This page separates reported trial results from statistical interpretation. The numerical results presented here are restricted to the ClinicalTrials.gov record. ClinicalTrials.gov provides the official trial registry record.
1. Trial at a Glance
RED-HF was a randomized, parallel-group, quadruple-masked phase 3 trial evaluating darbepoetin alfa versus placebo in heart failure. The registry reports 2278 randomized participants and a primary time-to-event endpoint combining all-cause death or first hospitalization for worsening heart failure.
| Feature | RED-HF |
|---|---|
| Phase | Phase 3 |
| Therapeutic area | Cardiology |
| Conditions | Heart Failure; Anemia; Cardiovascular Disease; Ventricular Dysfunction; Congestive Heart Failure |
| Design | Randomized, parallel-group, quadruple-masked |
| Allocation | Randomized |
| Primary purpose | Treatment |
| Enrollment | 2278 |
| Interventions | Darbepoetin alfa; placebo |
| Trial status | Completed |
| Start | June 1, 2006 |
| Primary completion | October 11, 2012 |
| Lead sponsor | Amgen |
| ClinicalTrials.gov | NCT00358215 |
2. Clinical Question
The statistical question was whether randomized treatment assignment to darbepoetin alfa, compared with placebo, was associated with a difference in the time from randomization to all-cause death or first hospitalization for worsening heart failure.
Population
Participants enrolled in a phase 3 trial addressing heart failure and anemia, within the registry's listed cardiovascular and ventricular-dysfunction conditions.
Intervention
Darbepoetin alfa.
Comparator
Placebo.
Primary question
Does randomized treatment assignment produce a difference in time to all-cause death or first hospitalization for worsening heart failure?
3. Trial Design
Placebo
- Placebo treatment assignment
- Compared with darbepoetin alfa under the randomized parallel-group design
- Included in the ITT efficacy analysis
Darbepoetin alfa
- Darbepoetin alfa treatment assignment
- Compared with placebo under the randomized parallel-group design
- Included in the ITT efficacy analysis
4. Endpoints
| Endpoint | Registry definition | Time frame | Type |
|---|---|---|---|
| Time to All Cause Death or First Hospitalization for Worsening Heart Failure | Time to death from any cause or first hospital admission for worsening heart failure, adjudicated by the Clinical Endpoint Committee, whichever occurred first. Participants without a qualifying event were censored at their last contact time or the study termination date, whichever occurred first. | From randomization to the end of study; maximum time on study was 73 months | Time-to-event |
| Time to Death From Any Cause | Time-to-event endpoint analyzed from randomization to the end of study. | From randomization to the end of study; maximum time on study was 73 months | Time-to-event |
| Time to Cardiovascular Death or First Hospital Admission for Worsening Heart Failure | Time-to-event endpoint analyzed from randomization to the end of study. | From randomization to the end of study; maximum time on study was 73 months | Time-to-event |
| Change From Baseline to Month 6 in KCCQ Overall Summary Score | Change from baseline in Kansas City Cardiomyopathy Questionnaire Overall Summary Score. | Baseline and Month 6 | Continuous |
| Change From Baseline to Month 6 in KCCQ Symptom Frequency Score | Change from baseline in KCCQ Symptom Frequency Score. | Baseline and Month 6 | Continuous |
The registry identifies one primary endpoint: time to all-cause death or first hospitalization for worsening heart failure. The other four posted outcome measures are secondary endpoints in the ClinicalTrials.gov record.
