Effect of mTOR Inhibition and Other Metabolism Modulating Interventions on the Elderly: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of mTOR Inhibition and Other Metabolism Modulating Interventions on the Elderly (NCT02874924), a randomized phase 2 study. The primary outcome is Immunological Responses.

2. Clinical Question

The trial’s background rationale concerns age-related decline in immune response. Its stated purpose was to test whether rapamycin might improve life functions in humans, with immune, cognitive, and functional consequences among its areas of interest. That rationale explains the choice of outcomes, but it does not establish that a change in the measured endpoint would translate into a change in infectious disease, cancer, or other clinical outcomes.

3. Trial Design

The registry classifies this as a Phase 2, randomized, quadruple-masked, parallel trial. It lists an enrollment of 34 and a completed status. The record gives a start date of 2016-06 and primary completion date of 2018-09. It identifies The University of Texas Health Science Center at San Antonio as the sponsor.

The main posted comparison is rapamycin against placebo, with both regimens described as once-daily treatment for 8 weeks. The registry also lists a separate rapamycin-alone arm for cardiovascular effects, described as having no placebo control. That arm is not part of the primary T-cell analysis: the endpoint description explicitly says that T-cell function was not analyzed in the cardiovascular arm. Its presence means that the study’s listed arms do not all contribute to every posted outcome.

The primary outcome is immunological responses, measured as the number of T cells per millimeter cubed at 8 weeks. The result is reported as a mean and standard deviation for each contributing arm. Physical performance and cognitive function are listed as secondary outcomes, also measured at 8 weeks.

The primary outcome counts differ from the registry’s enrollment figure, and the outcome-specific group counts are reported with each result. These are analysis counts for those outcomes, not a description of why individuals may be absent from a particular result. Reasons for any difference, the analysis population definition, and the handling of missing outcome data are not reported in the registry record.

Although the trial is described as quadruple-masked, the record does not identify which participant, clinician, assessor, or other roles were masked, nor does it describe the practical masking procedures. The original sample-size assumptions and detailed statistical plan are also not reported in the registry record. Accordingly, the planning illustrations accompanying the posted outcomes should not be read as the trial’s original design justification.

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:

Analysis population for the primary outcome, as defined in the registry: In the cardiovascular arm, no T cell function was analyzed.

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 Immunological Responses, measured over 8 weeks.

The primary endpoint is titled immunological responses. It measures T-cell function as the number of T cells per millimeter cubed, with the outcome assessed at 8 weeks. The registry reports a mean and standard deviation for the rapamycin and placebo groups. It notes that T-cell function was not analyzed in the cardiovascular arm, so that arm does not contribute a reported result for this endpoint.

T-cell measures are relevant to the trial’s stated interest in age-related immune responsiveness: the registry background describes declining ability to mount an effective immune response with age. Measuring a cellular immune marker can provide a way to compare immune-related biology between randomized groups. However, a group difference in this measure is not itself a direct measure of protection from infection, cancer, or other clinical events. The record does not report a threshold for a meaningful change, explain whether higher or lower values were considered preferable, or provide details of the assay and its measurement properties.

Because the outcome is continuous, the reported group means describe the average measured value, while the standard deviations describe variability among observations within each group. The comparison estimates a difference between group means. That estimate should be interpreted alongside its uncertainty and the sponsor’s separately reported analysis, rather than as a complete account of the study’s broader clinical aims.

7. Results Posted in the Registry

• Rapamycin: mean 8.33 versus 11.24 on control; difference -2.91 (95% CI -6.15 to 0.33), standardized effect d = -0.69; z-test p = 0.079.

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.

Physical Performance

• 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:
  • Rapamycin: mean 7.75 versus 7.17 on control; difference 0.58 (95% CI -0.30 to 1.46), standardized effect d = 0.52; z-test p = 0.199.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Rapamycin and the control. The interval gives the range of effects that remain compatible with the data.

Cognitive Function

• 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:
  • Rapamycin: mean 7.20 versus 6.92 on control; difference 0.28 (95% CI -2.96 to 3.52), standardized effect d = 0.06; z-test p = 0.866.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Rapamycin and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes add physical performance and cognitive function to the immune-focused primary result. Across the two posted comparisons, the estimated directions are not uniform: one favors a higher observed mean in the rapamycin group and the other is also slightly higher, while the primary estimate is lower in that group. The intervals for both secondary comparisons include no difference, so they do not provide precise evidence of a consistent pattern across domains.

