Evaluation of Vitamin D Requirements During Pregnancy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of Vitamin D Requirements During Pregnancy (NCT00292591), a randomized phase 3 study. The primary outcome is 25-Hydroxyvitamin D Concentration.

2. Clinical Question

The registry summary states that the study aimed to determine the effectiveness of vitamin D supplementation during pregnancy and describes a hypothesis that the highest dosing regimen would result in better vitamin D status regardless of ethnicity or race. The posted primary outcome is a laboratory measure of vitamin D status, not a clinical outcome such as a pregnancy complication or an infant health outcome. The registry record does not report a primary question comparing the 4,000 IU group directly with the 2,000 IU group, so the posted estimates do not establish the size or precision of that direct dose contrast.

3. Trial Design

The registry describes a phase 3, randomized, quadruple-masked, parallel-group study. It lists total enrollment as 501 and names the Medical University of South Carolina as sponsor. The study is marked completed. Its recorded start is 2004-01, and its primary completion is 2010-01. Mothers were assigned to one of three daily vitamin D dosing groups: 400 IU, 2,000 IU or 4,000 IU. The 400 IU group is described as receiving 400 IU/day plus 0 IU vitamin D3 as placebo/day; the two higher-dose groups received 2,000 IU total vitamin D3/day and 4,000 IU/day, respectively.

The registry summary places supplementation at the beginning of the second trimester. The endpoint description specifies a measurement at visit 7, one month prior to delivery, with a timeframe of 7 months. The primary outcome available in the record is circulating total 25(OH)D concentration in serum. It is recorded as a continuous measure summarized by a mean and standard deviation.

The arm-level outcome counts are 102 in the 400 IU group, 111 in the 2,000 IU group and 110 in the 4,000 IU group. These are the counts attached to the posted primary outcome, not a replacement for the total enrollment figure. The registry record does not explain why the outcome counts differ from total enrollment, describe participant flow, or state how many randomized participants contributed data to other analyses. Detailed eligibility criteria, allocation procedures, masking procedures and the trial’s original statistical design assumptions are not reported in the registry record. The “quadruple” masking label is recorded, but the identities of the masked parties are not specified.

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 25-Hydroxyvitamin D Concentration, measured over 7 months.

The primary endpoint is circulating total 25-hydroxyvitamin D concentration, also written as 25(OH)D, measured in serum. It is reported in ng/mL as a mean with a standard deviation for each dose group. The registry describes the measurement as occurring at visit 7, one month before delivery, with a timeframe of 7 months. This is a continuous laboratory measure: participants can have a range of measured concentrations, and the group summary describes the average concentration as well as the spread of individual measurements.

As a general statistical point, a laboratory concentration can serve as a biological measure related to the substance being studied. Comparing group means can describe whether the measured concentration differed across randomized dose groups at the recorded timepoint. It does not, by itself, show whether any difference is accompanied by a difference in symptoms, pregnancy outcomes or infant outcomes. Those are distinct questions and are not among the posted primary endpoint results.

The registry record does not report a clinical threshold used to classify vitamin D status, or a target concentration against which the means should be judged. It also does not report additional primary endpoint timepoints. Interpretation should therefore stay focused on the reported group means and their comparisons at this specified measurement, without treating the laboratory values as evidence of an unreported clinical benefit or harm.

7. Results Posted in the Registry

• Cholecalciferol 2000 IU: mean 41.00 versus 32.50 on control; difference 8.50 (95% CI 4.60 to 12.40), standardized effect d = 0.59; z-test p = <0.001.
• Cholecalciferol 4000 IU: mean 45.70 versus 32.50 on control; difference 13.20 (95% CI 9.33 to 17.07), standardized effect d = 0.92; z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous and recorded as a mean with a standard deviation. The posted arm summaries give the average 25(OH)D concentration and the spread of participant measurements within each dose group. To compare each higher-dose group with the 400 IU group, the posted calculations report a mean difference. A mean difference is expressed in the same units as the original outcome, here ng/mL, so its direction and magnitude can be understood on the scale of serum concentration.

What does a mean difference represent?

In general, a difference between group means describes how far apart the two estimated averages are. A positive value for the higher-dose group comparison indicates that its posted mean is higher than the mean in the reference group. The recalculated estimates are 8.5 ng/mL for 2,000 IU versus 400 IU and 13.2 ng/mL for 4,000 IU versus 400 IU. These recalculations use the posted group means and standard deviations and are unadjusted. They are not substitutes for a more detailed analysis that might account for design features or covariates, if any such analysis was conducted.

What do standard deviations and standard errors describe?

