Efficacy and Safety Study of Azilsartan Medoxomil Compared to Ramipril for Treating Essential Hypertension: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety Study of Azilsartan Medoxomil Compared to Ramipril for Treating Essential Hypertension (NCT00760214), a randomized phase 3 study. The primary outcome is Change From Baseline in Mean Trough Clinic Sitting Systolic Blood Pressure..

2. Clinical Question

3. Trial Design

The registry record describes a phase 3, randomized, quadruple-masked, parallel-group study sponsored by Takeda. Its title identifies azilsartan medoxomil and ramipril as the treatments being compared in participants with essential hypertension. The three named arms were azilsartan medoxomil 40 mg once daily, azilsartan medoxomil 80 mg once daily, and ramipril 10 mg once daily. Enrollment was 885.

The study began in 2008-01, had primary completion in 2009-04, and is recorded as completed. The primary endpoint timeframe was baseline and Week 24. The endpoint description says the final visit or Week 24 value was compared with baseline. The clinic systolic pressure measure was the arithmetic mean of three trough sitting systolic blood pressure measurements.

Randomization supports comparisons between the assigned groups, while masking is intended in general to limit the influence of treatment knowledge on study conduct or assessment. The registry record identifies the masking level as quadruple but does not specify the roles included in that description. It also does not report the allocation ratio, details of the randomization procedure, or additional protocol features beyond those stated. The study had multiple blood-pressure outcomes, including clinic and ambulatory measures. The registry record lists 12 outcome measures and 24 analyses. The primary endpoint and its designated analysis population are distinct from the broader set of secondary measures.

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: Participants with essential hypertension were enrolled in one of three, once-daily (QD) treatment groups.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full analysis set with last observation carried forward.

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 Change From Baseline in Mean Trough Clinic Sitting Systolic Blood Pressure., measured over Baseline and Week 24..

The primary endpoint measures change from baseline in mean trough clinic sitting systolic blood pressure, in mmHg, at the final visit or Week 24. Systolic blood pressure is the pressure during heart contraction. In this study, the endpoint was based on the arithmetic mean of three trough sitting systolic measurements, rather than a single reading. The posted group results are least-squares mean changes, with standard errors as their dispersion measure.

A change-from-baseline endpoint describes how the measured value at follow-up differs from the participant’s baseline value. In general, adjusting an analysis for baseline can account for baseline measurements when comparing follow-up outcomes; the sponsor’s posted analyses are identified as ANCOVA analyses of final values. These analyses report adjusted group contrasts, while the recalculations based on posted summary statistics are unadjusted comparisons of the reported changes. Those are not identical estimands or methods.

Repeated clinic measurements can reduce reliance on a single reading, while a trough measurement targets a specified point in the dosing interval. These are general measurement considerations, not additional claims about the study protocol. The endpoint is relevant to the stated blood-pressure comparison, but it does not alone represent all outcomes that could matter to participants. The registry record’s named secondary measures include diastolic pressure and ambulatory blood-pressure measurements.

7. Results Posted in the Registry

• Azilsartan Medoxomil 80 mg QD: mean -21.24 versus -20.63 on control; difference -0.61 (95% CI -3.24 to 2.02), standardized effect d = -0.04; z-test p = 0.649.
• Ramipril 10 mg QD: mean -12.22 versus -20.63 on control; difference 8.41 (95% CI 5.79 to 11.03), standardized effect d = 0.52; z-test p = <0.001.

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.

Change From Baseline in Mean Trough Clinic Sitting Diastolic Blood Pressure

• 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 errors.
• Result:
  • Azilsartan Medoxomil 80 mg QD: mean -10.54 versus -10.18 on control; difference -0.36 (95% CI -1.90 to 1.18), standardized effect d = -0.04; z-test p = 0.646.
  • Ramipril 10 mg QD: mean -4.87 versus -10.18 on control; difference 5.31 (95% CI 3.77 to 6.85), standardized effect d = 0.56; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Azilsartan Medoxomil 80 mg QD 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 higher for Ramipril 10 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in 24-hour Mean Systolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring.

• 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 errors.
• Result:
  • Azilsartan Medoxomil 80 mg QD: mean -12.29 versus -12.65 on control; difference 0.36 (95% CI -2.41 to 3.13), standardized effect d = 0.03; z-test p = 0.799.
  • Ramipril 10 mg QD: mean -7.83 versus -12.65 on control; difference 4.82 (95% CI 2.01 to 7.63), standardized effect d = 0.42; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Azilsartan Medoxomil 80 mg QD 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 higher for Ramipril 10 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in 24-hour Mean Diastolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring.