5. Analysis Populations and Statistical Comparisons
| Analysis | Population | Groups compared | Method |
|---|---|---|---|
| Primary time-to-event analysis | Intent-to-treat analysis set, defined as all randomized participants | Placebo vs Darbepoetin Alfa | Stratified log-rank test; hazard ratio and 95% CI from a Cox proportional-hazards model adjusted by the stratification factors |
| Death from any cause | Intent-to-treat | Placebo vs Darbepoetin Alfa | Stratified log-rank test; Cox proportional-hazards model adjusted by the stratification factors |
| Cardiovascular death or first hospitalization for worsening heart failure | Intent-to-treat | Placebo vs Darbepoetin Alfa | Stratified log-rank test; Cox proportional-hazards model adjusted by the stratification factors |
| KCCQ Overall Summary Score | ITT participants with non-missing change from baseline to Month 6 | Placebo vs Darbepoetin Alfa | Mixed-effects model adjusted for region, type of device, and baseline KCCQ score |
| KCCQ Symptom Frequency Score | ITT participants with non-missing change from baseline to Month 6 | Placebo vs Darbepoetin Alfa | Mixed-effects model adjusted for region, type of device, and baseline KCCQ score |
The registry's normalized methods for the posted analyses are stratified log-rank testing and a mixed-effects model. The time-to-event effect estimates are hazard ratios, while the KCCQ analyses use least-squares mean differences.
6. Statistical Methodology
Kaplan-Meier estimation
The registered primary endpoint is a time-to-event outcome, and its definition specifies that it was estimated by the Kaplan-Meier method. This is appropriate when participants can be followed for different lengths of time and some participants have not experienced the qualifying event when follow-up ends.
Here, di represents events at an event time and ni represents participants at risk immediately before that time. Censored participants contribute information up to their censoring time.
Stratified log-rank test
The primary and other time-to-event analyses used a stratified log-rank test. A stratified log-rank test compares event-time experience between randomized groups while accounting for prespecified stratification factors. The ClinicalTrials.gov record does not identify the individual stratification factors, so they are not specified here.
Cox proportional-hazards model
The registry states that the hazard ratio and 95% confidence interval were obtained from a Cox proportional-hazards model adjusted by the stratification factors. The Cox model provides a relative event-rate measure while allowing follow-up times and censoring to contribute to the analysis.
For this record, the analysis is reported as a comparison of Placebo vs Darbepoetin Alfa. The hazard ratio should therefore be interpreted together with the stated comparison direction, confidence interval, follow-up framework, and model assumptions.
Intention-to-treat analysis
The primary endpoint was analyzed using the intent-to-treat (ITT) analysis set, defined as all randomized participants. This keeps participants associated with their randomized assignment rather than redefining treatment groups according to subsequent treatment exposure. The ITT principle is particularly important in randomized trials because it preserves the treatment comparison established by randomization.
Mixed-effects model for KCCQ outcomes
The two KCCQ outcomes were analyzed using a mixed-effects model. The model estimated treatment differences while adjusting for region, type of device, and baseline KCCQ score. The analysis population was restricted to ITT participants with non-missing change from baseline to Month 6.
Adjustment can improve precision when baseline or design variables explain variation in the outcome. It does not turn an observational comparison into a randomized one; here, the treatment comparison remains anchored to randomized assignment.
7. Results: Primary Endpoint
The registry reports a formal statistical analysis for the primary endpoint, using the ITT analysis set and a stratified log-rank test. The reported hazard ratio and confidence interval come from the stratification-adjusted Cox proportional-hazards model.
Time to All Cause Death or First Hospitalization for Worsening Heart Failure
Hazard ratio
95% CI: 0.90–1.13 · P = 0.871
Analysis: stratified log-rank test; Cox proportional-hazards model adjusted by the stratification factors.
| Primary endpoint | Comparison | Estimate | 95% CI | P-value |
|---|---|---|---|---|
| Time to all-cause death or first hospitalization for worsening heart failure | Placebo vs Darbepoetin Alfa | HR 1.01 | 0.90–1.13 | 0.871 |
The reported hazard ratio of 1.01 is very close to 1. Under the reported comparison and fitted model, the estimated instantaneous rate of the composite event was approximately the same between the compared groups. More precisely, an HR of 1.01 corresponds to an estimated hazard ratio that is 1% above 1, but this should not be described as a 1% increase in each patient's risk.
