Vitamin K Supplementation in Post-Menopausal Osteopenia: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Vitamin K Supplementation in Post-Menopausal Osteopenia (NCT00150969), a randomized phase 3 study. The primary outcome is Percent Change in Bone Mineral Density (BMD) at the Lumbar Spine (L1-L4) Between Treatment Arms..

2. Clinical Question

This is a question about a difference between randomized groups in a measured bone-density outcome. The registry record identifies the two arms and the primary measurement, but the sponsor-reported analysis does not include a numeric effect estimate or confidence interval. Its reported p-value is therefore not enough, by itself, to convey the estimated size or precision of the group difference. A simple unadjusted re-calculation from the posted summaries gives a different p-value; because the registry flags a discrepancy, the sponsor’s own analysis takes precedence.

3. Trial Design

The registry identifies NCT00150969 as a completed phase 3 trial sponsored by University Health Network, Toronto. It began in 2002-01, with primary completion in 2006-09. The recorded enrollment was 440. The design was randomized, triple masked, and parallel, with vitamin K1 (phylloquinone) compared with placebo. The registry lists post-menopausal osteoporosis and post-menopausal osteopenia as conditions; the study summary and primary analysis describe women with osteopenia.

The active intervention is described as 5 mg vitamin K1, and the study summary specifies daily supplementation over a 2-year period. The primary endpoint timeframe is 0 to 24 months. The registry says BMD was measured yearly on one scanner at UHN using a DEXA Hologic 4500A densitometer. It does not report further details about the randomization procedure, allocation concealment, masking procedures, adherence, or the protocol’s sample-size justification.

The primary population description says all 440 women were included in the two-year BMD analyses on an intention-to-treat basis, using last observation carried forward for missing data. The registry reports 217 participants in the phylloquinone arm and 223 in the placebo arm for the primary outcome. The posted secondary outcome summaries do not all have identical group counts. Reasons for those differences are not reported in the registry record.

The registry lists 14 outcome measures and 12 posted secondary outcomes. The secondary outcomes cover BMD at other skeletal sites and measures related to bone formation, resorption, and osteocalcin carboxylation. It reports two analyses, and identifies the primary comparison method as a two-sided t-test. Additional details of the sponsor’s statistical plan, including any prespecified covariate adjustment or interim analyses, are not reported in the registry record.

4. Participant Flow and Accounting

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

Before assignment: 453 participants signed consent. 13 were not included in analysis(10 screen failure,3 drop out at baseline)

24 Month Main Study

Reasons for not completing this period:

24-48 Month Extension

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: For our 2 year BMD anlayses we included all 440 women based on intention to treat using last observation carried forward for missing data.

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 Percent Change in Bone Mineral Density (BMD) at the Lumbar Spine (L1-L4) Between Treatment Arms., measured over 0 to 24 months.

The primary endpoint is percent change in bone mineral density at the lumbar spine, specifically L1-L4, from 0 to 24 months. BMD is a continuous measurement: the outcome describes change in the amount of mineral measured in bone over the specified period. In general, a continuous endpoint can capture differences across the full range of measured values rather than reducing the result to whether a participant did or did not cross a threshold.

The registry says BMD was measured yearly on one scanner at UHN using a DEXA Hologic 4500A densitometer. Using one scanner is a stated feature of the measurement approach; further information about calibration, measurement reproducibility, or quality-control procedures is not reported in the registry record. The registry specifies percentage change as the unit and the mean as the summary measure, with standard deviation describing variation within each arm.

As a general statistical point, a bone-density endpoint can quantify change in bone mineral density, which is the outcome this trial set out to compare. It should not be treated as a direct report of fractures or other clinical events: the primary endpoint is BMD change, and the registry presents it as such. The primary analysis description says it included all 440 women on an intention-to-treat basis and used last observation carried forward for missing data. That method affects how missing endpoint values enter the analysis, and its implications are considered in the limitations.

