Effects of Vitamin D on Moderate to Severe Periodontitis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effects of Vitamin D on Moderate to Severe Periodontitis (NCT03044886), a randomized na study. The primary outcome is Attachment Loss (AL).

2. Clinical Question

The main statistical question that can be addressed from the posted primary results is how the recorded baseline AL means compare among the three assigned groups, and how uncertain those comparisons are. The registry reports an overall ANOVA for all three groups and also permits unadjusted pairwise comparisons with placebo. These are different summaries: the ANOVA assesses the group-level pattern overall, while each pairwise comparison focuses on one dose against placebo.

The distinction between baseline status and a treatment response is central to interpretation. Randomization describes the assignment process, but it does not turn a baseline measurement into an outcome measured after treatment. The registry record does not report the later AL values, the duration of supplementation, or an analysis of change. Therefore, the posted AL statistics describe group starting measurements only, not a clinical effect of vitamin D.

3. Trial Design

The registry identifies NCT03044886 as a randomized, double-masked, factorial study sponsored by Beijing Chao Yang Hospital. The recorded phase is NA, and the status is completed. The listed enrollment is 360. The registry gives a start of 2013-01 and a primary completion of 2016-12.

Three intervention groups are described: 2000IU/Day, 1000IU/Day, and Placebo. The intervention is classified as a dietary supplement. Participants in the active groups are described as taking the stated daily vitamin D dose; the control group is described as taking placebo. The registry does not explain the factorial factors, the allocation ratio, whether there were additional assignments, the masking procedures, or the duration of supplementation. The listed trial model alone does not establish how its factorial design operated.

The primary outcome is mean attachment loss at baseline, recorded in mm. The posted outcome summaries give 105 participants for 2000IU/Day, 110 for 1000IU/Day, and 108 for Placebo. These outcome counts are distinct from the adverse-event groups, for which the record lists 120 participants at risk in each group. The registry does not explain the difference between these sets of counts or identify the analysis population for each result.

Probing depth, alveolar crest height, and bleeding index are also listed as secondary measures. The posted summaries for these outcomes are likewise labeled at baseline. The record describes an overall ANOVA for the primary outcome and overall analyses for secondary outcomes, using ANOVA or ANCOVA as recorded. It does not report a detailed statistical analysis plan, the original sample-size rationale, or the handling of missing data. The registry’s factorial label should therefore be read alongside, rather than as a substitute for, those absent details.

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:

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 Attachment Loss (AL), measured over at baseline.

Attachment loss (AL) is the registered primary endpoint. The registry reports it as a mean continuous measure in mm, with standard deviation, at baseline. It describes measurement using a Williams probe at six sites on each tooth: mesial buccal, buccal, distal buccal, mesial lingual, lingual, and distal lingual. The reported outcome is the mean value across all sites and all subjects.

Attachment loss is used to quantify periodontal attachment status. A continuous measure retains the scale of the recorded measurement, allowing group means and their dispersion to be described. The standard deviation conveys how spread out individual measurements are around a group mean; it is not the uncertainty interval for the mean difference between groups.

For this record, the timing is especially important. The primary endpoint is explicitly recorded at baseline. The posted means therefore describe measurements before any reported follow-up assessment, and the registry does not provide a later AL result or a change-from-baseline estimate. A baseline measure can describe initial status and support assessment of group comparability, but it is not by itself evidence about an effect occurring after supplementation. The registry record does not report whether AL was also measured at later times or how such measurements were analyzed.

7. Results Posted in the Registry

• 2000IU/Day: mean 4.70 versus 4.80 on control; difference -0.10 (95% CI -0.37 to 0.17), standardized effect d = -0.10; z-test p = 0.468.
• 1000IU/Day: mean 4.80 versus 4.80 on control; difference 0.00 (95% CI -0.24 to 0.24), standardized effect d = 0.00; z-test p = 1.000.

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.

Probing Depth (PD)

• 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:
  • 2000IU/Day: mean 3.60 versus 3.60 on control; difference 0.00 (95% CI -0.20 to 0.20), standardized effect d = 0.00; z-test p = 1.000.
  • 1000IU/Day: mean 3.70 versus 3.60 on control; difference 0.10 (95% CI -0.10 to 0.30), standardized effect d = 0.13; z-test p = 0.326.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 2000IU/Day 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 1000IU/Day and the control. The interval gives the range of effects that remain compatible with the data.