• 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 errors.
• Result:
  • Azilsartan Medoxomil 80 mg QD: mean -8.32 versus -8.03 on control; difference -0.29 (95% CI -2.09 to 1.51), standardized effect d = -0.04; z-test p = 0.753.
  • Ramipril 10 mg QD: mean -5.26 versus -8.03 on control; difference 2.77 (95% CI 0.94 to 4.60), standardized effect d = 0.37; z-test p = 0.003.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Azilsartan Medoxomil 80 mg QD 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 higher for Ramipril 10 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry record lists secondary blood-pressure outcomes that include clinic diastolic pressure and ambulatory systolic and diastolic pressure over different periods of the day. The posted secondary summaries broadly show decreases from baseline across the reported groups. In the available comparisons, the two azilsartan medoxomil groups tend to have similar mean changes, while comparisons with ramipril generally show larger reductions for the azilsartan groups. This broad pattern is consistent with the direction of the primary endpoint results, but the outcomes are not interchangeable: clinic and ambulatory measurements capture blood pressure in different ways and time windows.

The posted secondary results include both estimates and confidence intervals, and some comparisons are less precise than the primary clinic outcome. A secondary result can add context by showing whether a pattern is also present in related measures, but it does not independently confirm the primary finding. The registry record lists 11 posted secondary outcomes. It does not report a multiplicity-adjustment strategy for these outcomes and analyses. When many hypotheses are tested, the chance of at least one apparently notable result can increase even if all null hypotheses are true. This is a general statistical concern, not a claim about which results would change under an adjustment.

For that reason, unadjusted secondary p-values carry less weight than a prespecified primary analysis, particularly when they are interpreted as a collection. The registry record does not report the hierarchy of secondary hypotheses or a procedure for controlling family-wise error or false discovery. The secondary measures are useful for describing the breadth of the posted blood-pressure findings, but conclusions should remain anchored in the prespecified primary endpoint and the sponsor’s reported analysis. No additional clinical meaning should be inferred from the statistical pattern alone.

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

• Change From Baseline in Mean Trough Clinic Sitting Diastolic Blood Pressure
• Change From Baseline in 24-hour Mean Systolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring.
• Change From Baseline in 24-hour Mean Diastolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring.
• Change From Baseline in the 12-hour Mean Systolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring
• Change From Baseline in the 12-hour Mean Diastolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring
• Change From Baseline in Daytime (6am to 10 pm) Mean Systolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring.
• Change From Baseline in Daytime (6am to 10 pm) Mean Diastolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring.
• Change From Baseline in the Nighttime (12 am to 6 am) Mean Systolic Blood Pressure Measured by Ambulatory Blood Pressure Monitoring.

9. Statistical Interpretation

10. Statistical Methods Explained

The record reports continuous outcomes, least-squares mean changes, standard errors, and sponsor ANCOVA analyses. General statistical concepts help distinguish these summaries and explain why their estimates may differ. The registry record does not report a complete statistical analysis plan, the original sample-size justification, or whether interim analyses were planned.

What does a mean change describe?

A mean change summarizes the average change in a measured outcome within a group. Negative changes in this endpoint indicate a reduction from baseline in the measured systolic blood pressure. The group mean does not describe every participant’s response: individual outcomes can vary around the mean. The posted estimates are least-squares means, which are model-based adjusted means. The record identifies their dispersion as standard error. A standard error describes uncertainty in an estimated mean, rather than the spread of individual measurements.

What is a treatment contrast?

A contrast subtracts one group’s estimated outcome from another group’s estimated outcome according to a stated ordering. Reversing that ordering reverses the sign, without changing the underlying pair of groups. A contrast therefore needs to be read with its group labels and definition. The recalculated summaries compare observed changes without adjustment, while the sponsor’s reported analyses are ANCOVA comparisons of final values. ANCOVA is a general regression-based approach that can account for covariates specified in the model. The exact covariates and full model specification are not reported in the registry record, so they should not be inferred.

Why can adjusted and unadjusted estimates differ?

