Study to Evaluate Potential Decrease in Hospitalization Events, Time Between Events, and Increasing Longevity in Patients With Symptomatic Heart Failure (0954-948): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Evaluate Potential Decrease in Hospitalization Events, Time Between Events, and Increasing Longevity in Patients With Symptomatic Heart Failure (0954-948) (NCT00090259), a randomized phase 3 study. The primary outcome is Number of Participants That Experienced One Component of the Composite Clinical Endpoint of All Cause Death or Hospitalization for Heart Failure.

2. Clinical Question

The question concerns whether assignment to the higher-dose regimen was associated with a different clinical-event experience than assignment to the lower-dose regimen. Because the endpoint combines death and heart-failure hospitalization, it captures more than one type of clinically important event. The combined result does not, by itself, show how much each component contributed to the overall comparison. Component results are reported separately among the secondary outcomes, but they do not replace the prespecified primary outcome in interpreting the central trial question.

The result should be read as a comparison between randomized treatment groups over the trial’s follow-up, not as a comparison of individual responses. Randomization provides a framework for comparing groups, while the reported estimates describe the uncertainty around that comparison. The registry record does not report the original statistical plan, details of the endpoint-adjudication process, or the criteria used to define intolerance of ACE inhibitor treatment.

3. Trial Design

NCT00090259 is a Phase 3, randomized, double-blind, parallel-group study sponsored by Organon and Co. Its official title describes a multicenter comparison of two losartan doses in people with symptomatic heart failure who were intolerant of ACE inhibitor treatment. The registry status is completed. The recorded study start is 2001-12-19 and the primary completion date is 2009-03-31.

The study compared daily losartan 50 mg with a regimen titrated to daily losartan 150 mg. In the lower-dose arm, participants received a 50-mg losartan tablet with a 100-mg losartan placebo tablet from Week 1 through the end of the study, up to 4 years. In the higher-dose arm, the description specifies 50 mg in Week 1, 100 mg in Week 2, and 150 mg daily from Week 3 through the end of the study, up to 4 years. The tablet and placebo arrangements are consistent with maintaining masking across the different dose schedules; the registry identifies the study as double-blind.

The primary outcome analysis is identified as intention-to-treat. Its follow-up timeframe is entire follow-up, with a median of 4.7 years. The arm-specific numbers contributing to the posted primary outcome are 1913 for losartan 50 mg and 1921 for losartan 150 mg. These denominators describe the outcome record and should not be taken as a report of adherence to the assigned regimen.

The registry record does not report the randomization procedure, allocation concealment details, the exact sites or countries, the original sample-size justification, or the protocol’s detailed visit schedule. It also does not state the methods used to monitor adherence, manage treatment discontinuation, or handle crossover. Those omissions limit how fully the conduct of the trial can be reconstructed from the registry record alone.

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: Patients who were on a Angiotensin II Antagonist (AIIA) had the option to begin losartan treatment with open-label losartan 12.5 mg for one week followed by losartan 25 mg for one week and were subsequently randomized to losartan 50 mg or losartan 150 mg.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Intention-to-Treat

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 Number of Participants That Experienced One Component of the Composite Clinical Endpoint of All Cause Death or Hospitalization for Heart Failure, measured over Entire follow-up (median = 4.7 years).

The primary endpoint is the number of participants who experienced one component of the composite clinical endpoint of all-cause death or hospitalization for heart failure. The record describes the analysis population as intention-to-treat and the timeframe as entire follow-up, with a median of 4.7 years. The event counts are 889 among participants assigned to losartan 50 mg and 828 among participants assigned to losartan 150 mg.

A composite endpoint combines multiple outcomes into a single measure. General explanation: this approach can capture a wider range of clinically consequential events than a single component alone, and it can increase the number of recorded events available for comparison. Its interpretation depends on the components being meaningful and on understanding whether the overall result is driven mainly by one component. A composite does not mean that all components occurred in every participant, nor does the combined count identify which component occurred unless component data are examined separately.