The 95% confidence interval of 0.90–1.13 quantifies uncertainty around the estimated hazard ratio. It spans values below and above 1, so the data are compatible with a range of relative hazard differences in either direction under the model and sampling framework.
The P-value of 0.871 is a measure of compatibility with the null hypothesis used for the superiority comparison under the specified statistical test. It is not a measure of effect size, clinical importance, or the probability that either treatment is effective.
Because this is a Cox-model hazard ratio, interpretation also depends on the model's proportional-hazards assumption. A single HR summarizes the relative event rate over the analyzed follow-up; it does not mean that every participant experienced the same relative change in risk.
The primary analysis used the ITT population and incorporated censoring through the time-to-event framework. Participants without a qualifying event were censored at their last contact time or the study termination date, whichever occurred first.
8. Results: Secondary Time-to-Event Endpoints
Time to Death From Any Cause
Hazard ratio for all-cause death
95% CI: 0.92–1.19 · P = 0.512
The analysis was conducted in the ITT population using a stratified log-rank test. The hazard ratio and 95% confidence interval came from a Cox proportional-hazards model adjusted by the stratification factors.
| Endpoint | Comparison | HR | 95% CI | P-value |
|---|---|---|---|---|
| Time to Death From Any Cause | Placebo vs Darbepoetin Alfa | 1.04 | 0.92–1.19 | 0.512 |
| Time to Cardiovascular Death or First Hospital Admission for Worsening Heart Failure | Placebo vs Darbepoetin Alfa | 1.01 | 0.89–1.14 | 0.922 |
Time to Cardiovascular Death or First Hospital Admission for Worsening Heart Failure
Hazard ratio for the composite endpoint
95% CI: 0.89–1.14 · P = 0.922
These secondary time-to-event results are directionally close to the primary estimate. Their confidence intervals include 1, and the registry-reported P-values are 0.512 and 0.922, respectively. These are secondary endpoint analyses and should be interpreted separately from the primary endpoint rather than combined into a single summary statistic.
For the all-cause mortality endpoint, an HR of 1.04 means the fitted model estimated a hazard ratio close to 1 for the stated Placebo-versus-Darbepoetin Alfa comparison. The 95% CI of 0.92–1.19 shows uncertainty extending modestly on both sides of 1.
For cardiovascular death or first hospitalization for worsening heart failure, the HR was 1.01, with a 95% CI of 0.89–1.14. Again, the interval includes 1 and therefore does not identify a directionally separated estimate under the stated model.
The P-values of 0.512 and 0.922 describe evidence against the relevant null hypotheses; they do not quantify how clinically important either treatment effect is. A P-value should not be converted into a probability that the null hypothesis is true.
9. Results: KCCQ Overall Summary Score
The registry reports a secondary continuous endpoint measuring change from baseline to Month 6 in the Kansas City Cardiomyopathy Questionnaire Overall Summary Score. The analysis population consisted of ITT participants with non-missing change from baseline to Month 6.
Least-squares mean difference
95% CI: 0.65–3.75 · P = 0.005
Mixed-effects model adjusted for region, type of device, and baseline KCCQ score.
| Endpoint | Comparison | Effect measure | 95% CI | P-value |
|---|---|---|---|---|
| Change from baseline to Month 6 in KCCQ Overall Summary Score | Placebo vs Darbepoetin Alfa | Least Squares Mean Difference 2.20 | 0.65–3.75 | 0.005 |
The reported adjusted mean difference was 2.20 KCCQ units for the stated Placebo-versus-Darbepoetin Alfa comparison. A mean difference is an absolute difference on the KCCQ score scale, not a hazard ratio and not a percentage change in survival.
The 95% CI of 0.65–3.75 describes uncertainty around the estimated adjusted mean difference. It indicates that the estimated difference is not known with perfect precision; the interval gives a range of values compatible with the statistical model and data under the stated confidence framework.
