Evaluation of CLP With and Without Spironolactone in Heart Failure Patients With Chronic Kidney Disease: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of CLP With and Without Spironolactone in Heart Failure Patients With Chronic Kidney Disease (NCT01598740), a randomized phase 1 study. The primary outcome is Change in Fecal Sodium Content.

2. Clinical Question

3. Trial Design

This was a phase 1, randomized, open-label crossover study of CLP with and without spironolactone in adults with heart failure. The registry record identifies heart failure with chronic kidney disease in its title and summary. Enrollment was 18, and the study status is completed. The recorded start was 2012-06 and primary completion was 2012-09.

In a crossover design, a participant may receive more than one treatment condition in a planned sequence, so comparisons can potentially use information from the same participant under different conditions. That feature can be statistically important because measurements from the same person are often related. The registry identifies the model as crossover, but does not report the treatment sequences, sequence allocation details, period structure, washout, or whether the posted analyses accounted for within-participant correlation and treatment-period effects. Those details should not be inferred from the design label alone.

The comparison reported for the primary endpoint is between CLP alone and CLP plus spironolactone. The outcome summaries list 16 participants for CLP alone and 18 for the combination condition. These outcome counts differ, and the registry record does not explain why. They should not be treated as proof that every participant contributed complete measurements under both conditions, nor do they explain which participants were included in the sponsor's analysis.

The primary outcome was change in fecal sodium content. A secondary outcome was change in fecal weight. The registry reports an ANCOVA analysis for each outcome, but does not report model details such as included covariates or how the crossover structure was handled. The design and analysis information therefore supports a basic description of the trial and its posted comparisons, but not a full reconstruction of the protocol or statistical model.

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: Each study period included a 5-day baseline period followed by a 7-day treatment period. The study periods were separated by a 7-day washout period.

Period 1

Period 2

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 in Fecal Sodium Content, measured over baseline average (days 3-6 or days 22-25) and treatment average (days 10-13 or 29-32).

The primary endpoint is change in fecal sodium content, measured in mg. It is defined as the treatment average minus the baseline average. The stated baseline averages use days 3-6 or days 22-25, and the treatment averages use days 10-13 or days 29-32. The registry record does not explain the choice between the two day ranges beyond this definition, so the mapping of those time windows to treatment periods should not be assumed.

Using a change score expresses how the measured fecal sodium content differed between a baseline interval and a treatment interval. In general, baseline-adjusted or change-based measures can help describe within-person movement over time, rather than simply comparing measurements made at one point. In a crossover study, repeated measurements may also reflect period and sequence features, which makes the model used to analyze them important. The registry record does not provide enough detail to assess how those features were handled.

The outcome is a continuous measurement, and the posted summaries use means and standard deviations. These statistics describe the average change and the spread of individual measurements around that average. The endpoint is a study measurement; by itself, it does not directly describe symptoms, clinical events, or the overall experience of participants.

7. Results Posted in the Registry

• Treatment Group: CLP + Spironolactone: mean 501.95 versus 635.10 on control; difference -133.15 (95% CI -401.02 to 134.72), standardized effect d = -0.34; z-test p = 0.330.

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 in Fecal Weight

• 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 deviations.
• Result:
  • Treatment Group: CLP + Spironolactone: mean 119.00 versus 144.70 on control; difference -25.70 (95% CI -90.81 to 39.41), standardized effect d = -0.26; z-test p = 0.439.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment Group: CLP + Spironolactone and the control. The interval gives the range of effects that remain compatible with the data.

The registry posts one secondary endpoint, change in fecal weight. Its group-level direction is consistent with the primary endpoint in that the average change is lower in the combination condition than in the CLP-alone condition. This directional consistency is a descriptive feature of the posted results, not independent confirmation of the primary finding. Both endpoints come from the same small crossover study and may reflect related aspects of the same treatment periods.