An unadjusted calculation uses the posted group summary statistics without fitting the sponsor’s model. An adjusted analysis can incorporate baseline or other model covariates, depending on its specification. Even when both analyses concern the same treatment groups and endpoint, adjustment can change the estimate, its uncertainty, or both. The posted recalculations are explicitly approximate because standard deviations are inferred from standard errors and sample sizes. They are useful as a transparent check of the summary data, but are not a replacement for the sponsor’s model-based result. Because the record flags a discrepancy, the sponsor’s own analysis takes precedence.

What do confidence intervals and p-values contribute?

A confidence interval gives a range of values compatible with the data under the assumptions of the analysis. Its width conveys precision: narrower intervals indicate less uncertainty about the estimated contrast than wider intervals, all else equal. Whether an interval includes zero is one way to assess whether the data are compatible with no mean difference under that method. It does not show the probability that the null hypothesis is true. A p-value describes how unusual data at least as discrepant as those observed would be under a specified null model and its assumptions. It is not a measure of clinical importance, and it does not tell how likely a result is to replicate.

The sponsor’s posted primary comparisons use ANCOVA and report 95% confidence intervals. The recalculated p-values are unadjusted; they do not account for multiplicity across the many outcomes and analyses. The registry record does not state whether the sponsor adjusted for multiple comparisons. This distinction matters when interpreting a collection of endpoint tests rather than one prespecified primary comparison.

Why can over-dispersion matter?

For continuous outcomes, the standard error reflects both the variability of measurements and the amount of information available. In general, greater variability makes a mean contrast less precise, while more observations can improve precision. Over-dispersion is more commonly discussed for count data: it means the observed variability exceeds what a chosen model assumes. If a model understates variability, its standard errors can be too small and intervals too narrow. That general issue is not evidence that over-dispersion occurred in this trial. The primary outcome is continuous, and the registry record does not identify an over-dispersion assessment.

What does the analysis population tell the reader?

The primary endpoint population is the full analysis set with last observation carried forward. In general, last observation carried forward fills a missing later measurement with an earlier observed value. This approach can affect estimates if the carried-forward value does not represent the outcome that would have been measured at the planned endpoint. The registry record does not report the amount or reasons for missing primary outcome data, nor does it report sensitivity analyses for missing values. The stated analysis population should therefore be read as part of the definition of the reported result, not as evidence that all randomized participants contributed a Week 24 measurement.

11. Confidence Intervals and Precision

The sponsor’s primary ANCOVA comparisons with ramipril have 95% confidence intervals: -11.04 to -5.78 for azilsartan medoxomil 40 mg, and -11.66 to -6.39 for azilsartan medoxomil 80 mg, using the sponsor’s reported contrast direction. Both intervals lie on the same side of zero. Their widths indicate uncertainty remains about the exact size of each adjusted contrast, even though the intervals do not include zero under the reported analysis.

The recalculated 40 mg versus ramipril contrast is 8.41 mmHg, with an interval from 5.785 to 11.03. The recalculated 80 mg versus 40 mg contrast is -0.61 mmHg, with an interval from -3.236 to 2.016. The latter includes zero and spans values on either side of it. It is compatible with a range of possible mean differences, including no difference, under this unadjusted calculation. This does not establish equivalence, which requires a prespecified margin and an appropriate analysis; such a margin is not reported in the registry record.

In general, a confidence interval reflects sampling uncertainty under the method and assumptions used. It is not a prediction interval for individual outcomes and does not include every source of uncertainty, such as model choice or missing-data assumptions. The recalculated intervals are based on approximate standard deviations inferred from posted standard errors and sample sizes. The reported ANCOVA intervals are the sponsor’s own adjusted results and should take precedence in light of the flagged discrepancy. Precision should be considered alongside the endpoint definition, analysis population, and multiplicity context rather than as a standalone measure of importance.

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 participants or total events. The posted planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each scenario uses the stated fraction of the observed effect as the effect to detect. The trial’s own original design assumptions and sample-size justification are not reported in the registry record; these figures are planning illustrations based on observed results, not a reconstruction of the original design.

The 80% power column gives the planned participants per arm under those assumptions for an 80% chance of detecting the specified effect if that effect is the true one and the model assumptions hold. The 90% power column gives the corresponding per-arm planning figure for a higher target chance of detection. These are design targets, not guarantees about what a future study will find. Smaller effects are harder to distinguish from random variation, so planning for a smaller effect requires more participants per arm. That pattern is reflected by the scenarios for 100%, 75%, and 50% of the observed effect.

For comparisons where the observed contrast is close to zero, basing planning on a fraction of that observed contrast can produce very large participant requirements. Such figures are especially sensitive to uncertainty in the observed effect and should not be read as a definitive sample-size recommendation. The planning values do not represent observed power for this completed trial.