Alveolar Crest Height (ACH)

• 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:
  • 2000IU/Day: mean 7.70 versus 7.80 on control; difference -0.10 (95% CI -0.73 to 0.53), standardized effect d = -0.04; z-test p = 0.756.
  • 1000IU/Day: mean 7.70 versus 7.80 on control; difference -0.10 (95% CI -0.71 to 0.51), standardized effect d = -0.04; z-test p = 0.749.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 2000IU/Day 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 1000IU/Day and the control. The interval gives the range of effects that remain compatible with the data.

Bleeding Index (BI)

• 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:
  • 2000IU/Day: mean 3.50 versus 3.80 on control; difference -0.30 (95% CI -0.61 to 0.01), standardized effect d = -0.26; z-test p = 0.057.
  • 1000IU/Day: mean 3.20 versus 3.80 on control; difference -0.60 (95% CI -0.93 to -0.27), standardized effect d = -0.48; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 2000IU/Day and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for 1000IU/Day than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes listed in the registry are probing depth, alveolar crest height, and bleeding index. Their posted measurements are labeled at baseline. Across these measures, the dose-group means are generally close to the placebo means, while the bleeding-index means show a more noticeable separation in the posted summaries. This overall pattern is descriptive and does not by itself establish a treatment response.

The registry’s reported overall analyses for the secondary measures are ANCOVA for probing depth, ANOVA for alveolar crest height, and ANOVA for bleeding index. These analyses do not provide evidence about post-treatment changes because the posted timeframes are baseline. A pairwise unadjusted result for a secondary measure can look more compelling than its overall analysis, but it addresses a narrower comparison and should not be considered in isolation.

There are multiple outcome measures and multiple analyses recorded. When many comparisons are examined, the chance of finding an apparently unusual result by chance increases. The registry record does not report a multiplicity adjustment or identify a single confirmatory secondary comparison. Accordingly, unadjusted secondary findings carry less weight than a prespecified, multiplicity-controlled analysis would, especially when they are not supported by an overall analysis and do not measure a post-baseline response.

The secondary results do not change the interpretation of the primary endpoint. The primary AL result is a baseline comparison, and the secondary measurements are also reported at baseline. They provide additional descriptions of the groups’ recorded starting measurements, not evidence that vitamin D changed periodontal status. The registry does not report later secondary outcome measurements or change estimates.

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

• Probing Depth (PD)
• Probing Depth (PD)
• Probing Depth (PD)
• Alveolar Crest Height (ACH)
• Alveolar Crest Height (ACH)
• Alveolar Crest Height (ACH)
• Bleeding Index (BI)
• Bleeding Index (BI)

9. Statistical Interpretation

10. Statistical Methods Explained

The registry records continuous outcomes as means with standard deviations. A mean gives the center of the observed measurements, while a standard deviation describes their variability across participants. These quantities answer different questions: a group can have a well-defined mean and still contain widely dispersed individual measurements. The standard deviation is not a confidence interval and should not be read as one.

What does the overall ANOVA test?

ANOVA is a method for comparing means across groups. In the primary analysis, the registry lists an ANOVA involving all three assigned groups and reports p = 0.576. An overall test assesses whether the group means show evidence of an overall difference; it does not identify a particular pair as different. The record does not give the ANOVA statistic, degrees of freedom, model details, or a confidence interval for the overall comparison.

The posted pairwise re-calculations compare each dose group with Placebo. They report a mean difference, an interval, and an unadjusted p-value. These comparisons focus on specific pairs and are not interchangeable with the overall three-group test. Because the pairwise p-values are unadjusted, they do not account for the possibility of making several comparisons.

How should a mean difference be read?

A mean difference expresses the first group’s mean relative to the control mean, in the original outcome units. A negative value means the dose-group mean is lower than the Placebo mean under the comparison’s stated ordering; a value of zero indicates no difference between the displayed means at that precision. For the primary AL comparisons, the values are in mm. The reported estimates are calculated from the posted group summaries and do not represent a change over time.