7. Results Posted in the Registry

• Phyloquinone: mean -1.28 versus -1.22 on control; difference -0.06 (95% CI -0.67 to 0.55), standardized effect d = -0.02; z-test p = 0.847.

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.

Percent Change in Bone Mineral Density (BMD) at the Femoral Neck Between Treatment Arms.

• 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:
  • Phyloquinone: mean -1.47 versus -1.83 on control; difference 0.36 (95% CI -0.31 to 1.03), standardized effect d = 0.10; z-test p = 0.295.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Phyloquinone and the control. The interval gives the range of effects that remain compatible with the data.

Percent Change in Bone Mineral Density (BMD) at the Ultra-distal Radius Between Treatment Arms.

• 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:
  • Phyloquinone: mean -2.49 versus -2.55 on control; difference 0.06 (95% CI -0.76 to 0.88), standardized effect d = 0.01; z-test p = 0.886.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Phyloquinone and the control. The interval gives the range of effects that remain compatible with the data.

Effect of Vitamin K1 Supplementation on Levels of Bone Formation Marker

• 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:
  • Phyloquinone: mean 21.00 versus 24.00 on control; difference -3.00 (95% CI -4.47 to -1.53), standardized effect d = -0.41; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Phyloquinone than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes broaden the assessment beyond lumbar-spine BMD. They include BMD at other skeletal sites and measures related to bone formation, bone resorption, and osteocalcin carboxylation. The posted secondary outcomes include 12 measures, while the registry lists 14 outcome measures overall. The record does not explain the difference between those counts.

Across the secondary findings, the pattern is not uniform: the BMD comparisons generally show small contrasts in the posted group summaries, while a bone-formation marker comparison is more separated and has an unadjusted p-value below 0.001. These outcomes are not interchangeable. A marker measured in ng/ml and a percentage change in BMD describe different features, so a result in one should not be treated as a replication of the primary BMD comparison. The registry’s secondary outcome list also includes other marker and skeletal-site outcomes, but the presence of multiple outcomes makes isolated findings harder to interpret.

Secondary results can help describe whether the primary pattern is accompanied by differences in related measures, but they do not replace the primary endpoint or resolve the disagreement between the sponsor-reported primary p-value and the summary-based re-calculation. The posted secondary comparisons are unadjusted. When many outcomes are examined, the chance of at least one apparently notable result can increase even if there is no corresponding underlying effect. In general, multiplicity methods are used to address that concern, but the registry does not report whether any such adjustment was prespecified or applied.

For that reason, unadjusted secondary results carry less confirmatory weight than a prespecified primary analysis, especially when a range of endpoints and timeframes is considered. The registry record does not provide a hierarchy among the secondary outcomes or enough information to establish which were intended as confirmatory. They are best read as additional descriptive evidence, with attention to their different measurement scales and the absence of reported multiplicity handling.

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

• Percent Change in Bone Mineral Density (BMD) at the Femoral Neck Between Treatment Arms.
• Percent Change in Bone Mineral Density (BMD) at the Ultra-distal Radius Between Treatment Arms.
• Effect of Vitamin K1 Supplementation on Levels of Bone Formation Marker
• Effect of Vitamin K1 Supplementation on Level of Bone Resorption Markers (C-telopeptide: CTX)
• Effect of Vitamin K1 Supplementation on Percent of Carboxylation of Osteocalcin
• Percent Change in Bone Mineral Density (BMD) at the Total Hip Between Treatment Arms.
• Percent Change in Bone Mineral Density (BMD) at the Lumbar Spine (L1-L4) Between Treatment Arms.
• Percent Change in Bone Mineral Density (BMD) at the Femoral Neck Between Treatment Arms.

9. Statistical Interpretation

10. Statistical Methods Explained

The registry identifies the primary outcome as a mean percent change in lumbar-spine BMD and describes the reported test as a two-sided t-test. A t-test is a general method for comparing means between two groups. The two-sided form evaluates differences in either direction, rather than testing only whether one arm’s mean is greater than the other’s. The record does not report all assumptions or implementation details of the sponsor’s test, such as whether any covariates or additional adjustments were used.