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 = -0.610; pooled standard deviation σ = 16.135.
2. n = 2 × (1.96 + 0.842)² × 16.135² / -0.610² = 10,983.3, rounded up to 10,984 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 <- -0.609999999999999                      # observed difference in means
sigma <- 16.1352835920276                     # 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(760214)
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 = 10,984 (80% power), 14,704 (90% power)
 75% of observed effect: n per arm = 19,526 (80% power), 26,140 (90% power)
 50% of observed effect: n per arm = 43,934 (80% power), 58,814 (90% power)
power.t.test: 10984.2 
Simulated power at n = 10,984 per arm: 0.802 (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 sponsor’s analyses are ANCOVA comparisons of final values and are reported with 95% confidence intervals and p-values. For the primary endpoint, the reported mean differences are -8.41 for the 40 mg azilsartan medoxomil group compared with ramipril and -9.03 for the 80 mg group compared with ramipril; both reported p-values are <.001. The registry record’s contrast ordering is reflected in those negative signs.

The recalculation uses posted group change summaries to form unadjusted differences. Its contrast direction can be the reverse of the sponsor’s reported direction, so signs should not be compared without identifying which group is subtracted from which. More importantly, the estimates are not based on the same analysis method: the recalculation does not reproduce the sponsor’s ANCOVA adjustment. The record flags a discrepancy between recalculated and reported results. Accordingly, the sponsor’s own analysis takes precedence; the recalculation is best treated as a check based on summary statistics, not a competing adjusted result.

Differences between adjusted and unadjusted results can arise from the model, the outcome definition used in the analysis, and the information retained in summary data. The registry record does not provide enough detail to identify the specific reason for the discrepancy. It would be inappropriate to infer the sponsor’s model covariates or to explain the difference more specifically than the record allows.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes, treatment contrasts, or analysis choices are examined. In general, repeated testing can increase the chance of at least one small p-value arising by chance. This trial has a primary endpoint, multiple secondary outcomes, and multiple analyses recorded. The registry record does not report whether the sponsor used a multiplicity adjustment, a testing hierarchy, or another procedure to control error across those analyses. It also does not report the full statistical analysis plan. Consequently, the posted p-values should not be assumed to have been adjusted unless the registry record states that they were.

The primary outcome population is described as the full analysis set with last observation carried forward. Last observation carried forward is a missing-data method that uses a participant’s last recorded value in place of a later missing value. In general, its suitability depends on why values are missing and how outcomes might change after the last observation. The registry record does not report how many primary outcome measurements were missing, the reasons for missingness, or sensitivity analyses using other assumptions. The effect of missing data on the estimates therefore cannot be assessed from the record.

The registry record reports the group sizes used for endpoint summaries, but does not state how those analysis counts relate to all randomized participants or describe exclusions in detail. It also does not report the original sample-size justification, the assumptions behind that justification, or whether interim analyses were planned. Those omissions limit assessment of how the trial was designed to address its primary question and whether analysis decisions were prespecified. They do not negate the posted results, but they define important uncertainties when interpreting the strength and generalizability of the statistical evidence.

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: atrial fibrillation (0.7%), acute coronary syndrome (0.3%), angina pectoris (0.3%), hydrocele (0.3%), retinal detachment (0.3%).

The registry record lists serious adverse events affecting 8 participants in the azilsartan medoxomil 40 mg group, 12 in the 80 mg group, and 6 in the ramipril group. The corresponding groups at risk were 294, 293, and 293. These are counts of affected participants, not an adjusted comparison of risk. The record also lists other adverse events affecting 22, 16, and 36 participants, respectively, in the same arm order. Serious and other adverse event categories should not be combined or treated as equivalent.

The most frequently listed serious-event terms include atrial fibrillation at 0.7%, followed by acute coronary syndrome, angina pectoris, hydrocele, retinal detachment, and salivary gland calculus, each at 0.3%. These terms describe recorded events; the registry record does not establish that a study treatment caused them. The death fields are not populated, so deaths are not reported in the registry record. The counts alone do not give detail about timing, duration, severity beyond the serious classification, or the clinical context of each event. They are descriptive safety information and do not substitute for a comparative safety analysis.

