Personalized Dietary Management in Type 2 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Personalized Dietary Management in Type 2 Diabetes (NCT05046886), a randomized na study. The primary outcome is Mean Amplitude of Glycemic Excursion (MAGE).

2. Clinical Question

3. Trial Design

The registry describes a randomized, single-masked, parallel-group behavioral trial of dietary management for type 2 diabetes. It lists NYU Langone Health as the sponsor, a status of completed, and a registry enrollment of 294. The brief summary describes a randomized trial of 255 participants with early-stage type 2 diabetes. These are both statements in the record; it does not explain the difference between the enrollment figure and the figure in the summary.

Three groups are named: Standardized, Personalized, and Usual Care Control (UCC). The brief summary says that the first phase used equal allocation across the three groups. It says that in the second phase, described as the current phase, the remaining participants were randomized with equal allocation to Standardized and UCC. The registry does not provide enough information to reconstruct the number assigned to each group in each phase or the reason for the change in allocation.

Standardized involved one-size-fits-all counseling to follow a Mediterranean-style diet. Personalized involved dietary counseling to follow that diet with personalization intended to reduce postprandial glycemic response. UCC received baseline advice about the Mediterranean-style diet and attention control. The record identifies single masking but does not report who was masked or how masking was maintained.

The primary endpoint was MAGE at Month 3. The registry also reports HbA1c at Month 3 as a secondary outcome, with HbA1c listed twice in its outcome descriptions. It reports two posted secondary outcome entries and four outcome measures overall. The registry does not report the trial's original sample-size justification, detailed allocation procedures, or a full protocol in the information summarized by the 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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: 1 UCC participant and 2 Personalized participants missed their 3-month assessment for MAGE and were excluded. Because of this, only 51 participants (out of a total of 52) in the UCC arm, and 36 (of 38) in the Personalized arm were 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.

Population: ll randomized participants that attended at least one intervention session were included in the baseline data analysis. The data were analyzed based on intent-to-treat as specified by the protocol.

6. Primary Endpoint

The registry lists the primary outcome as Mean Amplitude of Glycemic Excursion (MAGE), measured over Month 3.

The primary endpoint, mean amplitude of glycemic excursion (MAGE), describes the amplitude of glucose excursions over time. It is a continuous measure, reported in mg/dL as a mean and standard deviation. The registry says MAGE was evaluated using a continuous glucose monitor (CGM), which captures interstitial glucose readings every 15 minutes for up to 2 weeks from a sensor inserted into the participant's upper arm. The endpoint timeframe is Month 3.

MAGE is used to characterize glucose variation rather than to report a single glucose reading. Repeated CGM readings allow the endpoint to reflect patterns of excursions during monitoring. As a general statistical point, a continuous outcome preserves information about the measured values instead of reducing them to categories. Comparing group means gives a concise description of the endpoint distribution, while standard deviations describe the spread of observed values within each group.

The registry notes that 1 UCC participant and 2 Personalized participants missed the three-month MAGE assessment and were excluded. It reports that 51 UCC participants and 36 Personalized participants were analyzed; the Standardized result is reported for 56 participants. The record does not state whether the endpoint was calculated using a specific algorithm beyond its definition and CGM measurement description.

7. Results Posted in the Registry

• Standardized: mean 76.58 versus 75.07 on control; difference 1.51 (95% CI -6.67 to 9.69), standardized effect d = 0.07; z-test p = 0.717.
• Personalized: mean 75.30 versus 75.07 on control; difference 0.23 (95% CI -9.66 to 10.12), standardized effect d = 0.01; z-test p = 0.963.

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.