What does the mean difference describe?

A mean difference expresses the distance between the group means on the outcome’s measurement scale. For the primary comparison, the registry-based recalculation reports -0.06 for phylloquinone relative to placebo. Its sign indicates the direction of that calculated contrast under the stated subtraction order; its size describes the observed gap in the posted group means. It is an unadjusted re-calculation, not a sponsor-reported effect estimate. The groups’ standard deviations, 3.5 and 3.0, describe the spread of individual measurements around their respective means. A standard deviation is not a confidence interval and does not indicate how precisely the mean difference is estimated.

What does a p-value tell the reader?

In general, a p-value describes how unusual data at least as inconsistent with a null hypothesis would be if that null model and the analysis assumptions were correct. It does not give the probability that the null hypothesis is true, nor does it measure the clinical importance of an effect. The sponsor’s recorded p <0.05 and the re-calculated p = 0.847 are discordant. Since the record flags this discrepancy, the sponsor’s own analysis takes precedence. The posted record does not supply enough of the sponsor’s analysis output to explain the disagreement.

The recalculated p-value is based on the posted group summaries and a simple unadjusted comparison. It should not be confused with the sponsor’s test result or treated as an independently verified analysis of participant-level data. Summary-statistic re-calculations cannot account for unreported features of the original analysis. No participant-level data or complete sponsor analysis output are reported in the registry record.

Why are confidence intervals useful?

In general, a confidence interval gives a range of effect values compatible with the data and the calculation’s assumptions, while expressing sampling uncertainty. A narrower interval indicates greater precision than a wider one, but an interval does not guarantee that its range contains the true effect. The recalculated interval for the primary mean difference includes zero. That is consistent with the re-calculated p-value not indicating a clear difference under that simple analysis. The sponsor’s analysis has no numeric interval reported, so its precision cannot be assessed in the same way.

What does randomization add?

Random allocation is intended, in general, to make treatment groups comparable at the start of a trial, including with respect to factors that may affect an outcome. It supports a between-group comparison, but does not remove uncertainty due to sampling or ensure that every later analysis is free of bias. The registry states that the study was randomized, but details of sequence generation, concealment, and checks of baseline balance are not reported in the registry record. Triple masking is also recorded, but the registry record does not explain which parties were masked or how masking was maintained.

How should variation and missing values be considered?

Standard deviations describe variability among measurements within each group. In general, greater variability can make a group mean less precisely estimated for a given amount of information, and can make a difference between means harder to distinguish. The registry’s primary population description states that missing BMD data were handled with last observation carried forward. In general, that method substitutes a participant’s last observed value for a later missing value. It relies on assumptions about what the unobserved measurement would have been; the registry does not report those assumptions or sensitivity analyses using alternative missing-data methods.

The primary results are summarized as means and standard deviations, and the listed comparison is a two-sided t-test. The registry record does not report whether the sponsor used an intention-to-treat analysis in exactly the same way as the population description, whether the sponsor’s test incorporated the stated missing-data method, or whether there were additional prespecified analyses. Those details should not be inferred from the summary alone.

11. Confidence Intervals and Precision

Precision concerns the uncertainty around an estimated difference, not just whether a p-value crosses a threshold. In general, a confidence interval shows a range of values compatible with the observed data under the calculation’s assumptions. Its width reflects the amount of information and variability in the data, along with the method used to construct it. A confidence interval is not a guarantee that the true effect lies inside its limits.

The recalculated primary mean difference is -0.06, and its recalculated interval includes zero. This means the posted summaries, analyzed with the simple unadjusted method used for the re-calculation, are compatible with a range that includes no group difference. The interval also allows values on either side of zero, so the summary alone does not establish the direction of an underlying difference with precision. The sponsor’s reported p <0.05 does not come with a numeric effect estimate or confidence interval in the registry record. Its precision and estimated magnitude therefore cannot be evaluated from the sponsor output posted there.

