Comparison of Efficacy of Vitamin D and Vitamin D-calcium Fortified Yogurt Drink in Diabetic Patients: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparison of Efficacy of Vitamin D and Vitamin D-calcium Fortified Yogurt Drink in Diabetic Patients (NCT01229891), a randomized phase 2 study. The primary outcome is Serum 25-hydroxyvitamin D.

2. Clinical Question

3. Trial Design

The registry describes a completed, randomized, double-blind, parallel phase 2 trial sponsored by the National Nutrition and Food Technology Institute. The study start is listed as 2009-10 and primary completion as 2010-03. Enrollment is listed as 90. These registry entries describe the trial record; they do not establish how many participants completed follow-up or contributed to each outcome.

Three arms are described: plain yogurt drink, vitamin D-fortified yogurt drink, and vitamin D-calcium-fortified yogurt drink. Each arm's posted outcome summaries use 30 participants. The plain-drink arm is the comparator for the posted recalculated pairwise comparisons. Randomization, masking, and parallel-group model are identified in the record, but the procedures used to generate the allocation sequence, conceal allocation, maintain masking, or handle deviations from assigned treatment are not reported in the registry record.

The primary outcome is serum 25-hydroxyvitamin D at 12-week follow-up, reported as a mean with standard deviation. Secondary outcomes include fasting serum glucose, insulin, hemoglobin A1c, triglyceride, total cholesterol, LDL, and HDL. Although the registry lists eight outcome measures, only three outcomes have posted numerical results in the record: the primary outcome and three secondary outcomes. Other outcome results and details about the analysis population are not reported in the registry record.

The registry does not report the trial's original sample-size justification, planned statistical model, handling of missing observations, or prespecified analysis population. Those details cannot be inferred from the posted group summaries.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Serum 25-hydroxyvitamin D, measured over 12-week.

The primary endpoint is serum 25-hydroxyvitamin D, measured in nmol/L at 12-week follow-up. It is reported as a mean and standard deviation for each arm. As a general clinical measurement, circulating 25-hydroxyvitamin D is used to assess vitamin D status; the outcome therefore captures a biochemical marker related to the vitamin D content of the assigned drinks. It is not itself a measure of every health outcome that could matter to a person with type 2 diabetes.

The posted arm means are 45.6 for plain yogurt drink, 76.2 for vitamin D-fortified yogurt drink, and 78.4 for vitamin D-calcium-fortified yogurt drink. The recalculated unadjusted mean difference is 30.6 for the vitamin D-fortified drink compared with plain drink, with a 95% confidence interval from 11.44 to 49.76. For the vitamin D-calcium-fortified drink compared with plain drink, it is 32.8, with a 95% confidence interval from 10.96 to 54.64.

The endpoint provides an interpretable comparison of the measured marker at the stated follow-up time. The registry does not report a change-from-baseline estimate, baseline values, or a longer-term measurement. Accordingly, the posted result describes the endpoint summaries at 12-week follow-up, not the course of the marker over time or the persistence of any difference.

7. Results Posted in the Registry

• Vitamin D-fortified Yogurt Drink: mean 76.20 versus 45.60 on control; difference 30.60 (95% CI 11.44 to 49.76), standardized effect d = 0.81; z-test p = 0.002.
• Vitamin D-calcium Fortified Yogurt Drink: mean 78.40 versus 45.60 on control; difference 32.80 (95% CI 10.96 to 54.64), standardized effect d = 0.76; z-test p = 0.003.

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.

Fasting Serum Glucose (FSG)

• 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:
  • Vitamin D-fortified Yogurt Drink: mean 171.20 versus 203.30 on control; difference -32.10 (95% CI -63.40 to -0.80), standardized effect d = -0.52; z-test p = 0.044.
  • Vitamin D-calcium Fortified Yogurt Drink: mean 174.30 versus 203.30 on control; difference -29.00 (95% CI -58.18 to 0.18), standardized effect d = -0.50; z-test p = 0.051.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Vitamin D-fortified Yogurt Drink than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Vitamin D-calcium Fortified Yogurt Drink and the control. The interval gives the range of effects that remain compatible with the data.