The P-value of 0.005 indicates stronger statistical evidence against the null hypothesis of no adjusted mean difference than would be indicated by a conventional 0.05 threshold. The P-value does not say that the difference is clinically important, nor does it measure the magnitude of the 2.20-unit estimate.
The interpretation should also respect the analysis population: participants with missing baseline-to-Month-6 change were not part of this particular posted analysis. Consequently, the KCCQ result should not automatically be treated as identical to an analysis using every randomized participant regardless of missing outcome data.
10. Results: KCCQ Symptom Frequency Score
The second continuous secondary endpoint assessed change from baseline to Month 6 in the KCCQ Symptom Frequency Score, using the same general mixed-effects modeling framework.
Least-squares mean difference
95% CI: 0.53–4.05 · P = 0.011
Mixed-effects model adjusted for region, type of device, and baseline KCCQ score.
| Endpoint | Comparison | Effect measure | 95% CI | P-value |
|---|---|---|---|---|
| Change from baseline to Month 6 in KCCQ Symptom Frequency Score | Placebo vs Darbepoetin Alfa | Least Squares Mean Difference 2.29 | 0.53–4.05 | 0.011 |
The adjusted mean difference was 2.29 KCCQ units for the reported comparison. The corresponding 95% CI was 0.53–4.05, providing an uncertainty interval around the adjusted estimate.
The P-value of 0.011 is evidence against the specified null hypothesis of no adjusted mean difference under the posted model. It does not establish the clinical importance of a 2.29-unit difference and should not be interpreted as the probability that the observed difference occurred by chance.
As with the Overall Summary Score, this was not a simple unadjusted comparison of raw mean changes. The mixed-effects model adjusted for region, type of device, and baseline KCCQ score, and the analysis population required a non-missing baseline-to-Month-6 change.
11. Putting the Results Together
| Endpoint | Type | Effect estimate | 95% CI | P-value | Method |
|---|---|---|---|---|---|
| All-cause death or first hospitalization for worsening heart failure | Primary time-to-event | HR 1.01 | 0.90–1.13 | 0.871 | Stratified log-rank; stratification-adjusted Cox model |
| Death from any cause | Secondary time-to-event | HR 1.04 | 0.92–1.19 | 0.512 | Stratified log-rank; stratification-adjusted Cox model |
| Cardiovascular death or first hospitalization for worsening heart failure | Secondary time-to-event | HR 1.01 | 0.89–1.14 | 0.922 | Stratified log-rank; stratification-adjusted Cox model |
| KCCQ Overall Summary Score change | Secondary continuous | Mean difference 2.20 | 0.65–3.75 | 0.005 | Mixed-effects model |
| KCCQ Symptom Frequency Score change | Secondary continuous | Mean difference 2.29 | 0.53–4.05 | 0.011 | Mixed-effects model |
The statistical pattern is important: the posted primary time-to-event analysis has a hazard ratio of 1.01 with a 95% CI of 0.90–1.13 and P = 0.871, while the two KCCQ analyses have positive reported least-squares mean differences with P-values of 0.005 and 0.011. These are different endpoint types answering different questions. A treatment effect on a patient-reported continuous outcome cannot be substituted for an effect on a time-to-event composite.
12. Safety Results
The ClinicalTrials.gov record reports serious adverse events by treatment arm as affected participants divided by participants at risk.
| Safety measure | Placebo | Darbepoetin Alfa |
|---|---|---|
| Serious adverse events | 741 / 1140 affected / at risk | 781 / 1133 affected / at risk |
These figures describe the number of participants affected and the number at risk in each arm as reported in the registry data. They should not be converted into a new percentage or comparative effect estimate here because the task requires the trial's reported numbers to be preserved exactly and does not provide a formal statistical analysis for this safety measure.
13. Statistical Methods Explained
Why was a stratified log-rank test used?