The reported standard deviations, 3.5 for phylloquinone and 3.0 for placebo, describe participant-level variation in the primary outcome. They are not measures of uncertainty in the treatment contrast. In general, a mean can be estimated more precisely when there is more information, while greater outcome variability tends to reduce precision. Those principles help explain why both group size and spread matter when interpreting an interval.

Precision is also distinct from practical importance. A narrow interval can precisely estimate a small difference, while a wide interval may leave a broad range of effects plausible. The registry’s primary sponsor result lacks the interval needed to make that assessment for the sponsor analysis. The recalculated interval is based only on posted summary statistics and should be interpreted with the discrepancy in mind, rather than substituted for the sponsor’s 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 sample-size figures are planning illustrations based on the observed effect, not the trial’s original design justification. For this continuous endpoint, the displayed quantities 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 effect to detect is defined as the stated fraction of the observed effect. The original trial’s own sample-size assumptions are not reported in the registry record.

The 80% power column describes the number of participants per arm that the planning calculation associates with an 80% chance of detecting the specified effect under its assumptions, if that effect is the true one. The 90% power column uses a higher target chance of detection and therefore requires more participants per arm for the same assumed effect. These are planning concepts, not guarantees about what a future study will find.

For the primary outcome, planning for 100% of the observed effect gives 46,234 participants per arm for 80% power and 61,894 participants per arm for 90% power. Planning for 75% of the observed effect gives 82,193 participants per arm for 80% power and 110,033 participants per arm for 90% power. Planning for 50% of the observed effect gives 184,933 participants per arm for 80% power and 247,573 participants per arm for 90% power. The curve expresses the same general relationship between the effect assumed for planning and the required sample size.

Smaller effects are harder to distinguish from random variation, so detecting them generally requires more participants when other planning assumptions are held fixed. The extremely small recalculated primary contrast is the basis for these large illustrative figures; they should not be interpreted as a recommendation or as evidence about the trial’s original planning. This is not observed power: the figures are prospective planning calculations based on an observed effect, not a measure of the probability that this completed trial succeeded in detecting an effect.

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 = -0.060; pooled standard deviation σ = 3.256.
2. n = 2 × (1.96 + 0.842)² × 3.256² / -0.060² = 46,233.1, rounded up to 46,234 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 <- -0.0600000000000001                      # observed difference in means
sigma <- 3.25618484211621                     # 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(150969)
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 = 46,234 (80% power), 61,894 (90% power)
 75% of observed effect: n per arm = 82,193 (80% power), 110,033 (90% power)
 50% of observed effect: n per arm = 184,933 (80% power), 247,573 (90% power)
power.t.test: 46234.1 
Simulated power at n = 46,234 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

The registry reports that the sponsor used a two-sided t-test for the primary comparison and gives p <0.05. It does not report a sponsor effect estimate, confidence interval, or the fuller analysis output needed to interpret that p-value alongside the group summaries. The posted arm means are -1.28 for phylloquinone and -1.22 for placebo, with standard deviations of 3.5 and 3.0.

A simple unadjusted re-calculation from those summaries gives a mean difference of -0.06 and p = 0.847. This does not reproduce the sponsor’s reported p-value. The registry flags a discrepancy, so the sponsor’s own analysis takes precedence. The recalculation is a check based on summary statistics, not a substitute for the sponsor’s analysis and not a correction to the registry result.

The record does not explain why the two results differ. It does not provide enough detail to determine whether the discrepancy reflects a different analysis population, method, missing-data handling, or another aspect of the analysis. None of those explanations should be assumed. Because the sponsor’s numeric estimate and interval are not reported, the p-value alone cannot communicate the magnitude or precision of the sponsor’s finding. The appropriate reading keeps the sponsor result distinct from the recalculation and recognizes that the registry does not resolve their disagreement.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 14 outcome measures and 12 posted secondary outcomes. The primary endpoint is identified separately as percent change in lumbar-spine BMD. Testing several outcomes creates a multiplicity issue: in general, the more comparisons made, the greater the possibility that one may look statistically notable by chance. Adjustments or a prespecified testing hierarchy can help control how results across multiple outcomes are interpreted. Whether the sponsor used a multiplicity adjustment, or had a prespecified hierarchy for the secondary outcomes, is not reported in the registry record.