HbA1c 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:
  • Standardized: mean 6.75 versus 6.80 on control; difference -0.04 (95% CI -0.31 to 0.22), standardized effect d = -0.06; z-test p = 0.749.
  • Personalized: mean 6.90 versus 6.80 on control; difference 0.10 (95% CI -0.23 to 0.44), standardized effect d = 0.13; z-test p = 0.549.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Standardized and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Personalized and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcome entries concern HbA1c Levels at Month 3. The overall pattern is that the mean differences versus UCC are small in the posted summaries, and both confidence intervals include zero. This is directionally consistent with the primary endpoint comparisons in the limited sense that neither outcome's unadjusted summary comparison clearly separates the intervention mean from the UCC mean. MAGE and HbA1c measure different aspects of glycemia, however, and agreement in their broad pattern does not make them interchangeable or confirm one another.

The HbA1c results are based on analyzed groups that differ somewhat from the MAGE groups, including the reported counts for each outcome. They should therefore be interpreted as outcome-specific summaries rather than as a single identical analysis population. The registry does not explain all differences in the analyzed counts or report a detailed analysis plan for these secondary outcomes.

Unadjusted secondary results carry less weight when several outcomes or comparisons are examined, because the chance of obtaining an apparently notable result can increase with repeated testing. As a general statistical principle, multiplicity procedures or a prespecified hierarchy can help control how multiple comparisons are interpreted. The registry record does not report a multiplicity adjustment, a hierarchy of secondary hypotheses, or reported sponsor analyses. It is consequently not possible to determine from the record whether the secondary findings were confirmatory, exploratory, or interpreted using another prespecified approach.

The safest overall reading is descriptive: the posted HbA1c summaries do not present a clear separation from UCC, and their uncertainty overlaps values on either side of no difference. They add context to the primary MAGE summaries but do not resolve their uncertainty. No causal or clinical conclusion follows from this overall pattern alone.

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

• HbA1c Levels
• HbA1c Levels

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference describe?

A mean difference expresses the gap between two group averages on the outcome's original scale. For the MAGE comparisons, UCC is the reference group. A positive estimate means the reported mean in the named arm is higher than the UCC mean; a negative estimate means it is lower. The Standardized estimate is 1.512 mg/dL, and the Personalized estimate is 0.232 mg/dL. These are descriptive unadjusted contrasts calculated from the posted summary statistics. They do not adjust for other variables.

The estimate is not the only important part of a comparison. Its uncertainty depends on the amount of variation in the outcome and on the number of observations contributing to each group summary. A similar estimated contrast can be more or less precise in different studies. The posted standard deviations and analyzed group sizes are therefore relevant context for interpreting the estimates and their confidence intervals.

What does the standard deviation tell the reader?

A standard deviation describes how dispersed observed measurements are around their group mean. It is not the standard error of the mean and is not the width of a confidence interval. The MAGE standard deviations are 23.3 mg/dL for UCC, 19.46 mg/dL for Standardized, and 23.1 mg/dL for Personalized. Those values describe variation among the observations contributing to each group summary; they do not show the direction or cause of that variation.

As a general statistical explanation, the standard error describes uncertainty in an estimated quantity, such as a group mean. It is influenced by both outcome variability and the amount of information available. The registry's posted summary includes standard errors for the group means, but the comparison estimates and confidence intervals are more direct summaries of the uncertainty in the arm-versus-UCC contrasts.

How should the confidence intervals be read?

A confidence interval gives a range of values compatible with the observed data under the statistical procedure used to construct it. In repeated use of a procedure with its assumptions met, intervals constructed in this way have the stated coverage. It is not correct to treat a particular interval as assigning a probability to the fixed true effect, or as a range that contains most individual measurements.

The MAGE interval for Standardized versus UCC extends from -6.666 to 9.691 mg/dL. The interval for Personalized versus UCC extends from -9.659 to 10.12 mg/dL. Both include zero, so neither interval rules out no mean difference under the calculation represented by these summaries. They also include effects in either direction. The ranges are not sufficiently narrow to support a claim that the groups are practically equivalent; the registry record does not state an equivalence margin.

What does an unadjusted p-value represent?