A standard deviation describes variation among individual observations in a group. The reported standard deviations are 14.4 for 400 IU, 14.6 for 2,000 IU and 14.3 for 4,000 IU. A standard error, by contrast, describes the estimated uncertainty of a sample mean. The record’s comparison calculations list standard errors of 1.426 and 1.386 for the 400 IU and 2,000 IU means, and 1.426 and 1.363 for the 400 IU and 4,000 IU means. In general, standard errors are used to quantify how precisely a sample estimate represents an underlying group mean; they are not measures of participant-to-participant spread.

How should the p-values be read?

The posted unadjusted p-value is p < 0.001 for each comparison with the 400 IU group. In general, a p-value assesses how compatible data are with a specified null hypothesis under the assumptions of the test. It is not the probability that the null hypothesis is true, nor does it measure the clinical importance of an estimate. A p-value also does not convey precision as fully as a confidence interval, and it does not by itself address multiplicity across several comparisons. The registry record does not report whether these p-values are from the trial’s prespecified analysis or how any broader set of analyses was handled.

What is the role of the confidence interval?

In general, a confidence interval gives a range of values compatible with the data and the interval procedure’s assumptions. The reported 95% intervals are 4.603 to 12.4 ng/mL for 2,000 IU versus 400 IU and 9.333 to 17.07 ng/mL for 4,000 IU versus 400 IU. Each interval refers to the mean difference for its own comparison. The intervals do not capture the range of individual concentrations, and they do not establish the result of a comparison between the two higher-dose groups.

Why might over-dispersion matter in other outcome types?

As a general statistical concept, over-dispersion occurs when observed variability is greater than a model assumes. It can affect the uncertainty estimates of some count or categorical outcome models if not accounted for. The posted primary endpoint is continuous and summarized by means and standard deviations, and the record does not describe an over-dispersion model. This concept should not be taken as a claim that over-dispersion occurred in this trial.

What analysis details are missing?

The registry record does not report the trial’s original statistical analysis plan, the model used for the primary analysis, any covariate adjustment, handling of missing endpoint values, or the population included in an intended primary analysis. It also does not report the trial’s original sample-size justification or interim analyses. Those details cannot be inferred from the available arm summaries and recalculated comparisons. The record lists no analysis entries, so the reported comparison calculations should be understood as the available unadjusted summaries rather than as a complete account of the trial’s statistical methods.

10. Confidence Intervals and Precision

The estimated mean difference for the 2,000 IU group relative to the 400 IU group is 8.5 ng/mL, with a 95% confidence interval from 4.603 to 12.4 ng/mL. For the 4,000 IU group relative to the 400 IU group, the estimate is 13.2 ng/mL, with a 95% confidence interval from 9.333 to 17.07 ng/mL. These intervals are the most direct summaries of the precision of the posted mean-difference estimates.

In general, a confidence interval shows the uncertainty associated with an estimate under the assumptions used to construct it. A narrower interval indicates greater precision than a wider interval on the same scale. The intervals are compatible with a range of possible mean differences, rather than a single exact value. They do not state where most individual participants’ measurements fall; the group standard deviations describe individual-level variation, while the intervals describe uncertainty around group contrasts.

The lower and upper limits for each comparison are above zero, and the associated unadjusted p-value is p < 0.001 for each. This describes the posted statistical evidence for a positive mean difference in each comparison with 400 IU. It does not resolve uncertainty about unreported outcomes, missing-data handling, or analyses not included in the registry record. The intervals also do not provide a direct estimate for 4,000 IU versus 2,000 IU. A confidence interval for that separate contrast is not reported in the registry record.

Precision depends in part on the amount of information available and the variability of the measurements. The endpoint counts are 102, 111 and 110 across the three groups, and the reported standard deviations are similar in size. The registry record does not provide enough detail to assess all design and analysis choices that may affect precision, including any adjustment or missing-data procedure.

11. 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 illustration expresses the required number as participants per arm for 80% power and participants per arm for 90% power. These are planning illustrations for a two-arm comparison, not total event counts. The 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: 100%, 75% or 50%. The illustration is computed from the observed effect and is not the trial’s original design calculation; the trial’s own sample-size assumptions are not reported in the registry record. This is not observed power.

For the 2,000 IU versus 400 IU comparison, planning for 100% of the observed effect gives 46 participants per arm for 80% power and 62 participants per arm for 90% power. Planning for 75% of the observed effect gives 82 participants per arm for 80% power and 109 participants per arm for 90% power. Planning for 50% of the observed effect gives 183 participants per arm for 80% power and 245 participants per arm for 90% power.

For the 4,000 IU versus 400 IU comparison, planning for 100% of the observed effect gives 19 participants per arm for 80% power and 25 participants per arm for 90% power. Planning for 75% of the observed effect gives 33 participants per arm for 80% power and 45 participants per arm for 90% power. Planning for 50% of the observed effect gives 75 participants per arm for 80% power and 100 participants per arm for 90% power.