These outcomes relate to the primary result by broadening the questions asked about function and cognition, but they measure different constructs and use different scales. Their estimates should not be pooled informally with the T-cell measure or treated as confirmation of an immune finding. The registry does not report sponsor analyses for these secondary outcomes, and the posted group summaries do not establish a clinically meaningful threshold for either measure.

Unadjusted secondary results carry less weight when several outcomes are examined because each additional comparison creates more opportunities for chance findings. A prespecified multiplicity strategy can account for that concern, but such a strategy is not reported in the registry record. Without it, isolated secondary estimates are best regarded as exploratory rather than as standalone confirmatory evidence.

The secondary outcomes also share the limitations of the short assessment period and outcome-specific analysis counts. The registry record does not state how missing secondary measurements were handled or whether the outcomes were prioritized in advance. Consequently, the overall pattern is useful for describing the range of measured results, but it does not establish a broad or durable effect across physical, cognitive, and immune functions.

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

• Physical Performance
• Cognitive Function

9. Statistical Interpretation

10. Statistical Methods Explained

The primary result is a comparison of two group means for a continuous outcome. A mean describes the average observed T-cell count in a group. The standard deviation describes how spread out individual observations are around that group’s mean; it is not the uncertainty of the mean itself. A larger standard deviation indicates more variation among measured observations.

The recalculated mean difference is formed from the posted group means, with the rapamycin mean compared against the placebo mean. A negative estimate means the observed mean was lower in the rapamycin group under that subtraction convention. The estimate does not, by itself, indicate whether the difference is important in clinical terms. The registry does not report a clinically meaningful difference threshold for this endpoint.

The recalculation uses the posted means, standard deviations, and outcome counts to produce an unadjusted comparison. It is not an adjusted model and does not incorporate participant-level data. Such a calculation can be a useful check on the scale and uncertainty of a reported result, but it cannot reproduce procedures that require individual records, covariate adjustments, or other information absent from the group summaries. The registry does not report an adjusted primary model in the listed analysis details.

A t-test evaluates the compatibility of observed group differences with a model in which the groups have the same mean, under the assumptions of the chosen test. A two-sided test allows the observed difference to be evaluated in either direction. Its p-value describes how unusual the data would be under the test’s null model; it is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of a difference. The sponsor’s analysis is described as a two-sided t-test, while the registry’s primary result is separately labeled as an equivalence analysis.

Equivalence testing asks a different question from ordinary difference testing. Instead of asking whether the evidence is inconsistent with exactly no difference, it asks whether the plausible difference is contained within prespecified bounds regarded as acceptably small. Those bounds are essential to interpreting an equivalence claim. The equivalence margins and their rationale are not reported in the registry record, so the reported label and test statistics cannot be used to independently assess whether equivalence was established.

A confidence interval gives a range of values compatible with the data and the statistical model at the stated confidence level. It conveys estimation uncertainty, not a guarantee that the true value lies within the interval. For a difference, an interval spanning zero includes no difference as one compatible possibility. An interval can also include values in either direction, making the estimate less conclusive about direction. The width matters: broader intervals indicate less precision than narrower intervals, all else being equal.

The posted planning illustrations use the observed effect as a reference and show hypothetical participant requirements under stated assumptions. They are not the actual trial design calculations. The registry’s planning assumptions specify a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The displayed scenarios use the full observed effect, 75% of the observed effect, or 50% of the observed effect. Smaller target effects require more participants under these assumptions because they are harder to distinguish from random variation.

Over-dispersion is a general concern when data vary more than a chosen model expects. If a model understates variability, it can make uncertainty appear smaller than it is. The posted primary endpoint is summarized as a continuous measure with standard deviations, and the record does not report an over-dispersion model or evidence that over-dispersion was assessed. This concept should not be mistaken for a finding about these data.