Here, the endpoint combines death from any cause with hospitalization for heart failure. Death and hospitalization are distinct events, so the composite offers a broad summary of these outcomes but does not establish that the treatment groups differed in each component in the same way. Separate registry outcomes include deaths and heart-failure hospitalizations. The registry record does not provide the endpoint definition in further detail, such as how hospitalizations were adjudicated or whether repeat hospitalizations contributed to this participant-count endpoint.

7. Results Posted in the Registry

• Losartan 150 mg: 43.1% (828/1921) versus 46.5% (889/1913) on control; risk difference -3.4 percentage points (95% CI -6.5 to -0.2), risk ratio 0.93 (0.86–1.00); unadjusted two-proportion z-test p = 0.036.

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.

Number of Participants That Experienced One Components of the Composite Clinical Endpoint of All Cause Death or Cardiovascular Hospitalization

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Losartan 150 mg: 54.0% (1037/1921) versus 56.7% (1085/1913) on control; risk difference -2.7 percentage points (95% CI -5.9 to 0.4), risk ratio 0.95 (0.90–1.01); unadjusted two-proportion z-test p = 0.089.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Losartan 150 mg and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants That Died (Any Cause)

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Losartan 150 mg: 33.1% (635/1921) versus 34.8% (665/1913) on control; risk difference -1.7 percentage points (95% CI -4.7 to 1.3), risk ratio 0.95 (0.87–1.04); unadjusted two-proportion z-test p = 0.264.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Losartan 150 mg and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants That Were Hospitalized for Heart Failure

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Losartan 150 mg: 23.4% (450/1921) versus 26.3% (503/1913) on control; risk difference -2.9 percentage points (95% CI -5.6 to -0.1), risk ratio 0.89 (0.80–0.99); unadjusted two-proportion z-test p = 0.040.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Losartan 150 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes extend the primary comparison to cardiovascular hospitalization, all-cause death, and hospitalization for heart failure, including a composite of death or cardiovascular hospitalization. Taken together, their estimates generally point in the same direction as the primary comparison, with fewer participants experiencing the listed outcomes in the higher-dose group. The degree of statistical precision is not uniform: some reported intervals are compatible with no difference, while others lie on one side of the corresponding null value.

These results provide context for the primary composite, but they do not make the primary endpoint unnecessary. The secondary outcomes use different event definitions and should be interpreted as separate comparisons. In particular, the cardiovascular-hospitalization composite is not identical to the primary composite of all-cause death or heart-failure hospitalization. Likewise, an outcome concerning death alone does not answer the combined endpoint question.

Unadjusted secondary results carry less weight because multiple outcomes create multiple opportunities for apparently notable findings by chance. General explanation: when many hypotheses are tested, the chance of at least one small p-value can increase unless a plan controls the family-wise error rate or uses another multiplicity approach. The registry record does not report a multiplicity-adjustment method or a hierarchy for confirmatory secondary testing. Accordingly, secondary findings are best treated as supportive or descriptive evidence rather than as independent confirmation of the primary result.

The overall pattern is more informative than isolating any one secondary p-value, but it still does not establish that every outcome changed to the same extent. The record does not report further subgroup analyses, repeated-event analyses, or a prespecified method for integrating the secondary outcomes. Interpretation should therefore remain anchored in the primary endpoint and recognize the secondary analyses as additional, less definitive context.

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

• Number of Participants That Experienced One Components of the Composite Clinical Endpoint of All Cause Death or Cardiovascular Hospitalization
• Number of Participants That Died (Any Cause)
• Number of Participants That Were Hospitalized for Heart Failure
• Number of Participants That Experienced Cardiovascular Hospitalization

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is a binary participant-level outcome: whether a participant experienced the specified composite event during follow-up. The posted counts are compared between the two randomized groups. A participant-count endpoint is not a count of all events when someone can experience repeated events; the registry describes the primary result as the number of participants experiencing one component of the composite. The record does not provide a separate recurrent-event analysis for this outcome.