The registry reports a two-sided t-test for the primary comparison, but does not give a complete statistical analysis plan. Details about prespecified analysis populations, covariate adjustment, interim analyses, handling of protocol deviations, or other planned tests are not reported in the registry record. The two analyses listed in the record do not, by themselves, explain the full analysis plan. The primary sponsor p-value also conflicts with a simple re-calculation from the posted summaries, and the registry does not provide enough information to reconcile that discrepancy.

For missing primary BMD measurements, the registry states that all 440 women were included in the two-year intention-to-treat analysis using last observation carried forward. In general, this method carries a participant’s last measured value forward when a later value is missing. Its validity depends on assumptions about the missing measurement and the course of the outcome. The record does not report how many values were missing, why they were missing, or whether sensitivity analyses using other methods were conducted. Those details limit assessment of how missingness may have affected the result.

The secondary group counts vary across outcomes. Reasons for those differences and the handling of missing secondary measurements are not reported in the registry record. The registry also does not report whether the analyses accounted for these differences, whether secondary outcomes were adjusted for multiple testing, or whether analyses beyond those posted were conducted. These omissions do not establish that a particular method was or was not used; they mean the registry record does not permit those questions to be answered.

16. 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: hospitalization (5.8%), cancer (4.9%), death (0.5%).

The registry lists serious adverse events affecting 15 of 217 participants in the phylloquinone arm and 25 of 223 in the placebo arm. Other adverse events affected 11 of 217 and 10 of 223, respectively. The counts should be read as descriptive entries, not as evidence that an event was caused by or prevented by the intervention.

The record also lists hospitalization at 5.8%, Cancer at 4.9%, and Death at 0.5% among the top serious-event terms. It does not clarify the denominator or provide arm-specific values for these percentages. Death counts by treatment arm are not reported in the registry record. Details on event definitions, timing, relatedness, follow-up, and comparative statistical analyses are also not reported. Accordingly, these data do not support a causal safety conclusion or a direct comparison adjusted for exposure or follow-up.

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

The primary outcome is a comparison of mean percent change in lumbar-spine BMD over 0 to 24 months. The posted group summaries are close, and the simple unadjusted re-calculation produces a small mean difference and a confidence interval that includes zero. Taken alone, that recalculation does not provide clear evidence of a difference between the group means. It is not, however, the same as the sponsor’s reported analysis.

The sponsor’s reported two-sided p-value is p <0.05, while the re-calculated p-value is 0.847. Because the registry flags this discrepancy, the sponsor’s own analysis takes precedence. The registry does not report the sponsor’s estimate or confidence interval and does not explain the discrepancy. As a result, readers cannot determine from the sponsor output alone the magnitude or precision of the reported primary finding, nor reconcile it with the posted group summaries.

The result does not, by itself, establish whether vitamin K1 prevented bone loss. A group mean change is not a direct account of every participant’s experience, and the primary endpoint is BMD rather than fracture occurrence. The registry’s secondary measures offer additional information, but they involve multiple outcomes and do not resolve the primary reporting conflict. The unadjusted secondary comparisons should not be treated as confirmatory without information about prespecification and multiplicity handling.

In general, a statistically notable p-value does not automatically mean that an effect is large, precise, or important; those judgments require an effect estimate, uncertainty interval, and relevant context. Here, the sponsor’s reported p-value is not accompanied by a sponsor estimate or interval. The summary-based recalculation supplies an estimate and interval but conflicts with the sponsor result, and it cannot replace the sponsor’s analysis. The registry record therefore supports a careful distinction between its reported analysis and a limited recalculation, rather than a single definitive reading of the primary result.