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

The posted results describe mean blood-pressure changes over the study’s stated baseline-to-Week-24 timeframe in three randomized treatment groups. The primary endpoint values show reductions in each group, and the sponsor’s ANCOVA analyses report differences between each azilsartan medoxomil group and ramipril. The confidence intervals and p-values describe the uncertainty and statistical evidence for those specific contrasts under the sponsor’s analysis. The recalculated comparisons provide a separate, unadjusted view of posted summary statistics, with the sponsor’s results taking precedence because the record flags a discrepancy.

These results do not establish that one dose is superior to the other azilsartan medoxomil dose. The recalculated interval for their primary endpoint comparison includes zero, and the registry record does not report an equivalence or noninferiority framework for that comparison. Nor do mean changes establish what any individual participant experienced. Group averages do not describe the full distribution of outcomes.

The findings are limited to the measured endpoints, analysis population, and study period recorded. They do not establish longer-term effects, effects on outcomes not measured in the study, or a complete safety profile. The primary analysis used last observation carried forward, while details about missing measurements and sensitivity analyses are not reported in the registry record. Secondary outcomes broaden the blood-pressure description but require caution because multiplicity handling is not reported. Statistical evidence about a measured endpoint is not, by itself, a complete judgment about clinical importance or treatment choice. These interpretations describe the posted data and do not constitute medical advice.

18. Why This Trial Matters Statistically

This study illustrates why a clinical trial result should be read at several levels: the endpoint definition, the group means, the between-group contrast, its confidence interval, and the analysis method. A within-group decrease is not itself evidence of a treatment difference. The randomized comparison is the relevant framework for the treatment question, and the sponsor’s adjusted ANCOVA contrasts are distinct from recalculations made from group summaries.

It also shows how contrast direction can make the same pair of groups appear with opposite signs. Labels and subtraction order are essential to interpreting estimates. Confidence intervals add information that a p-value alone cannot provide: they show a range of plausible contrast values under the analysis and indicate how precisely the contrast is estimated.

The registry record also illustrates the limits of secondary analyses. Multiple blood-pressure measures can help describe whether findings extend across clinic and ambulatory measurements, but unadjusted testing across many outcomes requires caution. Missing-data methods and analysis populations are similarly important: the record names a full analysis set with last observation carried forward, yet does not report missingness details or sensitivity analyses. Finally, planning values derived from observed effects are not evidence of the completed trial’s power. They illustrate how sample-size requirements depend on the effect a future study aims to detect and the assumptions used for planning.

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 registry record does not report the original sample-size justification, its design assumptions, the allocation ratio, or the full randomization procedure. It does not report whether interim analyses were planned. These details limit independent assessment of the trial’s original design choices.

For the primary outcome, the record specifies a full analysis set with last observation carried forward but does not give missing-data counts, reasons for missingness, or sensitivity analyses. It identifies the sponsor’s ANCOVA method but does not provide the complete model specification. The recalculated contrasts are approximate, unadjusted estimates and differ in method from the sponsor’s analyses; the record flags this discrepancy, so sponsor results take precedence.

The registry record does not describe multiplicity control for the many outcome measures and analyses. Therefore, secondary p-values should not be read as though they necessarily account for the full set of comparisons. The posted safety information is also descriptive: event counts do not establish causality, and deaths are not reported in the registry record. Finally, the primary endpoint covers clinic systolic blood pressure through Week 24. The results do not, on their own, address outcomes beyond the recorded measures and timeframe. These are limitations of what can be assessed from the registry record, rather than proof that a particular analysis or study procedure was inadequate.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety Study of Azilsartan Medoxomil Compared to Ramipril for Treating Essential Hypertension — NCT00760214.
• Registry record last updated 2012-11-15; status last verified 2012-11.
• Results first posted 2011-04-19.
• 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

NCT00760214 is a completed phase 3 randomized, quadruple-masked, parallel-group study sponsored by Takeda. It enrolled 885 participants with essential hypertension and compared azilsartan medoxomil 40 mg once daily, azilsartan medoxomil 80 mg once daily, and ramipril 10 mg once daily.

The primary endpoint was change from baseline to Week 24 in mean trough clinic sitting systolic blood pressure. The sponsor reported ANCOVA comparisons of each azilsartan medoxomil group with ramipril, with 95% confidence intervals and p-values below .001. Recalculated unadjusted comparisons are approximate, and the registry record flags a discrepancy; the sponsor’s own analyses take precedence. Secondary outcomes cover additional clinic and ambulatory blood-pressure measures. The record does not report multiplicity handling, detailed missing-data information, or the original sample-size justification.