What does the risk difference express?

The recalculated risk difference expresses the difference between the observed proportions in the two groups, with the higher-dose group compared with the lower-dose group. General explanation: a risk difference is an absolute contrast on the probability scale. A negative value in this comparison means the observed event proportion is lower in the higher-dose group. Unlike a relative measure, it describes the gap between group proportions rather than their proportional relationship. The recalculated estimate is -0.034, and its confidence interval is -0.065 to -0.002.

This is a simple, unadjusted re-calculation from the posted group counts and denominators. It does not reproduce the trial’s time-to-event model. It also does not account for any covariates or adjustments that may have been used in the sponsor’s analysis; whether such adjustments were used is not reported in the registry record. The p-value associated with this re-calculation is unadjusted, and the registry does not report whether the study’s original analysis used this exact test.

Why is a hazard ratio also reported?

The registry reports a Cox regression analysis with a hazard ratio. General explanation: a Cox model uses information about the timing of events and the time participants remain under observation, rather than reducing follow-up to a simple event/no-event proportion alone. A hazard ratio compares the event hazard between groups over time. A value below 1 for the higher-dose group indicates a lower estimated hazard relative to the lower-dose group under the model. The reported primary hazard ratio is 0.899, with a 95% confidence interval from 0.818 to 0.988.

A hazard ratio is not the same as a risk ratio, a risk difference, or the probability that an individual will experience an event. Its interpretation depends on the model and its assumptions. General explanation: the Cox model commonly relies on proportional hazards, meaning the relative hazard between groups is treated as sufficiently stable over the modeled follow-up. Whether this assumption was checked, what censoring rules were used, and what covariates entered the model are not reported in the registry record.

How should the p-values be read?

The primary sponsor-reported p-value is 0.027 for the Cox-model analysis. The unadjusted p-value for the recalculated risk difference is 0.036. General explanation: a p-value quantifies how incompatible the observed data are with a specified null model, given the assumptions of the analysis. It is not the probability that the null hypothesis is true, and it does not measure the magnitude or clinical importance of an effect. The registry record does not describe an adjustment for testing multiple outcomes or analyses, so the p-values should not be treated as multiplicity-adjusted unless such an adjustment is documented elsewhere in the record.

The statistical analysis plan, primary hypothesis details, planned covariates, and rules for interim analyses are not reported in the registry record. Therefore, the posted analysis can be described, but it cannot be fully compared with an original prespecified analysis plan using this record alone. The registry identifies the primary population as intention-to-treat, but further details about participant inclusion, protocol deviations, or missing outcome information are not reported.

For binary outcomes, a confidence interval around a risk difference describes a range of values compatible with the observed data under the method used. General explanation: intervals that include zero are compatible with no difference on the risk-difference scale at the corresponding confidence level, whereas intervals wholly on one side of zero indicate estimates with a direction that is more clearly separated from no difference. For a hazard ratio, the corresponding null value is 1 rather than zero. These distinctions are important when comparing interval estimates reported on different scales.

The posted trial analysis and the recalculated comparison agree in direction for the primary outcome, but they are based on different statistical summaries. The sponsor’s Cox analysis incorporates time-to-event information; the simple recalculation compares participant proportions over the recorded follow-up. The registry reports no discrepancy between these results. Neither estimate can replace the other, and the sponsor’s model is the registry’s reported time-to-event analysis.

11. Confidence Intervals and Precision

The primary recalculated risk difference is -0.034, with a 95% confidence interval from -0.065 to -0.002. This interval is entirely below zero, so the range of values compatible with this unadjusted calculation points to a lower observed event proportion in the losartan 150 mg group. The interval nevertheless covers a range of possible difference magnitudes; it does not identify one exact effect.