The secondary analysis also has an ANCOVA p-value reported by the sponsor, but the registry does not provide the model estimate or interval for that analysis. The unadjusted summary comparison has considerable uncertainty. As with the primary result, these data do not establish the size or direction of a population effect with precision. The single posted secondary outcome does not permit a broader assessment of consistency across a set of different secondary measures.

Secondary results generally carry less weight than a prespecified primary result because they may be exploratory and may be interpreted alongside multiple outcomes or analyses. If many outcomes are examined, the chance of at least one apparently notable result can increase unless the analysis accounts for that multiplicity. Whether the sponsor adjusted for multiple testing, and whether this endpoint was designated as confirmatory or exploratory in the protocol, are not reported in the registry record.

The secondary outcome can add context about what was measured, but it should not be treated as a separate decisive test or as evidence that resolves the uncertainty in the primary comparison. Its interpretation depends on the same limitations around crossover modeling, missing-data handling, and incomplete reporting of the analysis plan.

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

• Change in Fecal Weight

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean describe?

A mean is the arithmetic average of the measurements in a group. For a continuous endpoint such as change in fecal sodium content, it gives a compact description of the central level of the observed measurements. A mean can be affected by unusually high or low observations, so it should be read together with a measure of spread and with the number of participants contributing measurements.

The standard deviation describes how dispersed the individual measurements are around the mean. A larger standard deviation indicates greater variation among the observations. It is not the same as the uncertainty of the mean: uncertainty in a mean comparison also depends on the number of observations, the analysis structure, and, for a crossover trial, how measurements from the same participant are related.

What does the mean difference represent?

The posted primary mean difference is -133.2 mg, calculated as the mean for CLP plus spironolactone minus the mean for CLP alone. A negative value in this coding means that the observed average change was lower in the combination group. The sign depends on the order of subtraction; it is not, by itself, a judgment about whether a difference is desirable or clinically important.

The recalculated comparison is an unadjusted contrast of the posted summary means. It does not incorporate covariates or participant-level pairing. This distinction matters because the registry identifies a randomized crossover design and reports a sponsor ANCOVA analysis. A crossover analysis may account for repeated measures, treatment period, or other model terms, but the specific terms used by the sponsor are not reported in the registry record.

How should the confidence interval be understood?

A confidence interval conveys the uncertainty around an estimate under the assumptions of the method used to construct it. In repeated use of the same procedure under its statistical assumptions, intervals constructed in this way have a specified long-run coverage property. It is not a range that guarantees the true value lies within it, nor does a 95% interval mean there is a 95% probability that the particular interval contains the true treatment effect.

For the unadjusted primary comparison, the 95% confidence interval runs from -401.0 to 134.7 mg. It includes zero, which corresponds to no difference under the contrast's subtraction convention. The interval also includes values on either side of zero. Its width indicates that the posted summary leaves substantial uncertainty about the magnitude and direction of the underlying average difference.

What does the p-value tell us?

The unadjusted p-value for the primary comparison is 0.33. A p-value is calculated under a null hypothesis and a statistical model; it describes how compatible the observed data are with that null model. It is not the probability that the null hypothesis is true, and it is not a measure of the clinical importance of the estimated difference. It should be considered with the estimate, confidence interval, design, and analysis assumptions.

The sponsor's reported analysis is ANCOVA and has a p-value of 0.066. ANCOVA, in general, compares outcomes while accounting for one or more covariates in a model. The term alone does not reveal which covariates were included, how baseline values were entered, or how correlation from the crossover structure was handled. Those details are not reported in the registry record, and the sponsor's estimate and confidence interval are not posted in the analysis entry.

Why does crossover structure matter?

In a crossover trial, measurements from the same person under different treatment conditions may be correlated. A method that accounts for this correlation can differ from a comparison that treats group summaries as independent. The unadjusted recalculation uses the posted means and standard deviations and does not reconstruct a participant-level crossover analysis. It is useful as a transparent descriptive comparison, but it should not replace the sponsor's analysis of the trial design.