The uncertainty interval around a mean difference describes a range of values compatible with the data and the calculation’s assumptions. Wider intervals indicate less precision than narrower intervals. If an interval includes zero, the data do not sharply distinguish a positive from a negative difference at the interval’s stated level. The registry record does not state the confidence level for these re-calculated intervals, so no confidence percentage should be attributed to them.

What does the study model tell us?

The registry labels the model factorial. In general, factorial studies can examine more than one intervention factor and may assess interactions between factors. However, the registry record does not identify the factors, their levels, or any interaction analysis. The listed dose groups and the model label are not enough to reconstruct that design or its analysis. The posted primary result is described as an ANOVA across the three groups, not as a reported factorial model with specified terms.

The secondary results use ANCOVA for probing depth and ANOVA for alveolar crest height and bleeding index, as recorded. In general, ANCOVA compares outcomes while accounting for covariates included in its model. The registry does not state which covariates were included, how they were selected, or what outcome timing the adjustment used. Since the posted secondary outcome timeframes are baseline, the values should be treated as baseline descriptions rather than effects after treatment.

Why can over-dispersion matter?

Over-dispersion is a general concern when variation in observed data exceeds what a statistical model assumes. If a model understates variability, its uncertainty estimates can be too narrow and its tests can overstate the strength of evidence. The posted outcomes are continuous means with standard deviations; the registry does not report an over-dispersion assessment or identify over-dispersion as a concern. This general issue is not a finding about this trial.

The record also does not report the original sample-size justification, assumptions for its own design, planned interim analyses, missing-data methods, analysis populations, or any prespecified multiplicity procedure. Those omissions limit the ability to assess how closely the posted analyses follow a protocol. They do not alter the arithmetic meaning of the means and pairwise re-calculations, but they prevent a full reconstruction of the planned statistical strategy.

11. Confidence Intervals and Precision

Precision is reflected in the uncertainty around an estimate, not only in the estimate itself. For the primary outcome, the re-calculated 2000IU/Day versus Placebo mean difference is -0.1 mm, with an interval from -0.370 to 0.170. The 1000IU/Day versus Placebo estimate is 0.0 mm, with an interval from -0.239 to 0.239. Both intervals extend to either side of zero, so neither pins down a direction of baseline difference with precision.

The interval for the 1000IU/Day comparison is narrower than the interval for the 2000IU/Day comparison in the reported re-calculations. Both remain compatible with small differences in either direction. Their precision should be read in the context of a baseline comparison: the intervals describe uncertainty about the group mean differences at baseline, not uncertainty about a treatment effect over time.

A confidence interval is generally a range generated by a statistical procedure to represent uncertainty in an estimate. The registry record does not state the confidence level for these re-calculated intervals. No particular coverage percentage should therefore be assumed from the posted interval values alone. The sponsor’s primary ANOVA supplies a p-value but no interval estimate or group-adjusted effect estimate.

The standard deviations for the primary group means describe participant-level spread, while the intervals describe uncertainty about between-group estimates. These are not substitutes for each other. The posted data provide some information about baseline group comparisons, but the absence of later AL results means the precision of any supplementation effect cannot be assessed from this primary result.

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, not total events. They are illustrations based on the observed effect, rather than the original trial’s design calculation. 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 the stated fraction of the observed effect. The trial’s own original design assumptions are not reported in the registry record.

The 80% power column gives the illustrative participants per arm for a design with an 80% chance of detecting the specified effect under those assumptions, if that effect and the model assumptions were correct. The 90% power column gives the corresponding per-arm planning figure for a higher chance of detection. These are prospective design quantities, not descriptions of the completed trial’s probability of finding a result.

Rows for 100%, 75%, and 50% of the observed effect show how the required sample size changes when the assumed effect to detect changes. A smaller effect is harder to distinguish from random variation, so detecting a smaller effect generally requires more participants. The figures are illustrative and depend on the observed effect used as their starting point; they should not be read as a recommendation or as the sample size used in the original protocol.