The p-value measures how unusual data at least as incompatible with a specified null model would be if that model and the assumptions of the test were correct. It is not the probability that the null is true, and it does not quantify the clinical importance of an estimate. The posted unadjusted p-values for the MAGE comparisons are 0.717 and 0.963. They do not indicate a statistically discernible difference under the unadjusted comparisons, but interpretation also requires attention to the estimates and their confidence intervals.

These comparisons use posted group means, standard deviations, and analyzed sample sizes. They are simple unadjusted re-calculations from those summary statistics, rather than a substitute for a trial-specific model. The registry lists no reported analyses and does not describe an adjusted primary analysis. The discrepancy indicator is false, so there is no flagged conflict between the posted comparison results and a sponsor analysis in this record.

Why can over-dispersion matter?

As a general statistical point, over-dispersion occurs when observed variability is greater than a model assumes. If a model understates variability, standard errors can be too small and confidence intervals too narrow, potentially making evidence appear stronger than it is. A continuous endpoint such as MAGE is with means and standard deviations, so those descriptive measures give readers some view of its spread. The registry does not report an over-dispersion assessment or a model-based adjustment for it; there is no basis in the record to say whether over-dispersion was considered in a sponsor analysis.

What is not specified about the analysis?

The registry record does not report the original statistical analysis plan, the planned primary comparison, any covariate adjustment, model diagnostics, interim analyses, or a multiplicity strategy. It also does not describe the handling of missing outcomes beyond noting the missed MAGE assessments and exclusions in UCC and Personalized. Those omissions limit the ability to assess whether the posted unadjusted comparisons match the trial's prespecified analysis. They do not change what the summaries themselves report, but they constrain conclusions about the intended inferential framework.

11. Confidence Intervals and Precision

Precision concerns how tightly the data estimate a group contrast. The MAGE mean difference for Standardized versus UCC is 1.512 mg/dL, with a 95% confidence interval from -6.666 to 9.691 mg/dL. The Personalized versus UCC estimate is 0.232 mg/dL, with a 95% confidence interval from -9.659 to 10.12 mg/dL. Both intervals cross zero and extend to values on either side, so the direction of the underlying mean difference is not pinned down by these estimates.

The interval for Personalized versus UCC covers a wider range of values than the interval for Standardized versus UCC. This is consistent with the smaller analyzed group in Personalized and the observed variability, though the widths should be interpreted as properties of the specific comparisons, not as proof of why they differ. The registry provides no prespecified threshold for a clinically important MAGE difference, so the practical importance of values within the intervals cannot be classified from the record.

A confidence interval is uncertainty about the estimated contrast under the calculation's assumptions, not a prediction interval for an individual participant. Nor does an interval that includes zero demonstrate equivalence. A formal equivalence or non-inferiority question would require a suitable design, a margin established for that purpose, and an analysis aligned to it. The registry record does not report such a margin or analysis.

The precision of these posted estimates should also be considered alongside the missing Month 3 MAGE assessments in UCC and Personalized. The record says those participants were excluded, but does not report a missing-data model or sensitivity analysis. The confidence intervals quantify sampling uncertainty under the simple comparison; they do not account for uncertainty from unreported missing-data assumptions or other possible analysis choices.

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 comparisons of two groups; they are not total event counts. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set as a stated fraction of the observed effect. The registry record does not report the trial's own original design assumptions or sample-size justification, so these figures should be read as planning illustrations based on the observed results.

The 80% power column gives the number of participants per arm that the illustration estimates would be needed to have an 80% chance of detecting the specified effect under the stated assumptions, if that effect were the true effect. The 90% power column makes the corresponding illustration for a 90% chance. These are planning probabilities under assumptions, not guarantees about the outcome of a future study. This is not observed power.

The rows represent planning for 100%, 75%, and 50% of the observed effect. When the effect being targeted is smaller, more participants are needed to distinguish it from random variation under the same assumptions. The projected numbers can become very large when the observed contrast is close to zero, because a smaller target effect is harder to detect. These calculations do not establish that the observed effect is real, important, or likely to recur. They also do not recover the original trial's intended sample size or explain its enrollment decisions.