Randomization is intended to support comparable groups on average, but the registry record alone does not show how the sequence was generated, how assignments were concealed, or whether the analysis preserved the randomized comparison. Quadruple masking is listed, yet the masked roles and methods are not described. Allocation procedures and masking details are therefore not independently assessable from this record.

The outcome counts indicate which observations entered the posted group summaries, but the record does not state whether analyses followed intention-to-treat, per-protocol, or another population definition. It also does not describe missing-data methods, imputation, exclusions, or sensitivity analyses. These omissions matter because a group summary is most straightforward to interpret when the analysis population and treatment of incomplete outcomes are clear.

11. Confidence Intervals and Precision

The recalculated primary mean difference is -2.91 cells/mm^3, and its confidence interval extends from below zero to above zero. That span indicates uncertainty about the direction and size of the underlying difference: values consistent with a lower mean in the rapamycin group and values consistent with a higher mean are both included. The unadjusted p-value is 0.079. Neither the p-value nor the interval can establish that the groups are equivalent.

The sponsor’s reported analysis gives a net mean difference of -1.81 and a 95% confidence interval from -8.48 to 4.86. This interval also crosses zero and is wide enough to include differences in either direction. Its stated p-value is 0.56. The sponsor’s interval and the recalculated interval arise from different reported estimates; the registry record does not explain the difference. They should not be combined or treated as interchangeable estimates.

In general, confidence intervals help distinguish a precise estimate from one that remains uncertain. A narrow interval constrains the range of effects compatible with the data more than a broad interval does. Here, the primary result’s uncertainty leaves a substantial range of possible differences, and the record does not supply a clinical threshold against which to judge the interval’s endpoints. Thus, statistical uncertainty cannot be translated into a judgment about clinical importance from this record alone.

The outcome-specific counts are limited, and the standard deviations indicate variability in the measured outcome. Both the amount of data and the spread of observations affect the precision of a mean difference. The registry does not report a confidence interval for the group means themselves, but it does report an interval for the sponsor’s comparison and enables an unadjusted interval recalculation from posted summary statistics. Precision should be considered alongside the study’s short, eight-week outcome timeframe and the absence of reported long-term 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 planning figures are participants per arm for 80% power and participants per arm for 90% power. They are not total event counts: the record’s convention is participants per arm for outcomes other than time-to-event outcomes. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The scenarios target the full observed effect, 75% of the observed effect, or 50% of the observed effect.

The 80% power column represents the hypothetical number of participants per arm needed to have an 80% chance of detecting the specified effect under those assumptions, if that effect and the model assumptions were correct. The 90% column uses a higher target probability of detection, so it generally calls for more participants per arm. These are planning illustrations computed from the observed effect, not the trial’s own original design assumptions; the original design assumptions are not reported in the registry record.

The scenarios also show why the assumed effect size matters. Planning to detect a smaller fraction of the observed effect requires more participants per arm than planning for the full observed effect. This reflects the general statistical principle that subtle differences are harder to distinguish from random variation. The observed effect in a small trial can itself be uncertain, so using it as a planning reference does not guarantee that a future study would see the same effect.

These figures are not observed power. They describe hypothetical planning requirements under stated assumptions, rather than the probability that the completed trial’s result is true or the probability that the trial detected an effect. They should be read as illustrations of how sample size changes with the target effect and desired power, not as evidence about the validity of the outcome.

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 = -2.910; pooled standard deviation σ = 4.188.
2. n = 2 × (1.96 + 0.842)² × 4.188² / -2.910² = 32.5, rounded up to 33 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 <- -2.91                      # observed difference in means
sigma <- 4.1877486947565                     # 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(2874924)
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 = 33 (80% power), 44 (90% power)
 75% of observed effect: n per arm = 58 (80% power), 78 (90% power)
 50% of observed effect: n per arm = 131 (80% power), 175 (90% power)
power.t.test: 33.5 
Simulated power at n = 33 per arm: 0.797 (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 reports the sponsor’s primary analysis as a two-sided t-test for a net mean difference. It gives an estimate of -1.81, a 95% confidence interval from -8.48 to 4.86, and p = 0.56, and labels the analysis as equivalence. The record does not report the equivalence margin or its rationale, so the statistical evidence for equivalence cannot be independently assessed from these details alone.