Other possible design considerations include treatment sequence and period effects. For example, measurements can vary over time independently of treatment, or the order in which conditions are received can matter. These are general issues in crossover analysis; whether they arose or how they were addressed in this study is not reported in the registry record. No protocol details, model specification, or participant-level data are available in the posted information to assess them directly.

What can and cannot be inferred from the posted analyses?

The two reported approaches give different p-values because they are not the same calculation. The recalculation is based on unadjusted summary statistics, while the registry reports an ANCOVA result from the sponsor. Neither p-value gives the estimated treatment effect on its own. For the sponsor analysis, the absence of an estimate and interval limits assessment of effect size and precision. For the recalculation, the absence of individual-level data limits assessment of the crossover relationship and any adjustments.

Statistical methods do not remove limitations in the data or reporting. The registry does not report the missing-data approach, analysis population definitions, covariates, or multiplicity strategy. These omissions prevent a complete evaluation of the assumptions behind the reported analyses. The results should consequently be read as a limited record of group summaries and a reported model-based p-value, rather than a complete statistical analysis report.

11. Confidence Intervals and Precision

The primary unadjusted difference is -133.2 mg, with a 95% confidence interval from -401.0 to 134.7 mg. The interval includes zero and extends to values in both directions. This means the posted summary is not precise enough to confine the plausible average difference to one direction. It also leaves uncertainty about whether any difference is small or larger in magnitude.

Precision is distinct from the point estimate. The point estimate gives one best summary under the unadjusted calculation, while the interval communicates uncertainty around that estimate. A wide interval can arise when measurements vary considerably, when the available sample is limited, or when the analysis does not use potentially informative features of the design. The observed standard deviations are 441.1 mg for CLP alone and 342.5 mg for CLP plus spironolactone, indicating appreciable variation in the posted group measurements. These summaries do not by themselves reveal the variability of within-participant differences in the crossover.

The interval applies to the unadjusted recalculation, not to the sponsor's ANCOVA result. The registry gives a sponsor p-value of 0.066 but does not report that analysis's effect estimate or confidence interval. It is therefore not possible to assess the sponsor model's interval precision or compare the two intervals directly.

Confidence intervals reflect statistical uncertainty under the analysis assumptions; they do not capture every source of uncertainty. Incomplete reporting about missing data, analysis populations, crossover periods, and model specification leaves additional uncertainty about how well the posted analyses represent the intended comparison. The interval should not be interpreted as resolving those design and reporting questions.

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 events. They are illustrations based on the observed effect, with the target effect set in turn to 100%, 75%, or 50% of that observed effect. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. These assumptions describe the illustration, not the original trial's design justification, which is not reported in the registry record.

The 80% power column gives the number of participants per arm that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect under its assumptions. The 90% power column gives the corresponding per-arm planning number for a higher chance of detection, again under those assumptions. These are planning targets, not observed findings about the trial.

As the target effect is made smaller, more participants are needed to distinguish it from random variation under the same planning assumptions. The displayed estimates therefore rise when planning for a smaller fraction of the observed effect. The normal approximation and equal allocation are simplifications; the calculations do not reproduce the reported ANCOVA or fully model the crossover design. The registry record does not report the original protocol's sample-size rationale or its assumptions. These figures are planning illustrations and are not observed power.

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 = -133.150; pooled standard deviation σ = 391.835.
2. n = 2 × (1.96 + 0.842)² × 391.835² / -133.150² = 135.9, rounded up to 136 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 <- -133.15                      # observed difference in means
sigma <- 391.835011448537                     # 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(1598740)
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 = 136 (80% power), 182 (90% power)
 75% of observed effect: n per arm = 242 (80% power), 324 (90% power)
 50% of observed effect: n per arm = 544 (80% power), 728 (90% power)
power.t.test: 136.9 
Simulated power at n = 136 per arm: 0.797 (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 registry reports that the sponsor analyzed the primary comparison using ANCOVA and gives a p-value of 0.066. It does not report the sponsor's estimated contrast, confidence interval, model covariates, or enough detail to reproduce that analysis. The p-value should therefore be described as the sponsor's reported model-based result, without attributing an unreported effect size or adjustment strategy to it.