The primary outcome is a time-to-event endpoint with potentially different follow-up times and censoring. A log-rank test compares the survival experience of randomized groups across event times. Stratification allows the comparison to account for the trial's stratification factors rather than ignoring them. The ClinicalTrials.gov record does not identify those factors individually.
What does a hazard ratio of 1.01 mean?
For the primary endpoint, the reported HR was 1.01 for the stated Placebo-versus-Darbepoetin Alfa comparison. A hazard ratio of 1 would indicate equal estimated hazards under the model; 1.01 is extremely close to that reference value. It does not mean that the groups had exactly equal event probabilities at every time point.
Why is the confidence interval important?
The 95% CI of 0.90–1.13 shows the precision of the primary hazard-ratio estimate. It is more informative than the point estimate alone because it shows that the estimated treatment contrast has uncertainty extending both below and above a hazard ratio of 1.
Why doesn't the P-value measure effect size?
A P-value describes how compatible the observed data are with a specified null hypothesis under the statistical model and testing procedure. It depends on both the magnitude of an effect and the amount of information available. Effect size is described by the hazard ratio or mean difference; uncertainty is described by the confidence interval.
Why was a mixed-effects model used for KCCQ?
The KCCQ endpoints are continuous outcomes measured as change from baseline to Month 6. The registry reports a mixed-effects model adjusted for region, type of device, and baseline KCCQ score. This provides an adjusted least-squares mean difference rather than simply comparing unadjusted arithmetic means.
What does the KCCQ mean difference represent?
A least-squares mean difference of 2.20 or 2.29 is a difference on the KCCQ score scale after the specified model adjustment. It is not a hazard ratio, relative risk, or percentage change. The statistical interpretation therefore requires attention to the score's scale and the adjusted analysis rather than borrowing language from survival analysis.
Why does the ITT population matter?
The primary endpoint analysis used all randomized participants. An ITT analysis maintains the randomized comparison and reduces the risk that post-randomization treatment behavior changes the definition of the treatment groups. It also means that the primary result is a comparison of randomized strategies rather than simply a comparison of participants who remained exposed to treatment.
14. Censoring and Time-to-Event Interpretation
The primary endpoint was followed from randomization through the end of study, with a maximum time on study of 73 months. Participants who did not experience a qualifying event were censored at their last contact time or the study termination date, whichever occurred first.
Why censoring is necessary
Not every participant experiences the endpoint during observed follow-up. Censoring allows their available follow-up to contribute information without treating the absence of an observed event as proof that an event could never occur.
What the HR does not provide
A hazard ratio does not directly provide absolute event probabilities, median time to event, or the number needed to treat. Those quantities require additional information not contained in the registry-reported statistical results.
The registry's definition also specifies that the primary composite endpoint uses whichever occurred first: death from any cause or first hospital admission for worsening heart failure. A composite endpoint therefore combines its component events into a single time-to-first-event outcome.
15. Covariate Adjustment and Stratification
The time-to-event analyses were based on stratified log-rank tests, with hazard ratios and confidence intervals from Cox proportional-hazards models adjusted by the stratification factors. The ClinicalTrials.gov record does not name those factors, so no additional variables are inferred.
The KCCQ analyses used a different adjustment strategy: the mixed-effects model adjusted for region, type of device, and baseline KCCQ score. This distinction is statistically important. Adjustment variables are part of the model specification and should not be assumed to be interchangeable between endpoint analyses.
| Component | Time-to-event analysis | KCCQ analysis |
|---|---|---|
| Endpoint type | Time-to-event | Continuous change from baseline |
| Primary method | Stratified log-rank test | Mixed-effects model |
| Effect measure | Hazard ratio | Least-squares mean difference |
| Adjustment described in registry | Stratification factors in Cox model | Region, type of device, baseline KCCQ score |
| Analysis population | ITT; all randomized participants for primary endpoint | ITT participants with non-missing Month 6 change |
16. Missing Data and Analysis Population
The ClinicalTrials.gov record explicitly define the primary time-to-event analysis population as all randomized participants. For the two KCCQ analyses, the population was ITT participants with non-missing change from baseline to Month 6.