The sponsor-reported Cox hazard ratio is 0.899, with a 95% confidence interval from 0.818 to 0.988. The interval is below the hazard-ratio null value of 1, and its upper limit is close to that value. General explanation: a confidence interval describes statistical uncertainty around an estimate under the analysis method and its assumptions. It is not a range that guarantees the true effect lies inside, and it does not describe variation in individual outcomes.

These two intervals use different scales and answer different versions of the comparison. The risk-difference interval concerns an absolute difference in recorded proportions; the hazard-ratio interval concerns a relative time-to-event measure. Their directions are consistent, but their numerical values should not be compared as if they were the same quantity. The registry record does not report the model diagnostics or sensitivity analyses that would help assess how robust the Cox interval is to its assumptions.

Precision is also specific to the endpoint and follow-up represented in the analysis. The primary result combines all-cause death and hospitalization for heart failure over entire follow-up, with a median of 4.7 years. The record does not supply confidence intervals for the component contributions within the composite. Thus, the primary interval characterizes the composite comparison, not each component separately or the effects at particular follow-up times.

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 because the primary endpoint is a binary participant-count outcome. They are not total event counts. The planning illustration assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. It uses the observed effect as its reference and considers planning for 100%, 75%, or 50% of that observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column describes the number of participants per arm that a hypothetical future study would need, under the stated assumptions, to have an 80% chance of detecting the specified effect if that effect were present. The 90% power column gives the corresponding planning target for a higher chance of detection under the same assumptions. For example, planning for 100% of the observed effect gives 3,419 participants per arm for 80% power and 4,577 participants per arm for 90% power. Planning for 75% of the observed effect gives 6,090 and 8,152 participants per arm, respectively; planning for 50% gives 13,724 and 18,372.

Smaller effects are harder to distinguish from random variation, so detecting a smaller effect requires more participants under otherwise unchanged assumptions. These values are planning illustrations based on the observed result, not observed power for the completed trial. They also do not establish that a future study would achieve the stated power if its event rates, follow-up, allocation, or analysis differed from these assumptions.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.465; treatment proportion p₁ = 0.431; average p̄ = 0.448.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7033 = 1.3784.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7028 = 0.5915.
4. n = (1.3784 + 0.5915)² / (-0.0337)² = 3,418.9, rounded up to 3,419 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
p0 <- 0.464715107161526                          # control proportion
p1 <- 0.431025507548152                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(90259)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 3,419 (80% power), 4,577 (90% power)
 75% of observed effect: n per arm = 6,090 (80% power), 8,152 (90% power)
 50% of observed effect: n per arm = 13,724 (80% power), 18,372 (90% power)
power.prop.test: 3418.9 
Simulated power at n = 3,419 per arm: 0.799 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 the sponsor’s primary analysis as a Cox regression hazard ratio of 0.899, with a 95% confidence interval from 0.818 to 0.988 and p = 0.027. This is the reported time-to-event analysis and uses a different measure from the recalculated unadjusted risk difference. The registry’s estimate indicates a lower event hazard in the losartan 150 mg group under the reported model.

The recalculated comparison uses the posted participant counts and denominators. It gives a risk difference of -0.034, with a 95% confidence interval from -0.065 to -0.002 and an unadjusted p-value of 0.036. Its direction is consistent with the sponsor-reported hazard ratio: both estimates favor a lower primary-endpoint event measure in the higher-dose group. The estimates should not be expected to match numerically because one is an absolute comparison of participant proportions and the other is a time-to-event comparison.

The registry record marks no discrepancy between the posted results and the recalculation. The sponsor analysis remains the reported trial analysis; the recalculation is a transparent, unadjusted comparison based on the posted summary counts. The record does not provide sufficient detail to reproduce the Cox model or determine whether it included covariate adjustments.

