possible to say from the record which adjustments, if any, were made beyond the model’s reported method.

The individual condition estimates are 0.06 for purple grape juice and 0.22 for apple juice. The reported primary contrast is -0.16. In the posted recalculation, the comparison is written in the reverse direction, as apple juice minus purple grape juice, and its estimate is 0.16. The sign of a difference depends on the order of subtraction; it does not indicate a different underlying pair of group estimates.

What does the confidence interval add?

A confidence interval describes statistical uncertainty around an estimated effect. In general, a narrower interval indicates greater precision, while a wider interval indicates less precision. The reported 95% interval for the mixed-model contrast extends from -0.42 to 0.11. Because it includes zero, it is compatible with no contrast as well as with contrasts in either direction. The interval should be considered together with the point estimate, rather than treated as a separate yes-or-no verdict.

The recalculated interval is based on an unadjusted comparison of posted summary statistics. Its inputs include the reported means and standard errors, and the recalculated standard deviation is approximate. It does not recreate a mixed model for a randomized crossover trial. Differences between the recalculated interval and the sponsor-reported interval may reflect that distinction in method and information, rather than a direct disagreement about the observed means.

What does a p-value describe?

A p-value quantifies how unusual data at least as inconsistent with a specified null model would be if that model were true, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. The sponsor-reported primary p-value is 0.25. The unadjusted recalculated p-value is 0.214. These values are associated with different analysis approaches and should not be treated as interchangeable results from the same fitted model.

The term unadjusted is important for the recalculated p-value: it describes the simple comparison and does not account for any model-based adjustments or multiplicity correction. The registry does not report whether the sponsor’s p-value was adjusted for multiple outcomes or other planned comparisons. That information is not reported in the registry record.

How does crossover structure affect analysis?

In a crossover trial, treatment sequence and assessment period can matter because each participant receives conditions in a sequence. General statistical considerations include whether outcomes differ by period, whether sequence is associated with the outcome, and whether effects of an earlier condition persist into a later period. A washout is part of the registered schedule, but the registry does not report evidence about carryover or how the mixed model handled it. No assumption about the adequacy of the washout can be made from the record alone.

The sponsor’s mixed-model analysis is the analysis identified in the registry as the reported primary analysis. The simple recalculation is useful as a transparent check on the direction and rough scale of the contrast using posted summary statistics, but it is not a substitute for a model that uses the trial’s crossover data and specified analysis structure. The registry does not give enough detail to reproduce that model.

What can planning calculations tell readers?

Planning calculations use an assumed effect and variability to illustrate how much information a future study might need under stated assumptions. They are not observations from this trial and do not describe the probability that the completed trial detected an effect. The posted planning illustration uses the observed effect as its reference and considers fractions of that effect. The corresponding participant counts are scenario-based calculations, not evidence that the trial was designed around those assumptions.

More generally, statistical interpretation combines the estimate, its interval, the analysis method, and the study design. In this trial, the registry gives the principal contrast and uncertainty but leaves important model details and missing-data methods unspecified. Those limits should remain visible when interpreting the reported result.

11. Confidence Intervals and Precision

The sponsor-reported primary estimate is -0.16, with a 95% confidence interval from -0.42 to 0.11. This interval is wide enough to include zero and values on both sides of zero. It therefore does not identify a single direction for the underlying contrast with high precision. The point estimate alone is not an adequate summary: the interval shows the range of effects reasonably compatible with the reported analysis and its assumptions.

The unadjusted recalculation, expressed as apple juice minus purple grape juice, estimates 0.16 with a 95% confidence interval from -0.092 to 0.412. This interval also includes zero and spans both directions. Its endpoints and p-value differ from the sponsor’s mixed-model result because it is a simple recalculation from posted summary statistics, not a reproduction of the sponsor’s model. The recalculated uncertainty is approximate.

Confidence intervals are not guarantees that the true effect lies within the particular interval, nor are they a list of equally likely values. In general, they convey the sampling uncertainty attached to an estimate under the analysis assumptions. Their interpretation depends on how the estimate was obtained, including the model and design.