The recalculated comparison is different in scope. It uses the posted group means and standard deviations to estimate an unadjusted mean difference and its uncertainty. It does not account for the participant-level pairing that may be relevant in a crossover study, and it does not incorporate the sponsor's model terms. Its p-value of 0.33 is consequently not a correction or replacement for the ANCOVA p-value.

The discrepancy flag is false, but that does not make the methods identical. The two analyses can yield different numerical results because they use different information and assumptions. For interpretation of the trial's own analysis, the sponsor's ANCOVA is the registry-reported analysis; the recalculation is a supplementary, transparent summary comparison. The absent ANCOVA estimate and confidence interval mean that the sponsor result cannot be compared with the recalculation in terms of effect magnitude or precision.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary endpoint and a secondary endpoint, but does not report a multiplicity strategy. Multiplicity refers to the statistical issue that can arise when several outcomes, comparisons, or analyses are tested. Without an appropriate plan, the chance of obtaining at least one seemingly notable result can increase as the number of tests grows. The record does not state whether any correction was used, whether outcomes were ranked in a testing hierarchy, or whether secondary outcomes were intended as exploratory.

The registry reports an ANCOVA p-value for each posted endpoint, but does not provide full model specifications. It is not reported in the registry record which covariates were included, how baseline measures were handled, whether treatment period or sequence was modeled, or whether within-participant correlation was incorporated. These details are particularly relevant to a crossover design. They cannot be inferred solely from the term ANCOVA or from the design label.

The record does not report how missing outcome data were handled, whether any imputation was performed, or what rules determined inclusion in each analysis. The reported primary summaries include 16 participants for CLP alone and 18 for CLP plus spironolactone, while total enrollment was 18. The reason for the different outcome counts is not reported in the registry record. The counts do not establish the analysis population for the ANCOVA, nor do they reveal whether incomplete observations, exclusions, or another reporting convention explain the difference.

Definitions of intention-to-treat, per-protocol, or other analysis populations are not reported. Nor does the record describe sensitivity analyses for missingness or departures from the planned analysis. These omissions limit assessment of whether the posted results are robust to alternative assumptions. They do not demonstrate that any particular analysis decision was made; they identify information unavailable in the registry entry.

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 non-serious adverse event terms

The registry reports zero serious adverse events in each treatment group: 0 among 16 at risk with CLP alone and 0 among 18 at risk with CLP plus spironolactone. It also reports other adverse events affecting 5 of 16 participants in the CLP-alone group and 8 of 18 in the combination group. The record lists no top serious adverse-event terms.

These counts describe what was posted for the study and should not be read as proof that serious events could not occur. With a small study, absence of a recorded serious event does not provide a precise estimate of risk. The registry does not give event definitions, severity categories for the other adverse events, event-level descriptions, attribution to treatment, or timing. It is therefore not possible to interpret the other-event counts as treatment-caused events or to compare types of events.

Deaths are not reported in the registry record. The available adverse-event entry is limited and does not support a broad safety conclusion. The counts should be understood as descriptive registry data, not as a comprehensive account of safety in a larger population.

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

The results describe measurements of fecal sodium content and fecal weight in a completed, phase 1, randomized, open-label crossover study. For the primary endpoint, the unadjusted group summaries yield a negative mean difference for CLP plus spironolactone relative to CLP alone, but the 95% confidence interval includes zero and spans values in both directions. The sponsor's reported ANCOVA p-value is 0.066, while the unadjusted recalculation has a p-value of 0.33. The registry does not provide enough ANCOVA detail to determine why the results differ or to compare their estimated effects.

These findings do not establish that the treatment conditions are equivalent. A non-conclusive statistical result is not evidence that there is no difference; uncertainty may remain even when a particular analysis does not provide strong evidence against its null model. Conversely, the direction of the observed means does not establish that the combination produces a meaningful change. The registry does not provide a threshold for clinical importance, and the outcome is a fecal measurement rather than a reported clinical event or patient-centered outcome.