15. Multiplicity, Missing Data and Analysis Populations

The registry record identifies an intention-to-treat population for the primary endpoint, but does not give further details about the analysis population rules. It does not report how participants with incomplete outcome follow-up were handled, whether missing data were imputed, or how withdrawals and treatment discontinuations were treated analytically. The record also does not describe censoring rules for the Cox analysis. These omissions limit assessment of whether missingness or loss to follow-up could have affected the estimates.

The record lists multiple secondary outcomes and analyses but does not report a multiplicity strategy. It does not state whether a formal hierarchy was used, whether p-values were adjusted, or whether secondary outcomes were considered confirmatory. General explanation: testing several outcomes can increase the likelihood of at least one result appearing statistically notable by chance. A prespecified strategy can help clarify which findings are intended to support confirmatory conclusions and how uncertainty across outcomes is handled. Without that information, nominal p-values for secondary outcomes should be interpreted cautiously.

The original protocol and statistical analysis plan details are not reported in the registry record. In particular, the record does not state the original sample-size justification, interim-analysis plan, stopping rules, covariate-adjustment plan, or whether any analyses were changed after study conduct began. These are unknown from the record and should not be inferred from the posted result fields.

The primary endpoint is explicitly labeled intention-to-treat, which indicates the recorded analysis population designation. It does not, by itself, provide all operational details needed to evaluate implementation. The registry record does not explain how participants were classified after protocol deviations, whether treatment assignment was retained in every case, or whether any sensitivity analyses assessed alternative population definitions. Those details matter when judging how closely an analysis reflects the randomized comparison.

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: pneumonia (4.6%), renal failure (2.2%), chronic obstructive pulmonary disease (1.5%), anaemia (1.2%), renal failure acute (1.1%).

The registry’s safety record lists serious adverse events for 691 participants in the losartan 50 mg group and 710 in the losartan 150 mg group. It lists other adverse events for 1358 participants and 1394 participants, respectively. These are posted participant counts; the registry record does not provide a safety analysis comparing the groups with confidence intervals or a stated hypothesis test.

The listed serious adverse-event terms include pneumonia at 4.6%, renal failure at 2.2%, chronic obstructive pulmonary disease at 1.5%, anaemia at 1.2%, acute renal failure at 1.1%, and osteoarthritis at 1.1%. These percentages are reported as registry values. The record does not specify in this summary whether these term percentages use all randomized participants, participants with serious adverse events, or another denominator, so they should not be used to calculate comparative risks.

These safety figures are descriptive and do not establish that one regimen caused more or fewer adverse events. The record does not report deaths in the safety fields, nor does it provide event timing, severity grading beyond the serious-event designation, or details of relatedness to treatment. Safety interpretation therefore requires caution and should be kept separate from the primary efficacy endpoint comparison.

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

The posted primary results show fewer participants with the composite of all-cause death or hospitalization for heart failure in the losartan 150 mg group than in the losartan 50 mg group. The recalculated risk difference and the sponsor-reported Cox hazard ratio both point toward a lower event measure with the higher-dose regimen, and their reported confidence intervals do not include their respective null values.

This does not establish that the higher dose is appropriate for every person, that it changes every component of the composite, or that the result applies to populations not represented by the study. The trial compared two losartan doses among people with symptomatic heart failure intolerant of ACE inhibitor treatment. It was not a comparison against no treatment, and the record does not provide evidence about every possible treatment alternative or clinical setting.

A statistically distinguishable group result is not the same as a guarantee of an individual outcome. General explanation: trial estimates describe average differences between groups, with uncertainty; individual responses and risks can vary. The primary endpoint also combines death and heart-failure hospitalization, so the overall result cannot be read as a separate estimate for each component.

The result does not by itself settle the balance between benefits and harms. Safety counts are available, but the registry record does not provide a complete comparative safety analysis, detailed adverse-event timing, or information about treatment adherence. It also does not report enough methods detail to fully assess missing data, censoring, or model assumptions. The strongest interpretation supported by the record is therefore a directional comparison of the posted primary outcome, with its reported uncertainty, in the trial population and follow-up.