This difference matters when interpreting the results. The primary endpoint does not require a Month 6 measurement because it is a time-to-event outcome. The KCCQ analyses, by contrast, require the relevant baseline and Month 6 information needed to calculate the posted change endpoint.
17. Multiplicity and the Endpoint Hierarchy
The registry data identify one primary endpoint and four additional posted outcome measures. The ClinicalTrials.gov record identifies the four additional outcomes as secondary analyses.
| Endpoint | Role | Statistical framework |
|---|---|---|
| All-cause death or first hospitalization for worsening heart failure | Primary | Stratified log-rank; Cox model |
| Death from any cause | Secondary | Stratified log-rank; Cox model |
| Cardiovascular death or first hospitalization for worsening heart failure | Secondary | Stratified log-rank; Cox model |
| KCCQ Overall Summary Score change | Secondary | Mixed-effects model |
| KCCQ Symptom Frequency Score change | Secondary | Mixed-effects model |
The ClinicalTrials.gov record does not provide an alpha-allocation scheme, multiplicity adjustment procedure, or hierarchical testing sequence. Therefore, the secondary P-values should be reported as posted rather than treated as though a particular multiplicity-control strategy had been documented.
18. Interim Analysis, Non-Inferiority, Crossover, and Bayesian Methods
Interim analysis
The ClinicalTrials.gov record does not report an interim-analysis procedure or alpha-spending strategy.
Non-inferiority
The posted analyses are identified as superiority analyses. No non-inferiority margin is reported in the ClinicalTrials.gov record.
Crossover
No crossover design or crossover analysis is reported in the ClinicalTrials.gov record.
Bayesian methods
No Bayesian analysis is identified in the ClinicalTrials.gov record.
These omissions are analytically relevant. They prevent assumptions about unreported design features from being presented as facts. The page therefore focuses on the methods explicitly documented in the ClinicalTrials.gov record: randomized allocation, ITT analysis, stratified log-rank testing, Cox proportional-hazards modeling, and mixed-effects modeling.
19. Hazard Ratio: A Careful Interpretation
The primary hazard ratio was 1.01. Because the registry-reported comparison is Placebo vs Darbepoetin Alfa, the estimate is very close to the value 1 that represents equal modeled hazards. The estimate does not imply identical individual outcomes or identical cumulative event probabilities at every time point.
The 95% CI of 0.90–1.13 expresses uncertainty around the estimated hazard ratio. It includes 1, meaning the interval spans both a lower-hazard and higher-hazard direction relative to the reference value.
The P = 0.871 result is not an effect-size measure. A large P-value does not prove that two treatments are identical, just as a small P-value would not by itself establish that an effect is clinically meaningful.
The Cox model is a proportional-hazards model. The hazard ratio is therefore a model-based summary and should not automatically be interpreted as a constant relative difference in cumulative risk over the entire follow-up period.
20. Clinical Interpretation vs Statistical Interpretation
Statistical interpretation
The posted primary time-to-event analysis estimated an HR of 1.01 with a 95% CI of 0.90–1.13 and P = 0.871. The analysis used a stratified log-rank test and a stratification-adjusted Cox model in the ITT population.
Secondary outcomes
The two KCCQ outcomes had reported least-squares mean differences of 2.20 and 2.29, with 95% CIs of 0.65–3.75 and 0.53–4.05 and P-values of 0.005 and 0.011, respectively.
These results should not be compressed into a single overall statistic. The primary endpoint measures time to a clinical event, whereas KCCQ measures change on a patient-reported outcome scale at Month 6. Their estimates have different meanings and arise from different statistical models.
21. Important Limitations and Interpretation Issues
- Registry-level detail: the ClinicalTrials.gov record provides the principal endpoint definitions and posted analyses but do not provide the full statistical analysis plan.