In general, the 80% and 90% columns describe the planned probability of detecting the specified effect under the stated assumptions if that effect is present. Higher target power requires more participants under otherwise unchanged assumptions. Smaller effects also require more participants to detect, which is why the illustrations increase as the assumed fraction falls from 100% to 50%. These figures do not establish what the original investigators planned or what power the completed trial achieved.

12. 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 = 8.500; pooled standard deviation σ = 14.505.
2. n = 2 × (1.96 + 0.842)² × 14.505² / 8.500² = 45.7, rounded up to 46 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 <- 8.5                      # observed difference in means
sigma <- 14.5046094977584                     # 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(292591)
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 = 46 (80% power), 62 (90% power)
 75% of observed effect: n per arm = 82 (80% power), 109 (90% power)
 50% of observed effect: n per arm = 183 (80% power), 245 (90% power)
power.t.test: 46.7 
Simulated power at n = 46 per arm: 0.789 (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.

13. Multiplicity, Missing Data and Analysis Populations

The posted primary outcome has three dose groups, and the reported recalculated contrasts compare each higher-dose group with the 400 IU group. Considering more than one comparison raises a general multiplicity question: when several hypotheses are tested, the chance of at least one false-positive result can increase if each is judged separately without adjustment. The registry record does not report a multiplicity adjustment, a hierarchy of hypotheses or a prespecified approach for interpreting the two comparisons. The listed p-values are unadjusted, so they should not be read as multiplicity-adjusted findings.

The registry lists one outcome measure and no posted secondary outcome results. It also lists no analysis records. This does not establish that no other outcomes or analyses were collected or examined; it means they are not reported in the registry record. The record does not state whether the primary outcome was the only planned analysis, whether subgroup comparisons were intended, or how the stated hypothesis concerning ethnicity or race was evaluated. No subgroup estimates are posted in the outcome information.

Missing-data handling and analysis populations are also not reported in the registry record. The outcome counts are 102 for 400 IU, 111 for 2,000 IU and 110 for 4,000 IU, while total enrollment is 501. The record does not explain the relationship between these counts and enrollment, identify reasons for measurements not included, or specify whether the analysis followed an intention-to-treat, per-protocol or other population definition. It does not describe imputation, exclusions, or sensitivity analyses for missing outcomes.

As a general matter, missing data can affect both the estimated group means and their uncertainty, especially if the probability of having a measured endpoint differs across participants or groups. Without details about participant flow and missingness, the extent or direction of any such effect cannot be assessed. These gaps do not negate the posted summaries; they limit the ability to reconstruct the full analysis and judge how robust it is to alternative assumptions.

14. 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.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: pregnancy loss (miscarriage/fetal death) (7.7%).

The registry’s adverse-event information gives counts at risk and counts affected in each group. For serious adverse events, the 400 IU group lists 9 affected among 166 at risk, the 2,000 IU group lists 4 among 167 at risk, and the 4,000 IU group lists 13 among 168 at risk. The record also names “Pregnancy loss (miscarriage/fetal death)” as a leading serious-event term, with 7.7%. It does not provide a group-specific breakdown for that term in the information.

For other, non-serious adverse events, the counts affected are 22 among 166 at risk in the 400 IU group, 35 among 167 at risk in the 2,000 IU group, and 27 among 168 at risk in the 4,000 IU group. These are registry counts, not estimates adjusted for differences in exposure or follow-up. The adverse-event denominators differ from the arm counts attached to the primary outcome; the record does not explain the difference.

Deaths are not reported in the registry record. The adverse-event counts do not, by themselves, establish whether an event was caused by a study dose, and the record does not provide event narratives, timing, severity grading beyond the serious/non-serious categories, or statistical comparisons of safety outcomes. They should be read as descriptive reported counts rather than as a basis for causal conclusions.

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

The posted primary outcome data show higher mean serum 25(OH)D concentrations in the 2,000 IU and 4,000 IU groups than in the 400 IU group at the measurement one month before delivery. The corresponding unadjusted mean-difference estimates are 8.5 ng/mL and 13.2 ng/mL, and both posted p-values are p < 0.001. The confidence intervals indicate uncertainty around each estimated comparison, with both reported intervals above zero.

These results concern a laboratory concentration at a particular recorded timepoint. They do not, on their own, establish whether the measured differences translate into changes in health outcomes for mothers or infants, and they do not identify a clinical threshold for adequate vitamin D status. The registry record does not report such a threshold or primary clinical outcomes that would answer those questions. It also does not report a direct statistical comparison of 4,000 IU with 2,000 IU, so the two comparisons against 400 IU should not be used as a substitute for that contrast.