18. Why This Trial Matters Statistically

This trial illustrates why the choice of statistical measure matters. A simple comparison of the proportion of participants experiencing the primary composite gives an absolute risk difference, while the reported Cox analysis uses time-to-event information and gives a hazard ratio. Both estimates point in the same direction, but each summarizes the data differently. Keeping the measures distinct prevents a hazard ratio from being misread as an absolute probability difference.

The endpoint also demonstrates the trade-off involved in composite outcomes. Combining all-cause death and hospitalization for heart failure creates a broad summary of clinically important events, but the composite alone cannot show how its components contributed. The separately posted secondary outcomes help provide context, while still requiring caution because multiple analyses are reported and no multiplicity strategy is described in the registry record.

The trial is also a useful example of reading precision alongside direction. The risk-difference and hazard-ratio intervals both lie on the side favoring the higher-dose group, but they reflect different statistical estimands and assumptions. A p-value alone would not communicate the range of plausible effect sizes or the scale of the comparison.

Finally, the contrast between a completed randomized study and the limited information in a registry record highlights the importance of reporting the statistical plan and implementation details. The record identifies the design, primary population, main endpoint, and sponsor analysis, but does not describe key elements such as missing-data handling, Cox-model diagnostics, or multiplicity control. These details determine how confidently readers can evaluate the analysis, not just the numerical result.

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 details specific to this trial are not reported in the registry record. The criteria defining symptomatic heart failure and intolerance of ACE inhibitor treatment are not given in the posted summary. Baseline clinical characteristics, the randomization procedure, allocation concealment, recruitment sites, and country distribution are also not described. Without those details, the representativeness of the enrolled population and the balance of prognostic factors cannot be assessed from this record alone.

The intervention description specifies dose titration, but adherence, dose interruptions, discontinuation, crossover, and concomitant treatments are not reported. The registry gives a median follow-up of 4.7 years and describes the study regimen as continuing up to 4 years, but does not explain the relationship between these follow-up descriptions or provide individual follow-up distributions. This limits assessment of exposure and observation time.

For the primary outcome, the record does not provide detailed event definitions, adjudication methods, component-specific contributions, or repeat-event analyses. It reports a Cox-model result but does not state covariate adjustments, censoring rules, or checks of model assumptions. Missing-data procedures, sensitivity analyses, and the original analysis plan are also not reported.

The safety record is descriptive and lacks comparative uncertainty estimates and detailed denominators for the listed serious adverse-event terms. The record does not report the multiplicity approach for the several secondary outcomes. These limitations do not negate the posted results, but they restrict how fully the analysis and its generalizability can be evaluated from the registry record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study to Evaluate Potential Decrease in Hospitalization Events, Time Between Events, and Increasing Longevity in Patients With Symptomatic Heart Failure (0954-948) — NCT00090259.
• Registry record last updated 2024-05-16; status last verified 2022-02.
• Results first posted 2010-08-02.
• 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

NCT00090259 is a completed Phase 3, randomized, double-blind, parallel-group study sponsored by Organon and Co. It compared losartan 50 mg daily with a regimen titrated to losartan 150 mg daily in people with symptomatic heart failure intolerant of ACE inhibitor treatment. The primary endpoint was the number of participants experiencing all-cause death or hospitalization for heart failure during entire follow-up, with a median of 4.7 years.

The posted primary counts were 889 of 1913 for losartan 50 mg and 828 of 1921 for losartan 150 mg. The recalculated unadjusted risk difference was -0.034, while the sponsor-reported Cox hazard ratio was 0.899. Both estimates point toward fewer primary-endpoint events in the higher-dose group, with reported intervals excluding their respective null values. The registry also lists secondary outcomes and descriptive safety counts, but does not report several analysis-plan, missing-data, multiplicity, and model-diagnostic details needed for a full methodological audit.