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Heart FailurePhase 3NCT00634712

CHARM-Preserved: Complete Statistical Analysis of Candesartan Cilexetil in Heart Failure

An independent statistical review of the randomized phase 3 CHARM-Preserved trial evaluating candesartan cilexetil versus placebo in patients with congestive heart failure.

Acronym: CHARM-Preserved · Status: Completed
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

CHARM-Preserved was a randomized, double-blind, parallel phase 3 treatment trial evaluating candesartan cilexetil in congestive heart failure.

734
Enrollment
2
Arms
3
Phase
1999-06
Start date
FeatureCHARM-Preserved
ConditionCongestive Heart Failure
DesignRandomized, parallel, double-blind
Primary purposeTreatment
InterventionsCandesartan (drug); Placebo (drug)
Lead sponsorAstraZeneca
Primary completion date2003-05

2. Clinical Question

Population

Patients with congestive heart failure.

Intervention

Candesartan cilexetil.

Comparator

Placebo.

Primary question

Whether candesartan cilexetil affected cardiovascular mortality or hospitalization due to congestive heart failure.

3. Trial Design

01
Randomization
734 patients
02
Assignment
2 arms
03
Masking
Double
04
Follow-up
Registry timeframe
05
Endpoint
CV mortality or HF hospitalization
ArmIntervention
Candesartan armCandesartan (drug)
Control armPlacebo (drug)

4. Endpoints

EndpointRegistry definitionTime frame
Primary endpointCardiovascular mortality or hospitalisation due to congestive heart failure, 4, 6 weeks, 6 months, every 4 months thereafter until 24 months

5. Planned Analysis

The ClinicalTrials.gov record identifies the primary endpoint as a composite cardiovascular time-to-event outcome involving cardiovascular mortality or hospitalization due to congestive heart failure. Results have not been posted on ClinicalTrials.gov.

For a composite endpoint of mortality and hospitalization, clinical trials commonly analyze the time until the first occurrence of either component using survival analysis methods. These methods account for patients who have different follow-up durations and may remain event-free at the end of observation.

6. Statistical Methodology

Composite endpoints

A composite endpoint combines multiple clinically meaningful events into one outcome. The analysis generally compares the time until the first qualifying event between randomized groups.

Why composite endpoints require interpretation

A composite result reflects the combined behavior of its components. Mortality events and hospitalization events may differ in clinical importance and frequency, so interpretation requires understanding which components contribute most strongly to the observed comparison.

Time-to-event analysis

Time-to-event methods are designed for outcomes where both the occurrence and timing of events matter. Patients without an observed event at the end of follow-up contribute information through their available observation period.

Randomization and masking

Random allocation helps balance known and unknown prognostic factors between treatment groups. Double masking reduces the possibility that knowledge of assigned treatment influences outcome assessment or patient management.

7. Statistical Methods Explained

Why use a composite endpoint?

Combining cardiovascular mortality and heart-failure hospitalization can increase the number of observed events compared with mortality alone, potentially improving statistical efficiency. The tradeoff is that each component must be interpreted separately when understanding clinical meaning.

How are cardiovascular death and hospitalization outcomes usually analyzed?

These outcomes are typically evaluated using time-to-event approaches because patients may have different follow-up durations and some observations may be censored.

What does randomization accomplish?

Randomization creates comparable treatment groups on average, allowing differences in outcomes to be attributed more reliably to the assigned intervention.

Why does double masking matter?

Masking helps limit bias by preventing participants and investigators from knowing treatment assignment during the study period.

Why does follow-up duration matter?

The registry specifies assessments through 24 months, meaning outcome interpretation depends on the amount of time patients are observed for cardiovascular events.

8. Limitations

9. Why This Trial Matters Statistically

ConceptHow it appears in CHARM-Preserved
Randomized trial designRandomized parallel comparison
BlindingDouble masking
Composite endpointCardiovascular mortality or hospitalization due to congestive heart failure
Time-to-event analysisAppropriate framework for outcomes occurring over follow-up

10. Related Tutorials

Learn more about the methods used in this trial:

11. Related Calculators

12. Sources