Insulin

• 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:
  • Vitamin D-fortified Yogurt Drink: mean 6.50 versus 10.80 on control; difference -4.30 (95% CI -6.60 to -2.00), standardized effect d = -0.95; z-test p = <0.001.
  • Vitamin D-calcium Fortified Yogurt Drink: mean 6.40 versus 10.80 on control; difference -4.40 (95% CI -6.66 to -2.14), standardized effect d = -0.99; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Vitamin D-fortified Yogurt Drink than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Vitamin D-calcium Fortified Yogurt Drink than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Hemoglobin A1c (HbA1c)

• 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:
  • Vitamin D-fortified Yogurt Drink: mean 7.00 versus 8.70 on control; difference -1.70 (95% CI -2.66 to -0.74), standardized effect d = -0.89; z-test p = <0.001.
  • Vitamin D-calcium Fortified Yogurt Drink: mean 7.80 versus 8.70 on control; difference -0.90 (95% CI -1.74 to -0.06), standardized effect d = -0.54; z-test p = 0.037.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Vitamin D-fortified Yogurt Drink than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Vitamin D-calcium Fortified Yogurt Drink than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary results cover fasting serum glucose, insulin, and HbA1c. For each, the arm means are lower in both fortified-drink groups than in the plain-drink group. The intervals and unadjusted p-values, however, do not convey equally strong statistical separation across every comparison. The registry also lists triglyceride, total cholesterol, LDL, and HDL as secondary outcomes, but numerical results for those outcomes are not reported in the registry record.

This pattern can be considered alongside the primary result, which is a measured vitamin D marker and is higher in both fortified-drink arms than in the plain-drink arm. The secondary markers concern glycemic and metabolic measures rather than the primary marker itself. Their pattern may be relevant to the study's broader stated aim, but these comparisons do not establish that the primary endpoint caused any secondary differences. The record does not report a formal mediation analysis or other analysis linking changes in the primary marker to changes in secondary outcomes.

Secondary findings carry less weight when several outcomes and pairwise comparisons are examined without a reported multiplicity strategy. With multiple opportunities to observe a small p-value, an unadjusted result can be more likely to appear notable by chance. The registry does not report which secondary outcomes or comparisons were designated in advance as key, whether an order of testing was specified, or whether multiplicity was controlled. Thus, the secondary results are best treated as exploratory evidence rather than a set of independent confirmatory conclusions.

The registered outcome list is broader than the outcomes with posted numerical results. This incomplete reporting limits assessment of the full pattern across the planned outcome set. In particular, the absence of numerical results for the listed lipid measures means that no conclusion about those measures can be drawn from this record.

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

• Fasting Serum Glucose (FSG)
• Insulin
• Hemoglobin A1c (HbA1c)
• Serum Triglyceride (TG)
• Serum Total Cholesterol (Tchol)
• Serum Low Density Lipoprotein (LDL)
• Serum High Density Lipoprotein (HDL)

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference represent? A mean difference is the first arm's average minus the comparator arm's average, following the comparison direction used in the posted results. For the primary endpoint, positive estimates mean the fortified-drink arm's mean is higher than the plain-drink arm's mean. For fasting serum glucose, insulin, and HbA1c, negative estimates mean the fortified-drink arm's mean is lower. The estimate retains the endpoint's original units, such as nmol/L for serum 25-hydroxyvitamin D or percent for HbA1c.

What do the arm summaries tell us? Each arm is summarized by a mean and standard deviation. A mean describes the center of the observed values, while the standard deviation describes their spread. The standard deviation is not the uncertainty in the estimated mean difference; that uncertainty also depends on the number of observations contributing to each summary. The registry posts 30 participants for each arm's primary and displayed secondary outcome summaries. The record does not say whether these are all randomized participants, completers, or an outcome-specific analysis set.

How were the displayed comparisons obtained? The estimates are unadjusted recalculations from the posted summary statistics. They compare each fortified-drink arm with plain yogurt drink and use the posted means and standard deviations. No covariate adjustment or model-based result is posted. Because these are summary-statistic recalculations, they cannot reproduce analyses requiring individual-level data, such as adjustment for baseline values, evaluation of repeated measures, or detailed handling of missing observations. Sponsor-reported analyses are not reported in the registry record.