These illustrations are based on unadjusted observed contrasts and should not be confused with a formal prospective design calculation. A prospective calculation would depend on choices such as the outcome scale, target effect, variability assumptions, allocation, analysis method, and desired power. The registry record does not report the trial's original assumptions for those choices. The planning results therefore describe what follows from the listed illustration assumptions, not what the trial was designed to detect.

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 = 1.512; pooled standard deviation σ = 21.377.
2. n = 2 × (1.96 + 0.842)² × 21.377² / 1.512² = 3,136.2, rounded up to 3,137 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 <- 1.51239073000001                      # observed difference in means
sigma <- 21.3768961000107                     # 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(5046886)
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 = 3,137 (80% power), 4,199 (90% power)
 75% of observed effect: n per arm = 5,576 (80% power), 7,464 (90% power)
 50% of observed effect: n per arm = 12,545 (80% power), 16,794 (90% power)
power.t.test: 3137.1 
Simulated power at n = 3,137 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. Multiplicity, Missing Data and Analysis Populations

The registry lists HbA1c Levels twice among the secondary outcomes and reports two posted secondary outcome entries. It also reports four outcome measures overall, but does not clarify how those measures relate to the repeated HbA1c listing. The record does not identify a prespecified hierarchy among outcomes or comparisons, state how multiplicity was addressed, or report adjusted secondary analyses. When multiple outcomes are tested, the chance of at least one apparently unusual result can increase; this is a general statistical concern, not evidence that a particular posted result is false.

The primary MAGE description states that 1 UCC participant and 2 Personalized participants missed the Month 3 assessment and were excluded. It reports 51 analyzed participants in UCC and 36 in Personalized; the Standardized MAGE summary reports 56 participants. For HbA1c, the posted analyzed counts are 51 for UCC, 55 for Standardized, and 35 for Personalized. The record does not fully explain the different counts across outcomes or provide a complete accounting of all missing measurements.

The registry record does not report whether missing data were imputed, whether a sensitivity analysis was conducted, or whether the endpoint analyses followed an intention-to-treat or per-protocol population. It therefore does not establish how assumptions about missing outcomes might affect the estimates. The primary results describe the participants included in the posted endpoint summaries, rather than a demonstrated result for every randomized participant.

The record also does not report an original statistical analysis plan, an interim-analysis plan, or the sponsor's detailed model and covariate choices. It lists zero reported analyses. Without those details, readers cannot verify whether the posted summary-statistic comparisons reproduce a prespecified analysis or how the trial team handled multiplicity and missingness in its intended inference.

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 registry reports zero serious adverse events in each listed group: UCC, Standardized, and Personalized. The serious-event risk sets are 59 for UCC, 61 for Standardized, and 41 for Personalized. The registry also reports zero other adverse events in each group, with the same group-specific risk-set counts, and zero deaths in all three groups.

These figures describe what was recorded in the registry for the listed groups. A zero count means no event of that category was reported in the group during the recorded period; it does not prove that the risk is absent. The record does not provide event terms for serious events, as no serious terms are listed. It also does not provide detailed information about event definitions, severity grading, duration of follow-up for safety, or causal attribution.

The safety risk sets differ from the analyzed populations for the Month 3 MAGE and HbA1c outcomes. Those denominators should not be treated as the outcome-analysis counts or as a basis for comparing endpoint results. The registry figures alone do not establish comparative safety, and they should be read as reported counts rather than as a complete assessment of all possible harms.

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

The posted results describe mean MAGE and HbA1c values at Month 3 for participants included in the relevant outcome summaries. For MAGE, the Standardized and Personalized group means were close to the UCC mean, and the unadjusted confidence intervals for both mean differences included zero. The HbA1c summaries likewise do not show a clear separation from UCC in the posted unadjusted comparisons. These are descriptions of the registry results, not proof that the interventions have no effect.

Failure to detect a clear difference is not the same as demonstrating that two approaches are equivalent. The MAGE intervals remain compatible with effects in either direction, and the registry does not report an equivalence margin. The posted means also do not establish how individual participants responded: group-level averages can conceal variation across participants, and standard deviations describe that spread without identifying its causes.