This is not observed power. It is a planning illustration based on the specified effect fractions and assumptions, not a retrospective measure of the trial’s success or failure. The original sample-size justification and its design assumptions are not reported in the registry record.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.100; pooled standard deviation σ = 1.004.
2. n = 2 × (1.96 + 0.842)² × 1.004² / -0.100² = 1,581.0, rounded up to 1,582 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -0.0999999999999996                      # observed difference in means
sigma <- 1.00357182010271                     # 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(3044886)
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 = 1,582 (80% power), 2,117 (90% power)
 75% of observed effect: n per arm = 2,811 (80% power), 3,763 (90% power)
 50% of observed effect: n per arm = 6,325 (80% power), 8,467 (90% power)
power.t.test: 1582 
Simulated power at n = 1,582 per arm: 0.804 (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

For the primary outcome, the registry records the sponsor’s overall analysis as an ANOVA across 2000IU/Day, 1000IU/Day, and Placebo, with p = 0.576. It does not provide an estimated overall difference, confidence interval, or further ANOVA details. The recorded analysis concerns AL at baseline.

The pairwise comparisons are unadjusted re-calculations from the posted means, standard deviations, and group sizes. They estimate each dose group’s baseline mean relative to Placebo. These calculations do not reproduce the full sponsor analysis: an overall three-group test and two pairwise comparisons have different scopes, and the registry does not report a sponsor-adjusted pairwise estimate for the primary outcome.

The record does not flag a discrepancy between the sponsor analysis and the re-calculation. The numerical results can therefore be read as complementary summaries rather than competing estimates: the ANOVA gives an overall test, while the re-calculations quantify the displayed pairwise baseline differences and their uncertainty. Neither analysis estimates a post-supplementation change because the reported primary measurement is at baseline.

The sponsor’s own analysis is the primary record of the trial’s reported inferential analysis. The re-calculations help describe the posted summary data, but they should not be mistaken for a fully adjusted analysis or for a replacement for an analysis plan that is not reported.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists several outcome measures and more analyses than there are posted secondary results. It reports 12 outcome measures and 16 analyses, while 9 secondary results are posted. The secondary-outcome listing repeats the names of measures, and the record does not explain how the full set of measures and analyses maps to the posted results.

Multiplicity arises when several hypotheses are tested. Even if each test is conducted appropriately on its own, examining many results can increase the likelihood that at least one appears unusual by chance. A prespecified hierarchy, family-wise adjustment, or other multiplicity strategy can help define how to interpret a collection of tests. The registry record does not report whether such a procedure was planned or used. The pairwise re-calculations are explicitly unadjusted, so their p-values should be considered exploratory rather than read as a family-wide conclusion.

The record does not describe missing-data handling, the analysis population, exclusions after randomization, or whether all randomized participants contributed to each outcome. The posted outcome sample sizes differ across groups, but the reason is not reported in the registry record. The adverse-event groups list different at-risk counts from those accompanying the outcome summaries, and the record does not explain how these populations relate.

The registry also does not report interim analyses, a protocol-based analysis plan, covariate choices for ANCOVA, or whether the listed results were prespecified. These absences do not prove that such plans or procedures did not exist; they mean they cannot be evaluated from the registry record. Interpretation should remain tied to the analyses and measurements explicitly posted, with caution about selective reporting, missingness, and the number of tests.

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.

The adverse-event record lists 120 participants at risk in each of the 2000IU/Day, 1000IU/Day, and Placebo groups. For every group, it reports zero serious adverse events, zero other adverse events, and zero deaths. No top serious-event terms are listed.

These figures describe what the registry record reports for the stated at-risk groups. They do not mean that adverse events were impossible, nor do they establish that the groups had identical safety experience. The record does not give event definitions, collection methods, observation duration, severity details beyond the serious-event category, or an explanation of how these groups relate to the outcome-analysis counts.

With zero events recorded, there is no event-rate comparison to interpret from these entries. The safety information should therefore be read narrowly as a registry report of no events in the listed categories, not as a comprehensive estimate of risk or a conclusion about safety.

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

The registry record shows that the three groups had similar mean AL values at baseline at the reported precision. The sponsor’s overall baseline analysis reports p = 0.576, and the unadjusted pairwise estimates are small with intervals that include zero. These results describe the recorded initial measurements and the uncertainty around their comparisons.

They do not show whether vitamin D supplementation improved, worsened, or had no effect on attachment loss. The posted primary outcome is explicitly at baseline, and no later AL measurements or changes are reported. The same timing limitation applies to the posted secondary measures. A baseline comparison is not a treatment-effect estimate, even when the groups were assigned by randomization.