What is a confidence interval? A confidence interval expresses uncertainty around an estimated difference under the assumptions of the calculation. It gives a range of values compatible with the data and method, rather than a guarantee that the true value lies inside that particular interval. For these pairwise comparisons, intervals crossing zero include both a difference in one direction and no difference under the interval's scale. Intervals that remain on one side of zero indicate greater statistical separation from zero under the same calculation; they do not establish clinical importance.

How should p-values be understood? A p-value describes how unusual results at least as incompatible with a null comparison would be under a specified statistical model, if the null model and its assumptions held. It is not the probability that the null hypothesis is true, nor a measure of the size or practical importance of an effect. The posted p-values for the recalculated comparisons are unadjusted. The registry does not report a prespecified multiplicity procedure or sponsor analysis plan, so these values should not be interpreted as if adjustment across outcomes and comparisons had been established.

Why can dispersion and assumptions matter? In a general comparison of means, the estimated standard error depends on within-arm variability and the amount of information in each arm. Greater dispersion makes an estimate less precise when other features are held constant. A normal approximation can be useful for planning or inference in suitable settings, but its adequacy depends on the data and design. Individual participant data are not available in the registry record, so distributional features, outliers, and model assumptions cannot be independently assessed. The posted standard deviations are not evidence by themselves that the outcome distributions are normal.

What is not established by these calculations? The record does not report baseline-adjusted effects, change scores, confidence intervals from the trial sponsor's model, or methods for missing data. Nor does it report whether analysis followed intention-to-treat principles, how protocol deviations were handled, or whether participants and investigators remained masked. Those omissions prevent a full appraisal of the planned analysis and how it was implemented. The posted recalculations are useful for describing the numerical separation and its approximate precision, but they cannot fill in unreported design or analysis decisions.

11. Confidence Intervals and Precision

The confidence intervals show how much uncertainty accompanies the recalculated mean differences. For serum 25-hydroxyvitamin D, the vitamin D-fortified comparison has an estimate of 30.6 and a 95% confidence interval from 11.44 to 49.76. The vitamin D-calcium-fortified comparison has an estimate of 32.8 and a 95% confidence interval from 10.96 to 54.64. Both intervals are entirely above zero, while still spanning a range of possible difference sizes.

For secondary outcomes, intervals vary in relation to zero. The fasting serum glucose comparison for vitamin D-fortified drink has a confidence interval from -63.4 to -0.798, whereas the vitamin D-calcium comparison extends from -58.18 to 0.175. The insulin intervals are -6.595 to -2.005 and -6.659 to -2.141. For HbA1c, the intervals are -2.664 to -0.737 and -1.745 to -0.056. These intervals describe the unadjusted recalculations, not sponsor-reported model estimates.

Precision is not the same as importance. A relatively narrow interval can still include values whose practical relevance is uncertain, and a point estimate does not convey its uncertainty alone. Clinical interpretation would require context about meaningful differences and the population, neither of which is specified sufficiently in the registry record. The summary data also do not allow assessment of the distribution of individual responses or whether a small number of observations strongly influence the means.

Confidence intervals are calculated under statistical assumptions. As the original analysis plan and individual-level data are not reported in the registry record, the posted intervals should be treated as approximate, unadjusted comparisons based on summary statistics.

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 figures are planning illustrations based on the observed effect, not the trial's original design justification. For continuous outcomes, the figures are participants per arm, not total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The planning scenarios consider detecting the stated fraction of the observed effect. The original trial's own design assumptions are not reported in the registry record.

The 80% power column gives the planned number of participants per arm under which the calculation has an 80% chance of detecting the specified effect, if the planning assumptions hold. The 90% power column uses a higher probability of detecting that same specified effect, and therefore generally requires more participants per arm. These are design calculations, not a description of what happened in this trial. This is not observed power.

Rows for 100% of the observed effect use the full estimated difference as the planning target; rows for 75% and 50% use smaller target effects. Smaller effects are harder to distinguish from random variation, so they require more participants per arm under the same assumptions. For example, the serum 25-hydroxyvitamin D comparison for vitamin D-fortified drink lists 25 participants per arm for 80% power at 100% of the observed effect, 43 at 75%, and 97 at 50%. The parallel 90% power figures are 33, 58, and 129 participants per arm.

