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Hypertension Phase 4 Prevention NCT00122811

HYVET: Complete Statistical Analysis of Antihypertensive Therapy in Very Elderly Patients

An independent statistical review of the Hypertension in the Very Elderly Trial (HYVET), a randomized, quadruple-masked phase 4 prevention study evaluating antihypertensive therapy in patients with hypertension.

ClinicalTrials.gov identifier: NCT00122811
Scope of this record

This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record.

1. Trial at a Glance

HYVET was a randomized, parallel-group, quadruple-masked phase 4 trial evaluating antihypertensive therapy for hypertension in very elderly patients.

4000
Enrollment
2000-11
Start Date
4
Phase
NCT00122811
Registry ID
FeatureHYVET
ConditionHypertension
AllocationRandomized
Design modelParallel
MaskingQuadruple
Primary purposePrevention
Lead sponsorImperial College London
Sponsor typeOther

2. Clinical Question

Population

Patients with hypertension enrolled in the Hypertension in the Very Elderly Trial.

Intervention

Indapamide SR 1.5mg and Perindopril 2-4mg.

Comparator

The registry identifies the randomized trial design but does not report comparator details in the available record.

Primary question

The trial evaluated whether the intervention affected the occurrence of all strokes (fatal and non-fatal).

3. Trial Design

Randomization

Participants were randomly allocated.

Masking

The study used quadruple masking.

Structure

Parallel-group design.

Purpose

Prevention.

4. Endpoints

EndpointDefinitionTime Frame
All strokes (fatal and non-fatal)Primary endpointDuration of trial

5. Planned Analysis

The registry identifies the primary endpoint as all strokes (fatal and non-fatal) over the duration of the trial. No results or posted statistical analyses are available in the ClinicalTrials.gov record.

For a randomized time-to-event cardiovascular endpoint such as stroke occurrence, analyses commonly compare event rates between randomized groups using survival-analysis approaches. These methods account for participants who may not experience the event before the end of follow-up or who have incomplete observation.

Conceptual time-to-event framework
Survival probability S(t) = probability of remaining free of the event through time t

The analysis focuses on the timing of events rather than only whether an event occurred, allowing follow-up duration to contribute information.

6. Statistical Methodology

Randomization

Randomization creates treatment groups that can be compared without assigning treatment based on participant characteristics. This design supports causal interpretation of differences between randomized groups.

Time-to-event analysis

The primary endpoint is an event occurring over the duration of follow-up. Statistical methods for these endpoints typically incorporate censoring, where individuals contribute follow-up information until the last observed time if the event has not occurred.

Interpretation of hazard-based measures

When hazard ratios are used, they describe relative event rates over time under a statistical model. They do not directly represent the percentage of individuals who experience or avoid an event.

7. Statistical Methods Explained

Why is randomization important in HYVET?

Randomization reduces systematic differences between groups at baseline, allowing the comparison of outcomes to reflect the assigned intervention more directly.

Why analyze strokes over time instead of only counting strokes?

Time-to-event methods use both whether an event occurred and when it occurred, which is important when participants have different lengths of follow-up.

What does censoring mean?

Censoring occurs when follow-up ends before the event is observed. Appropriate statistical methods preserve the information contributed before that point.

Why does masking matter statistically?

Masking can reduce the influence of expectations on treatment administration, outcome assessment, and reporting.

Why are confidence intervals important?

Confidence intervals describe uncertainty around estimated treatment effects and help distinguish precise estimates from those with substantial uncertainty.

Why are registry endpoints important?

Prespecified endpoints define the outcomes the trial was designed to evaluate and help distinguish planned analyses from exploratory questions.

8. Limitations

9. Why This Trial Matters Statistically

HYVET illustrates several foundational principles of randomized clinical trial analysis.

ConceptApplication
RandomizationCreates comparable intervention groups.
MaskingReduces potential assessment and performance bias.
Time-to-event analysisAppropriate framework for outcomes occurring over follow-up.
Clinical endpointsFocuses evaluation on meaningful patient outcomes.

10. Sources