The unadjusted recalculation from the posted group means and standard deviations gives a different estimate, -2.91, and an unadjusted p-value of 0.079. This calculation is a simple comparison of posted summary statistics, not a reconstruction of the sponsor’s full analysis. The registry record does not explain why the estimate and p-value differ, and it does not provide the participant-level data or full analysis details needed to investigate the difference.

These two results should be kept distinct: the sponsor’s result is the analysis reported by the registry, while the recalculation is a descriptive check based on the posted summaries. The discrepancy flag is false, but the numerical results are still not identical. Neither the sponsor’s p-value nor the recalculated p-value establishes clinical equivalence, and the record lacks the margin required to interpret the equivalence claim fully.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and two secondary outcomes, but it does not report a multiplicity plan. When researchers test several outcomes, the chance of at least one apparently unusual result can increase. Procedures such as adjusting significance criteria or identifying a limited hierarchy of confirmatory outcomes can address this issue. Whether any such procedure was prespecified or used is not reported in the registry record. The unadjusted secondary results should therefore be interpreted cautiously.

The record also does not provide a full statistical analysis plan, details of interim analyses, or a sample-size justification for the original trial. These items are not evidence that a particular procedure was or was not used; they are simply not reported in the registry record. The planning illustrations based on observed effects do not fill that gap, because they are not the original trial design assumptions.

Outcome-specific group counts are reported, but the record does not explain the analysis populations or why the counts vary across outcomes. It does not say whether participants were analyzed according to randomized assignment, whether exclusions occurred, or whether the primary analysis was intention-to-treat or per-protocol. Those definitions affect what population the estimates describe.

Missing-data details are also not reported. There is no description of how incomplete measurements were handled, whether imputation was used, or whether sensitivity analyses assessed the effect of missing observations. Without this information, the potential influence of missingness on the posted group summaries cannot be evaluated from the registry record.

The registry’s masking and randomization labels provide broad design information, but sequence generation, allocation concealment, masked roles, and procedures for maintaining masking are not described. These missing methods details limit assessment of potential bias. They do not establish that bias occurred; they mark questions the record does not answer.

16. 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.

Most frequent non-serious adverse event terms

The adverse-event record reports serious adverse events among 0 participants at risk of 14 in the rapamycin group and 0 participants at risk of 14 in the placebo group. The cardiovascular arm reports 0 serious adverse events among 6 at risk. These are the posted serious-event counts for the groups and do not describe event severity beyond the registry’s serious classification.

For other adverse events, the registry reports 2 affected participants among 14 at risk in the rapamycin group, 0 among 14 at risk in the placebo group, and 0 among 6 at risk in the cardiovascular arm. No deaths are reported in any of the listed groups. The record does not provide event terms for serious adverse events, and the serious-event terms list is empty.

These counts are descriptive. Zero reported serious events does not prove that serious harms cannot occur, particularly when the observed group counts are limited. The record does not report event definitions, severity grading for other events, exposure-adjusted rates, or a detailed comparison of adverse-event risks. The cardiovascular arm also lacks a placebo control, so its counts should not be interpreted as a controlled comparison.

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

The posted primary result describes an eight-week comparison of mean T-cell counts in the rapamycin and placebo groups. The unadjusted recalculation estimates a lower mean in the rapamycin group, but its confidence interval includes values on either side of no difference. The sponsor’s reported analysis gives a different estimate and is labeled as an equivalence analysis, but the registry record does not report the margin needed to evaluate that claim. The evidence therefore does not support a simple conclusion of either a meaningful difference or demonstrated equivalence.

The trial also reports physical-performance and cognitive outcomes, but these do not yield a uniform pattern across measured domains, and their uncertainty intervals include no difference. They offer additional descriptions of the outcomes measured rather than a definitive conclusion about broad changes in function or cognition. The record does not report long-term follow-up for these outcomes.

The registry’s background discusses immune decline with age and laboratory findings that motivated the human trial. Those points explain the rationale; they are not results from this clinical comparison. The posted data do not determine whether rapamycin changes the risk of infection, cancer, lifespan, or healthspan. The measured cellular endpoint is not itself a clinical event, and the record does not report a validated threshold linking its change to those outcomes.