The table and curve should be read as illustrations of how the target effect and desired power affect planning. They do not imply that the original study selected its enrollment using these calculations, or that the observed results had the listed power. The registry does not report the trial's original sample-size calculation or its assumptions.

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 = 30.600; pooled standard deviation σ = 37.866.
2. n = 2 × (1.96 + 0.842)² × 37.866² / 30.600² = 24.0, rounded up to 25 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 <- 30.6                      # observed difference in means
sigma <- 37.866343895338                     # 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(1229891)
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 = 25 (80% power), 33 (90% power)
 75% of observed effect: n per arm = 43 (80% power), 58 (90% power)
 50% of observed effect: n per arm = 97 (80% power), 129 (90% power)
power.t.test: 25 
Simulated power at n = 25 per arm: 0.795 (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 multiple outcome measures and the posted results include pairwise comparisons of each fortified-drink arm with the plain-drink arm. Repeatedly testing outcomes and contrasts raises a multiplicity issue: even when no true difference exists across a collection of tests, some results may appear statistically notable by chance. A prespecified testing hierarchy, family-wise error procedure, or false-discovery approach can help interpret a family of tests, but no such approach is reported in the registry record.

The p-values accompanying the recalculated comparisons are unadjusted. They should therefore be read as results for individual comparisons, not as multiplicity-controlled evidence across the full outcome set. The registry does not report which endpoint was intended to receive confirmatory priority beyond identifying the primary outcome, nor does it report how the secondary outcomes were ranked or whether the analysis plan changed. The primary endpoint designation helps distinguish the stated main outcome, but it does not resolve the interpretation of multiple secondary tests.

Missing-data methods and analysis populations are also not reported in the registry record. The outcome summaries give 30 participants per arm, but the record does not say whether all randomized participants contributed, whether values were missing, or how any missingness was handled. It does not report whether the analysis used an intention-to-treat, per-protocol, or other population. Without these details, the effect of exclusions or incomplete follow-up cannot be assessed.

The registry also does not provide a statistical analysis plan, details of baseline adjustment, or results from sponsor analyses. These gaps do not invalidate the posted summaries, but they limit the ability to determine whether the displayed comparisons match prespecified analyses and whether the uncertainty accounts for the design and analysis decisions. Conclusions should remain tied to the posted outcomes and unadjusted calculations.

15. 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 0% reporting threshold.

The registry's adverse-event summaries list 30 participants at risk in each arm for serious adverse events and 0 affected in each arm. For other adverse events, the record likewise lists 30 at risk and 0 affected in each arm. No serious adverse-event terms are listed. The death fields are null, which means deaths are not reported in the registry record; a null entry should not be read as a reported count of zero.

These figures describe what the registry record posts, not a complete account of safety. The record does not provide event definitions, collection procedures, severity grading, attribution, duration of follow-up for safety, or information about withdrawals due to adverse events. A zero count in a posted summary cannot establish that no events occurred outside the recorded categories or reporting period, and it does not rule out uncommon harms. The available summaries are limited to the stated at-risk and affected counts.

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

The posted results indicate higher mean serum 25-hydroxyvitamin D at 12-week follow-up in both fortified-drink arms than in the plain-drink arm. The unadjusted recalculated differences are accompanied by confidence intervals that remain above zero. This is evidence of separation in the measured endpoint summaries under the calculation used; it is not, by itself, evidence about every consequence of the formulations or about outcomes beyond the measured follow-up.

The secondary results show lower posted means for fasting serum glucose, insulin, and HbA1c in the fortified-drink arms than in the plain-drink arm. Some unadjusted intervals exclude zero and others include zero. These are multiple secondary comparisons, with no multiplicity approach reported, and numerical results are absent for the listed lipid outcomes. They should not be elevated to definitive conclusions from the posted summaries alone.

The data do not establish a direct difference between the vitamin D-only and vitamin D-calcium drinks because that comparison is not reported. Nor do they identify whether any observed differences reflect vitamin D, calcium, other drink characteristics, adherence, or another factor. The trial compared formulations against plain yogurt drink; it did not, in the posted results, isolate all components through additional contrasts.