The record also does not establish that all clinically relevant characteristics were balanced, nor does it provide a detailed account of eligibility, adherence, follow-up, missing outcomes, or the analysis population. Those limitations restrict what can be inferred from the baseline summaries. Statistical uncertainty intervals do not address unreported design or data-collection limitations.

The study’s stated objective was to evaluate the direct effect of high dose vitamin D supplementation and suggest a dose for clinical use. The posted baseline results cannot answer that objective. They also cannot determine a recommended dose, and no clinical recommendation follows from these statistics. The appropriate interpretation is confined to the reported baseline group summaries and the registered overall tests, with the treatment effect remaining unestimated in the posted results.

18. Why This Trial Matters Statistically

This trial illustrates why outcome timing is as important as the outcome name. Attachment loss is the primary measure, and the registry gives detailed measurement procedures, but the timeframe is baseline. Without a post-baseline value or change estimate, even a well-described clinical measure does not answer whether an intervention altered it.

The record also illustrates the distinction between an overall test and pairwise estimates. The sponsor reports an ANOVA across three groups, while the re-calculations quantify each dose-versus-placebo baseline contrast. Each summary answers a different question. Reporting both estimates and their uncertainty can make the size and precision of group differences easier to understand, but it does not resolve the timing limitation.

Secondary endpoints add context, but multiple outcomes and analyses require care in interpretation. A single unadjusted comparison can be less persuasive when it is part of a wider set of tests, particularly when the analysis plan and multiplicity handling are not reported. The record’s factorial label also highlights the importance of reporting design details: without the factors and model terms, readers cannot assess whether the posted analyses reflect the intended factorial questions.

Finally, the entries show that registry records can include outcome summaries, sponsor analyses, and safety counts with different participant numbers, without explaining how those analysis populations relate. Transparent reporting of timing, populations, missing-data methods, prespecified analyses, and sample-size rationale is essential for judging what a trial’s statistical results can support. These are interpretive considerations, not conclusions about unreported conduct.

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 principal limitation for interpretation is that the primary and posted secondary outcomes are all labeled at baseline. The registry does not provide later measurements, change-from-baseline results, or a treatment-effect estimate. Thus the posted outcome data do not assess the stated supplementation objective.

The factorial model is named but not described. The record does not identify the factorial factors, allocation ratio, interaction terms, or the relationship between the model and the three listed groups. It also does not report the original sample-size justification, planned interim analyses, detailed analysis plan, analysis populations, or handling of missing data.

The outcome summaries list 105, 110, and 108 participants across the three groups, while each adverse-event group lists 120 participants at risk. The registry does not explain these differences. It also does not state whether the outcome counts reflect all randomized participants or how missing measurements were handled.

The primary sponsor analysis supplies an overall p-value but no effect estimate or interval. The pairwise estimates are unadjusted re-calculations, and the confidence level for their intervals is not stated. Several outcomes and analyses are recorded, but no multiplicity procedure is described. The secondary results consequently have limited confirmatory value.

Finally, the registry condition entry reads “Chronic Peritonitis,” whereas the study title refers to periodontitis. This record-level terminology difference is not resolved in the posted information. These limitations concern the information available in the registry and should not be taken as claims about procedures that may have been documented elsewhere.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Effects of Vitamin D on Moderate to Severe Periodontitis — NCT03044886.
• Registry record last updated 2019-02-18; status last verified 2019-02.
• Results first posted 2019-02-18.
• 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.

23. Record Summary

NCT03044886 is recorded as a completed, randomized, double-masked, factorial study sponsored by Beijing Chao Yang Hospital. The intervention groups are 2000IU/Day, 1000IU/Day, and Placebo. The listed enrollment is 360, and the primary completion is 2016-12.

The primary endpoint is mean attachment loss in mm at baseline. The registry reports an overall ANOVA p = 0.576 and baseline group summaries. Re-calculated pairwise comparisons likewise concern baseline values, not changes after supplementation. Probing depth, alveolar crest height, and bleeding index are also posted at baseline.

The record reports zero serious adverse events, zero other adverse events, and zero deaths in each listed adverse-event group. It does not provide a post-treatment primary result, the original sample-size rationale, or sufficient detail to reconstruct the factorial analysis. The posted statistics therefore describe baseline group measurements and recorded safety counts, not a treatment effect.