The individual condition estimates are also accompanied by standard errors: 0.089 for purple grape juice and 0.093 for apple juice. A standard error describes uncertainty in an estimated mean; it is not the spread of individual participant measurements. The registry reports the primary endpoint as a least-squares mean and identifies standard error as its dispersion measure.

The trial’s enrollment was 24, and the confidence intervals reflect the information available in this pilot study. The interval does not establish equivalence, and the registry gives no clinical-importance threshold against which to judge the range. Thus, the most defensible reading is that the estimated contrast is uncertain and the data do not resolve the direction or magnitude with precision. The reported estimate should be interpreted alongside the crossover design and the limited statistical detail in the registry record.

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 display gives planning illustrations in participants per arm for 80% power and participants per arm for 90% power. It is not a count of observed participants or events in the completed trial. The underlying assumption states that the illustration uses a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. It considers an effect equal to the observed effect and smaller fractions of that effect.

In plain language, the 80% power column indicates the number of participants per arm estimated to give an 80% chance of detecting the specified effect under the planning assumptions, if that effect were the true effect and the assumptions held. The 90% power column describes the corresponding planning target for a 90% chance. Neither column is a guarantee for a future study; actual power depends on the true effect, variability, design, analysis, and data quality.

The rows for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect illustrate how the assumed effect size changes the planning requirement. Smaller effects need more participants to detect them with the same target power, all else equal. The listed calculations are based on the observed effect and are not the original rationale for the trial. The registry does not report the trial’s own sample-size justification or original design assumptions.

These figures are planning illustrations, not observed power. They should not be used to infer that the completed trial had a particular probability of detecting its result, nor should they be read as evidence that the sponsor planned the study around the posted calculations.

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 = 0.160; pooled standard deviation σ = 0.446.
2. n = 2 × (1.96 + 0.842)² × 0.446² / 0.160² = 121.9, rounded up to 122 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 <- 0.16                      # observed difference in means
sigma <- 0.445914790066443                     # 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(1043939)
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 = 122 (80% power), 164 (90% power)
 75% of observed effect: n per arm = 217 (80% power), 291 (90% power)
 50% of observed effect: n per arm = 488 (80% power), 653 (90% power)
power.t.test: 122.9 
Simulated power at n = 122 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. Analyses Reported by the Sponsor

The registry’s reported primary result comes from the sponsor-identified mixed models analysis: a difference of least-squares means of -0.16, with a 95% confidence interval from -0.42 to 0.11 and p = 0.25. This is the analysis reported for the trial’s primary endpoint. The registry does not provide the full model specification, so the result cannot be independently reconstructed from the record.

The posted recalculation uses the two condition means and standard errors to make a simple, unadjusted comparison. It reports apple juice minus purple grape juice as 0.16, with a 95% confidence interval from -0.092 to 0.412 and p = 0.214. This contrast is ordered in the opposite direction to the sponsor-reported -0.16 contrast. Once the subtraction order is considered, the point estimates correspond in direction and magnitude, while the uncertainty estimates differ.

The difference between the intervals and p-values should not be interpreted as evidence that one analysis is wrong. The recalculation is an approximation from summary statistics and does not use the individual-level crossover information or reproduce the mixed model. Its calculation of dispersion is approximate. The registry does not state that the sponsor result and recalculation are discrepant; the record’s discrepancy indicator is false.

The recalculation is therefore best treated as a transparent, unadjusted reference for the posted means, while the mixed-model result remains the sponsor’s reported primary analysis. Neither result supports a claim of equivalence, and both intervals include zero. The registry does not report enough detail to assess all modeling assumptions or reproduce the sponsor’s analysis independently.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and three secondary outcomes, and it reports four outcome measures and four analyses. When multiple outcomes or comparisons are tested, the chance of at least one apparently noteworthy result can increase if each is assessed separately. Statistical approaches can address this issue through prespecified testing hierarchies or multiplicity adjustments. The registry does not report whether either approach was used, so the role of multiplicity in interpreting the posted p-values is not clear.