- Hazard-ratio interpretation: the Cox hazard ratio is model-based and depends on the proportional-hazards framework.
- Censoring: time-to-event analyses rely on the observed follow-up and specified censoring rules.
- Composite endpoint: the primary outcome combines all-cause death and first hospitalization for worsening heart failure, so the result does not isolate the treatment contrast for each component.
- Secondary endpoints: the KCCQ results are secondary analyses and should not be treated as replacements for the primary endpoint.
- KCCQ analysis population: the posted analysis includes ITT participants with non-missing baseline-to-Month-6 change, which differs from the all-randomized population used for the primary time-to-event analysis.
- Multiplicity: the ClinicalTrials.gov record does not specify an adjustment procedure for the four secondary endpoints, so no particular familywise-error interpretation is imposed here.
- Missing-data method: the ClinicalTrials.gov record does not identify a specific imputation strategy for missing KCCQ measurements.
- Unreported design details: no non-inferiority margin, crossover procedure, Bayesian method, or interim-analysis/alpha-spending strategy is reported.
- Clinical interpretation: statistical significance of a secondary continuous endpoint does not by itself establish the clinical importance of that difference.
22. Why This Trial Matters Statistically
RED-HF provides a useful teaching case because it places two different statistical frameworks within the same randomized trial: survival analysis for clinical time-to-event outcomes and mixed-effects modeling for patient-reported continuous outcomes.
| Concept | How it appears in RED-HF |
|---|---|
| Randomization | 2278 participants were enrolled in a randomized, parallel-group phase 3 design. |
| Blinding | The registry classifies the study as quadruple-masked. |
| ITT analysis | The primary endpoint was analyzed in all randomized participants. |
| Kaplan-Meier estimation | The registered primary time-to-event endpoint was estimated by Kaplan-Meier methods. |
| Hazard ratio | The primary and secondary time-to-event analyses report hazard ratios. |
| Stratified log-rank test | Used for the primary and secondary time-to-event comparisons. |
| Cox model | Provided hazard ratios and confidence intervals adjusted by the stratification factors. |
| Confidence intervals | Reported as two-sided 95% intervals for all five statistical analyses. |
| Mixed-effects model | Used for both Month 6 KCCQ change outcomes. |
| Covariate adjustment | KCCQ models adjusted for region, type of device, and baseline KCCQ score. |
| Composite endpoint | The primary endpoint combines all-cause death and first hospitalization for worsening heart failure. |
| Censoring | Participants without a qualifying primary event were censored at last contact or study termination, whichever occurred first. |
23. Related Tutorials
Learn more about the methods used in this trial:
24. Related Calculators
25. Sources
- ClinicalTrials.gov: RED-HF, NCT00358215.
- PubMed: PMID 36791280.
- PubMed: PMID 30051179.
- PubMed: PMID 29367268.
Continue through the Clinical Biostats statistical pathway
Use the trial's methods as a starting point for deeper study of survival analysis, hazard ratios, confidence intervals, mixed-effects models, and randomized-trial methodology.
26. Record Summary
RED-HF is a useful statistical case study because its registry record combines a randomized, quadruple-masked phase 3 design with a primary composite time-to-event endpoint and two patient-reported continuous outcomes. The primary endpoint was analyzed using a stratified log-rank test and a stratification-adjusted Cox proportional-hazards model, producing an HR of 1.01 (95% CI 0.90–1.13; P = 0.871). The two additional time-to-event analyses produced HRs of 1.04 and 1.01, while the two KCCQ analyses produced least-squares mean differences of 2.20 and 2.29.
The key statistical lesson is that these estimates cannot be interpreted interchangeably. A hazard ratio describes a relative time-to-event contrast under a Cox model; a least-squares mean difference describes an adjusted difference on a continuous outcome scale. Confidence intervals quantify uncertainty around both types of estimates, while P-values address the corresponding null hypotheses rather than measuring effect magnitude or clinical importance.