The record does not report baseline outcome values, changes from baseline, missing-data handling, the analysis population, a full statistical plan, or longer-term results. These omissions limit interpretation of how the results arose and how broadly they might apply. Findings from this trial should be understood as results for the posted population, interventions, outcomes, and follow-up, rather than as proof of a general effect or a guide to individual care.

17. Why This Trial Matters Statistically

This trial illustrates several statistical issues common in small clinical studies. The primary outcome is continuous and reported as a mean with standard deviation, making the comparison interpretable in the endpoint's natural units. Pairwise mean differences show the direction and size of separation, while confidence intervals communicate uncertainty more fully than a point estimate or p-value alone.

The record also shows why trial results need to be read across an outcome hierarchy. The primary endpoint has a clear role in the registry description, while several secondary outcomes broaden the scientific question. Multiple comparisons make unadjusted secondary p-values less definitive, especially when the registry does not report a testing strategy or complete numerical results for the listed outcomes. A coherent overall pattern can be informative, but it does not remove the need to distinguish planned primary inference from exploratory findings.

Another important distinction is between an observed difference and the assumptions required to interpret it. Randomization and double masking are design features recorded for this study, but the record lacks details about implementation, missing data, and analysis populations. The posted recalculations provide a transparent descriptive comparison from group summaries, yet cannot recover information that was not reported.

Finally, the planning figures demonstrate that sample-size requirements depend on the target effect and desired power. They are illustrations based on the observed estimates, not evidence that the original enrollment was justified by the same assumptions. Keeping estimation, uncertainty, multiplicity, and planning separate helps prevent a numerical result from being asked to support more than the registry record can establish.

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 constrain interpretation. The registry reports endpoint means and standard deviations but does not report baseline values or change-from-baseline estimates. It is therefore not possible from this record to assess baseline comparability for these outcomes or to determine whether the posted values represent changes over follow-up. Individual participant data are also unavailable, limiting assessment of distributions, outliers, and influential observations.

Although enrollment is listed as 90 and each arm's posted summaries use 30 participants, the record does not explain the analysis population or whether all randomized participants contributed to every outcome. Missing-data procedures, adherence, withdrawals, and protocol deviations are not reported. The randomization and masking labels are present, but operational details are not. The trial's original sample-size justification and statistical analysis plan are also not reported.

The available numerical results are incomplete relative to the registry's outcome listing: several secondary outcomes have no posted numerical summaries. Multiplicity handling is not reported, and the displayed comparisons are unadjusted recalculations. There is no posted direct comparison between the two fortified drinks. The follow-up endpoint is stated as 12-week; longer-term outcome results are not reported in the registry record.

These limitations do not change the arithmetic of the posted summaries, but they affect how confidently those summaries can be interpreted as a complete account of the randomized trial. In particular, they limit assessment of the analysis choices, the role of missing observations, and the broader consistency of results across all registered outcomes.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Comparison of Efficacy of Vitamin D and Vitamin D-calcium Fortified Yogurt Drink in Diabetic Patients — NCT01229891.
• Registry record last updated 2012-01-16; status last verified 2011-12.
• Results first posted 2012-01-16.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry describes a completed randomized, double-blind, parallel phase 2 trial in people with type 2 diabetes, sponsored by the National Nutrition and Food Technology Institute. It compares plain yogurt drink with vitamin D-fortified and vitamin D-calcium-fortified yogurt drinks. Enrollment is listed as 90; posted summaries use 30 participants per arm.

The primary endpoint is mean serum 25-hydroxyvitamin D in nmol/L at 12-week follow-up. Both fortified-drink arms have higher posted means than the plain-drink arm, with unadjusted recalculated confidence intervals above zero. Posted secondary numerical results cover fasting serum glucose, insulin, and HbA1c; results for the other listed secondary outcomes are not reported in the registry record.

The record does not report the original sample-size justification, full analysis plan, multiplicity handling, missing-data methods, or analysis population. The posted adverse-event summaries list no affected participants for serious or other adverse events; deaths are not reported in the registry record.