The primary analysis population is identified as intent-to-treat. This label indicates the planned analysis population in the record, but the registry does not define the operational rules for inclusion, such as how participants with incomplete measurements or deviations from the assigned sequence were handled. The number of participants contributing to each outcome analysis and the reasons for any missing measurements are not reported in the registry record.

Missing-data methods can affect estimates and uncertainty, particularly when incomplete observations are related to participant characteristics or outcomes. The registry does not report whether missing outcomes occurred, what assumptions were made about missingness, or whether any imputation or sensitivity analyses were performed. No conclusion about the completeness of outcome data can be drawn from the listed intent-to-treat label alone.

The record names a mixed models analysis for the primary comparison but does not specify its terms, covariance structure, or approach to incomplete repeated measurements. It also does not report an analysis plan detailed enough to determine whether the model was prespecified or how it handled the crossover sequence and periods. These features matter because the trial’s observations are organized across treatment periods.

Interim analyses, stopping rules, and the sponsor’s original sample-size justification are not reported in the registry record. Their absence from the record does not show that a particular procedure was or was not used; it means the record does not supply that information. Overall, the posted results permit a reading of the reported estimates and intervals, but important details about multiplicity, missing data, and analysis implementation remain unavailable.

16. 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.

The registry reports zero serious adverse events and zero other adverse events for the purple grape juice and apple juice groups, with 24 listed as at risk for each category in each group. These are the adverse-event figures recorded for the trial. The registry does not list any serious adverse-event terms.

The figures should be read as event counts within the categories and groups reported, not as proof that no adverse effects occurred. The record does not provide further detail about how events were defined, how they were collected, or the duration over which participants were monitored. It also does not explain whether adverse events were summarized by treatment period or by another grouping convention in the crossover design. The number of deaths is not reported in the registry record.

Because participants received both juice conditions in the crossover schedule, the group entries should not be added together or interpreted as independent sets of participants. The registry’s listed at-risk counts describe the posted safety summaries. These data give a limited description of reported events and do not, on their own, establish comparative safety or rule out uncommon or unrecorded events.

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

The primary result is an estimate of a short-term difference in RH-PAT change between the juice conditions in a randomized crossover pilot study of childhood cancer survivors. The sponsor-reported mixed-model contrast is -0.16, with a 95% confidence interval from -0.42 to 0.11. The interval includes zero, and the reported p-value is 0.25. The data therefore do not resolve a clear difference in the measured endpoint under the reported analysis.

This does not mean that the conditions are equivalent. Equivalence requires an explicit margin and an analysis designed to assess whether the uncertainty excludes differences considered important. The registry does not report an equivalence margin or an equivalence analysis. Nor does a result that is not statistically distinguishable from zero prove that the true effect is zero.

The endpoint is a physiological measure of endothelial function, not a direct measure of cardiovascular events, survival, or long-term health. A change in RH-PAT can inform the stated vascular-function question, but the record does not establish how a given change translates into longer-term clinical outcomes. The registry does not provide a threshold for clinical importance, so the magnitude cannot be classified as clinically meaningful or unimportant from the record alone.

The trial’s pilot phase, enrollment of 24, and short outcome timeframe constrain how broadly the results can be interpreted. The crossover design allows participants to receive each condition, but the registry does not report enough modeling detail to assess how period or carryover effects were handled. Masking is listed as none, which is also relevant context when considering measurement and participant behavior.

The result should therefore be understood as uncertain evidence about a specific measured outcome, over a defined assessment period, in this study population. It is not a conclusion about all childhood cancer survivors, all forms of grape juice, or long-term cardiovascular health. The registry record does not support medical advice or a claim that either juice condition improves or fails to improve health.