The numerical results are based on the posted arm summaries and unadjusted recalculations. The registry record does not report detailed methods for handling missing endpoint measurements, the analysis population, covariate adjustment, multiplicity, or the trial’s original statistical analysis plan. These omissions limit the degree to which the full analysis can be reconstructed or its sensitivity assessed. The stated hypothesis concerning vitamin D status regardless of ethnicity or race is part of the registry summary, but subgroup results addressing that hypothesis are not reported in the registry record.

The safety information is likewise descriptive. Serious and other adverse-event counts are listed by group, but the record does not provide causal assessments or formal statistical comparisons for these events. Overall, the posted findings describe group differences in the measured serum concentration and give a quantified range of statistical uncertainty for two comparisons. They do not support broader claims about clinical outcomes, an optimal dose, subgroup effects or causation beyond what is directly reported.

16. Why This Trial Matters Statistically

This trial illustrates how a randomized, multi-group design can compare more than one dose against a shared reference group. The three arm-level means show the measured outcome across 400 IU, 2,000 IU and 4,000 IU dosing groups, while the posted comparisons quantify each higher-dose group’s mean difference from the 400 IU group. Reporting the outcome in its original unit, ng/mL, makes the estimates interpretable on the scale of the laboratory measurement.

The example also highlights why a p-value should not stand alone. Each comparison has a confidence interval that communicates the uncertainty around the estimated mean difference, and the standard deviations describe substantial individual variation around the group means. Those measures answer different statistical questions. A small p-value does not eliminate uncertainty, describe individual outcomes or establish clinical importance.

Several design and reporting questions matter when interpreting trial results beyond the point estimates. The registry identifies randomization, masking and a parallel-group model, but does not report the original sample-size justification, analysis plan, missing-data procedures, analysis population or multiplicity approach. The posted planning illustrations are useful for understanding how detectable-effect assumptions relate to participant requirements, but they are not evidence of the original design or the completed study’s observed power.

Finally, the study’s primary endpoint is a biological measurement, while the registry summary’s broader interest is vitamin D status during pregnancy. Separating a laboratory concentration from clinical outcomes is important: the former can describe the measured endpoint, but does not automatically answer questions about symptoms, pregnancy outcomes or infant health. This distinction keeps statistical interpretation aligned with what the reported outcome can support.

17. 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 main limitation for interpretation is that the available outcome record is narrow. It reports one primary continuous measure at one stated timepoint, with arm means, standard deviations and comparisons against the 400 IU group. Secondary outcome results and analysis records are not listed. A direct comparison of 4,000 IU with 2,000 IU is not reported in the registry record, nor are subgroup results addressing the hypothesis about ethnicity or race.

Important statistical details are also absent. The trial’s original sample-size justification, statistical analysis plan, adjustment strategy, multiplicity handling, missing-data procedures and analysis population are not reported in the registry record. Participant flow and reasons why the primary outcome counts differ from total enrollment are not described. These omissions prevent a complete assessment of how the reported calculations relate to the trial’s planned analyses and whether alternative assumptions would materially change the estimates.

The endpoint is a serum concentration rather than a posted clinical outcome. The registry record does not report a threshold for interpreting the concentration as sufficient or insufficient, or results for clinical outcomes that might contextualize the laboratory difference. The observed means therefore cannot, by themselves, answer broader clinical questions.

Safety reporting is descriptive and does not include event attribution, group-specific figures for the named leading serious-event term, or deaths. The adverse-event counts at risk also differ from the primary outcome counts, without an explanation in the record. Finally, the posted p-values are unadjusted, and the record does not say how the set of comparisons was selected or whether multiplicity was addressed. These limitations call for a focused reading of the recorded comparisons rather than conclusions beyond the reported endpoint and safety summaries.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Evaluation of Vitamin D Requirements During Pregnancy — NCT00292591.
• Registry record last updated 2016-09-19; status last verified 2016-08.
• Results first posted 2016-08-09.
• 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.

21. Record Summary

NCT00292591 is a completed phase 3, randomized, quadruple-masked, parallel-group study sponsored by the Medical University of South Carolina. Total enrollment is listed as 501. Mothers were assigned to daily vitamin D dosing groups of 400 IU, 2,000 IU or 4,000 IU. The recorded study start is 2004-01 and primary completion is 2010-01.

The primary outcome is mean serum 25(OH)D concentration in ng/mL, measured at visit 7, one month prior to delivery, with a stated timeframe of 7 months. The posted arm means are 32.5 for 400 IU, 41.0 for 2,000 IU and 45.7 for 4,000 IU. Unadjusted recalculations report mean differences of 8.5 ng/mL and 13.2 ng/mL, respectively, for the higher-dose groups versus 400 IU; both have p < 0.001.

The registry record does not report secondary outcome results, analysis records, the original statistical analysis plan, missing-data procedures, or the trial’s original sample-size assumptions. Safety results are reported as descriptive adverse-event counts.