18. Why This Trial Matters Statistically

This trial illustrates why an effect estimate and its uncertainty are essential companions to a p-value. The registry reports the sponsor’s primary p-value but omits the sponsor’s numeric contrast and confidence interval. The posted group summaries permit a simple unadjusted re-calculation, yet that result differs from the sponsor’s. The record flags the discrepancy but does not explain it. This leaves an important gap between the reported test and the descriptive arm results.

It also shows how outcome variability matters. The primary result is a continuous measure summarized by group means and standard deviations. In general, the observed difference must be interpreted in relation to the spread of measurements and the amount of information available; a small observed mean gap can be difficult to estimate precisely when individual values vary. The planning illustration makes clear that sample-size requirements depend heavily on the effect assumed for future planning. It is a calculation based on the observed effect, not evidence about the original design’s rationale or the completed trial’s observed power.

The secondary outcomes raise a different statistical issue. Several skeletal sites and biological markers are assessed, but the registry does not report multiplicity handling or a testing hierarchy. An apparently notable secondary result should therefore be interpreted alongside the whole set of outcomes and its exploratory context, rather than in isolation.

Finally, missing-data handling is part of the analysis, not a minor technical detail. The primary description specifies intention-to-treat analysis with last observation carried forward, but does not report the extent or reasons for missingness or sensitivity analyses. Together, these features make transparent reporting of the analysis population, estimate, interval, missing-data assumptions, and multiplicity plan important for a complete statistical interpretation.

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.

Several trial-specific reporting limitations constrain interpretation. First, the primary sponsor analysis is reported as a two-sided t-test with p <0.05, but the registry does not give its effect estimate or confidence interval. A simple re-calculation from posted summaries yields a different p-value, and although the record flags a discrepancy, it does not explain it. That prevents direct reconciliation of the sponsor result with the group means.

Second, the primary analysis description says last observation carried forward was used for missing BMD data, but the registry does not report how many measurements were missing, why they were missing, or whether sensitivity analyses were performed. The validity of this method depends on assumptions about unobserved values, and the record does not describe those assumptions. Secondary outcome counts also vary, with no explanation of the differences or missing-data approach for those outcomes.

Third, the registry lists multiple outcomes but does not report a multiplicity adjustment, a hierarchy for testing them, or which secondary comparisons were confirmatory. This limits the weight that can be given to isolated secondary findings. The detailed statistical analysis plan, including any covariate adjustment, interim analysis, or sample-size justification, is not reported in the registry record.

The primary endpoint is measured over 0 to 24 months, and the record describes yearly measurement on one scanner. Longer-term outcomes, fracture results, details of measurement quality control, and full adverse-event analysis are not reported in the registry entries. The registry lists serious adverse-event terms and counts, but does not provide arm-specific death counts or clarify the denominator for the term percentages. These limitations are gaps in the registry record; they do not establish what may have been available elsewhere.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Vitamin K Supplementation in Post-Menopausal Osteopenia — NCT00150969.
• Registry record last updated 2023-12-28; status last verified 2023-12.
• Results first posted 2012-03-26.
• 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

NCT00150969 is a completed, randomized, triple-masked, parallel phase 3 trial sponsored by University Health Network, Toronto. It enrolled 440 participants and compared 5 mg daily vitamin K1 (phylloquinone) with placebo in post-menopausal women with osteopenia. The primary outcome was mean percent change in lumbar-spine BMD from 0 to 24 months, measured with a DEXA Hologic 4500A densitometer.

The registry reports a sponsor two-sided t-test with p <0.05 but does not give the sponsor’s estimate or confidence interval. A simple unadjusted re-calculation from the posted group summaries gives a different p-value; because the record flags a discrepancy, the sponsor’s analysis takes precedence. The record does not explain the disagreement. Missing primary BMD data were handled using last observation carried forward, and multiplicity handling for the secondary outcomes is not reported in the registry record.