18. Why This Trial Matters Statistically

This trial is statistically informative because it illustrates how design, estimation, and uncertainty interact in a small crossover study. The primary endpoint is continuous, and the registry reports both a model-based comparison and condition-level estimates with standard errors. That makes it possible to distinguish the estimated contrast from the uncertainty around it, rather than relying on a single p-value.

The crossover structure is an important part of the analysis question. When participants receive conditions in sequence, measurements may depend on treatment, period, sequence, or effects that persist from an earlier period. The registry reports a washout and a mixed models analysis, but not the model specification. This is a useful reminder that naming a statistical method is not the same as providing enough detail to reproduce or assess it.

The comparison also demonstrates why contrast direction must be explicit. The sponsor-reported estimate and the unadjusted recalculation have opposite signs because the comparisons are written in opposite orders. Without stating which condition is subtracted from which, a reader could mistake a sign change for a disagreement about the result.

Confidence intervals add an essential measure of precision. Here, the reported primary interval includes zero and permits effects in either direction. That information is more informative than treating the p-value as a binary decision, but it still cannot establish equivalence or clinical importance. The registry supplies no threshold for interpreting the magnitude of RH-PAT change.

Finally, the secondary outcomes and sample-size illustrations show why completeness and planning assumptions matter. Results for some listed secondary outcomes are not reported, and the planning figures are illustrations rather than the trial’s original design rationale. Together, these features make the study a useful example of how to interpret a pilot result without overstating what its estimates can establish.

19. 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 study has several limitations specific to the registered design and the information in the record. It is described as a phase 1 pilot with enrollment of 24, so its estimates are imprecise, as reflected in the primary confidence interval. The registry does not report a clinical-importance threshold for the RH-PAT index, making it difficult to judge the practical importance of the estimated contrast.

The crossover design requires attention to the order and timing of treatment periods. A 4 week washout is included in the schedule, but the record does not say whether this interval was considered sufficient or how period, sequence, or carryover effects were addressed in the analysis. These are general methodological considerations for crossover trials, not evidence that such effects occurred in this study.

The study is listed as unmasked. The record does not describe whether outcome assessment was conducted by personnel unaware of the juice condition, or what procedures were used to limit possible influence on measurement. The primary endpoint involves a physiological measurement, but the registry’s masking entry alone cannot establish the presence or absence of measurement bias.

The sponsor’s mixed-model result is reported without sufficient model detail to reproduce the analysis. The recalculated comparison is approximate and unadjusted, and it does not replace the sponsor analysis. The registry also does not report missing-data handling, detailed analysis-population rules, or a multiplicity strategy. Results for myeloperoxidase and high-sensitivity C-reactive protein are not reported in the registry record, leaving the secondary-outcome picture incomplete.

Finally, the outcome timeframe is 4 weeks, and the primary measure is a physiological marker rather than a clinical event. The record does not report longer-term cardiovascular outcomes. These limitations constrain interpretation of the measured short-term comparison and the degree to which it can be generalized beyond the study’s stated population and conditions.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Purple Grape Juice in Improving Vascular Health in Childhood Cancer Survivors — NCT01043939.
• Registry record last updated 2014-12-31; status last verified 2014-12.
• Results first posted 2012-11-29.
• 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.

23. Record Summary

NCT01043939 is a completed phase 1 randomized, open-label crossover pilot trial sponsored by the University of Minnesota. It enrolled 24 childhood cancer survivors and compared purple grape juice with clear apple juice in randomized treatment sequences that included a run-in and washout period.

The primary outcome was change in endothelial function measured by the RH-PAT index over 4 weeks. The sponsor-reported mixed-model contrast was -0.16, with a 95% confidence interval from -0.42 to 0.11 and p = 0.25. An unadjusted recalculation expressed in the reverse contrast direction gave 0.16, with a 95% confidence interval from -0.092 to 0.412 and p = 0.214.

The primary interval includes zero and does not establish equivalence or clinical importance. The registry lists three secondary outcomes, but results for two of them are not reported in the registry record. Important details about model specification, missing data, and multiplicity are also not reported.