The registry record does not include reported sponsor analyses or a detailed statistical analysis plan. It does not report adjustment for baseline characteristics, a missing-data strategy beyond the stated MAGE exclusions, or a multiplicity approach. Accordingly, the posted unadjusted contrasts should not be treated as a complete account of the trial's intended statistical inference.

The results also do not answer whether dietary counseling changes outcomes over a longer period, whether results apply to populations beyond those described in the registry, or whether any observed difference is clinically important. The primary endpoint is reported at Month 3, and the record does not establish a broader time course. No medical advice or treatment recommendation follows from these registry summaries alone.

17. Why This Trial Matters Statistically

This trial is statistically informative as an example of why effect estimates and uncertainty matter more than a binary reading of a p-value. The posted MAGE estimates are near zero, but their confidence intervals still cover values below and above zero. That combination does not support a confident claim about the direction of a difference, and it is not evidence of equivalence. A reader needs the estimates, their precision, the outcome variability, and the analysis context together.

The trial also illustrates the distinction between a registry enrollment figure and the numbers contributing to particular endpoint summaries. The record lists enrollment of 294, while its brief summary describes 255 participants; it does not explain the difference. The reported endpoint analysis groups have their own counts, and some MAGE assessments were missed. These figures answer different questions and should not be conflated.

Finally, the registry's planning illustrations are not the original sample-size rationale. They are derived from observed effects under stated assumptions, and smaller target effects require more participants. When observed contrasts are close to zero, planning calculations based on those contrasts can produce large illustrative sample sizes. This underscores why prospective sample-size planning should be grounded in a justified target effect and design assumptions, rather than interpreted as a retrospective verdict on whether a trial was adequately powered.

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 trial-specific limitations of interpretation follow from the registry record. The brief summary describes a two-phase randomization approach: equal allocation among three groups in the first phase, followed by allocation between Standardized and UCC in the second phase. The record does not report how many participants entered each phase or provide enough detail to assess the consequences of the change in allocation. It also does not explain why the registry enrollment is 294 while the brief summary describes 255 participants.

The primary endpoint is assessed at Month 3, and the record identifies missed MAGE assessments in UCC and Personalized that were excluded. It does not state how missing outcomes were otherwise handled or provide sensitivity analyses. The reported HbA1c analysis counts also differ from the MAGE counts, without a full explanation in the registry record.

Statistical reporting is limited: the registry lists zero reported analyses and does not report the trial's original analysis plan, covariate adjustment, multiplicity approach, or original sample-size assumptions. The single-masking designation is recorded, but who was masked is not reported. The record also does not specify an equivalence margin, so close estimates cannot be interpreted as proof of equivalence.

These limitations do not invalidate the posted descriptive results, but they restrict how far readers can generalize beyond the analyzed groups or infer how the investigators intended to handle uncertainty, missingness, and multiple outcomes.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Personalized Dietary Management in Type 2 Diabetes — NCT05046886.
• Registry record last updated 2026-06-18; status last verified 2026-05.
• Results first posted 2026-06-18.
• 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 record describes a completed, randomized, single-masked, parallel-group behavioral trial of dietary management for type 2 diabetes, sponsored by NYU Langone Health. It names Standardized, Personalized, and Usual Care Control groups and describes a two-phase allocation process in the brief summary.

The primary endpoint is Month 3 MAGE measured by CGM. The posted unadjusted mean differences versus UCC are close to zero, with confidence intervals that include zero and extend in both directions. Month 3 HbA1c results are also posted as secondary outcomes. The record reports zero serious adverse events, zero other adverse events, and zero deaths in each group.

The registry does not report sponsor analyses, the original sample-size rationale, a detailed analysis plan, or methods for multiplicity and missing-data handling. The results should therefore be read as posted endpoint summaries with uncertainty, rather than as a complete account of the trial's prespecified inference.