Likewise, these results do not justify medical advice or a treatment recommendation. Interpretation is constrained by outcome-specific counts, uncertainty in the estimates, missing details about analysis populations and missing data, and the lack of reported equivalence margins and multiplicity procedures. The findings should be read as registry-reported results for the specified measures and timeframe, not as a definitive assessment of all potential benefits or harms.

18. Why This Trial Matters Statistically

This trial is statistically instructive because it brings together a randomized comparison, a continuous biological endpoint, a sponsor-reported equivalence analysis, and an unadjusted recalculation from posted group summaries. These are related but not interchangeable forms of evidence. The distinction matters: a recalculation can check the arithmetic implied by summary data, while a sponsor analysis may use a different procedure or analysis population that the registry record does not fully describe.

The primary estimate illustrates why direction alone is not enough. Its sign describes which group had the lower observed mean under the subtraction convention, while the confidence interval describes uncertainty about the difference. Because that interval crosses zero, the observed direction does not settle whether the underlying difference is positive or negative. A p-value also cannot replace an assessment of interval width or clinical relevance.

The equivalence label highlights an important design principle. Showing that a conventional test does not identify a difference is not the same as demonstrating that differences are small enough to be unimportant. Equivalence requires prespecified margins, and those margins are not reported in this record. Readers should distinguish a nonsignificant difference test from an equivalence conclusion.

The secondary outcomes further illustrate the consequences of examining multiple measures. A pattern across domains can be informative, but unadjusted results require caution when the multiplicity strategy is unknown. Finally, planning figures based on the observed effect show how sample-size needs depend on the target effect and desired power; they do not retrospectively establish whether the trial was adequately designed. Together, these features make clear why effect estimates, uncertainty, analysis details, and design assumptions must be read together.

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 registry record leaves important endpoint details unspecified. It does not describe the T-cell assay, measurement procedures, or a threshold for a clinically meaningful change. The primary outcome is a cellular measure, so the record does not establish how its observed differences relate to clinical outcomes such as infection or cancer.

The primary outcome is reported for the rapamycin and placebo groups, while the cardiovascular arm has no T-cell analysis. The record does not explain the outcome-specific analysis populations or the reasons that group counts differ across measures. It also does not report missing-data handling, exclusions, or sensitivity analyses. These gaps limit assessment of how representative the posted summaries are of the randomized groups.

The sponsor’s reported equivalence analysis lacks a reported equivalence margin. The simple recalculation differs numerically from the sponsor’s result, and the registry does not explain the difference or provide enough detail to reproduce the sponsor’s analysis. The secondary analysis plan and any multiplicity adjustment are also not reported, limiting the strength of conclusions drawn from those outcomes.

The intervention period and posted outcome timeframe are 8 weeks. The record does not report longer-term results for the outcomes discussed, so durability cannot be assessed. It also lists a cardiovascular arm without a placebo control; its safety counts cannot support a controlled comparison. Although the trial is listed as randomized and quadruple-masked, detailed sequence, concealment, and masking procedures are not reported in the registry record.

These limitations identify uncertainty in what can be concluded from the record; they do not demonstrate that a particular bias or methodological problem occurred.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Effect of mTOR Inhibition and Other Metabolism Modulating Interventions on the Elderly — NCT02874924.
• Registry record last updated 2018-12-04; status last verified 2018-03.
• Results first posted 2018-12-04.
• 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

The registry record identifies NCT02874924 as a completed Phase 2, randomized, quadruple-masked, parallel trial sponsored by The University of Texas Health Science Center at San Antonio. It lists enrollment of 34, a start date of 2016-06, and primary completion on 2018-09. The trial focused on aging and described rapamycin and placebo regimens taken once daily for 8 weeks, alongside a rapamycin-alone cardiovascular arm without placebo control.

The primary outcome was T-cell function measured as cells per millimeter cubed at 8 weeks; the cardiovascular arm did not have T-cell function analyzed. Physical performance and cognitive function were listed as secondary outcomes. The registry reports the sponsor’s primary equivalence analysis and group-level outcome summaries, but does not report the equivalence margin, original design assumptions, multiplicity plan, missing-data procedures, or detailed analysis populations. The results therefore require interpretation in light of their uncertainty and the methodological details not reported in the registry record.