The results also do not show that either treatment improves or worsens health. No medical advice or treatment recommendation follows from the statistical summaries. The trial's enrollment, open-label status, crossover design, and incomplete reporting of analysis details all matter when interpreting what the estimates can say. In particular, the unadjusted recalculation does not recover participant-level pairing, and the sponsor's model cannot be fully evaluated from its posted p-value alone.

The posted results are best treated as limited evidence about these measured outcomes under the study conditions. They do not establish effects in populations beyond the participants studied, and the registry record does not give the detail needed to judge generalizability, the handling of missing data, or the full safety profile.

18. Why This Trial Matters Statistically

This study is statistically instructive because it combines a crossover design with continuous outcomes and a small enrollment. A crossover can offer within-participant comparisons, but valid analysis depends on the relationship between repeated measurements and on how treatment periods and sequences are represented. The registry identifies the design but does not report enough analytic detail to evaluate those features. This makes the distinction between sponsor ANCOVA and an unadjusted recalculation especially important.

The primary endpoint is reported as a mean change with standard deviations, a mean difference, a confidence interval, and an unadjusted p-value. Seeing these quantities together makes clear why a single p-value is not an adequate description of a result. The estimate gives a direction and scale, while the interval shows considerable uncertainty. The sponsor analysis adds a model-based p-value, but without its estimate and interval, its effect magnitude and precision remain unavailable.

The study also illustrates why planning calculations should be separated from the trial's original design rationale. The posted planning illustrations are based on fractions of the observed effect and specified generic assumptions. They do not reveal what the investigators planned before observing the data, and they are not observed power. The original sample-size justification is not reported in the registry record.

Finally, the difference between enrollment and endpoint counts, along with absent reporting about missing data and multiplicity, shows how registry summaries can leave important questions unresolved. Recognizing those boundaries is part of sound statistical interpretation: readers can describe the posted evidence without treating missing methodological details as known.

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 main trial-specific limitation is the limited enrollment of 18 participants, alongside outcome summaries of 16 participants for CLP alone and 18 for CLP plus spironolactone. The registry does not explain the differing counts. The reported group standard deviations also indicate substantial variation in the measured outcomes, and the primary unadjusted confidence interval is broad. Together, these features constrain the precision of the available summary comparisons.

The trial is labeled crossover, but the registry does not describe treatment sequences, period structure, transition procedures, or washout. It does not explain whether the posted outcome summaries represent repeated measurements from the same participants or how the sponsor's ANCOVA accounted for that structure. The recalculation based on group summaries cannot incorporate within-person correlation or resolve period and sequence questions.

The study was open-label, and masking was not used. The registry does not describe whether outcome assessment was blinded or whether measurement procedures could have been affected by knowledge of treatment. This is a reporting limitation, not evidence that measurement was biased.

Other important details are also absent: eligibility criteria, dose and administration information, the expansion of CLP, analysis population definitions, missing-data procedures, covariates, and multiplicity handling. The registry reports no sponsor effect estimate or confidence interval for the ANCOVA. These gaps prevent a complete audit of the protocol and analysis and limit interpretation of the reported p-values.

Finally, the posted outcomes concern fecal measurements. The record does not provide a clinical-importance threshold or evidence about patient-centered outcomes. Results from this study should therefore be interpreted within the scope of the measurements and population described, rather than generalized beyond the registry information.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Evaluation of CLP With and Without Spironolactone in Heart Failure Patients With Chronic Kidney Disease — NCT01598740.
• Registry record last updated 2013-07-19; status last verified 2013-07.
• Results first posted 2013-05-08.
• 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

NCT01598740 is a completed phase 1, randomized, open-label crossover study titled “Evaluation of CLP With and Without Spironolactone in Heart Failure Patients With Chronic Kidney Disease.” It enrolled 18 adults with heart failure, with chronic kidney disease specified in the registry title and summary. The recorded start was 2012-06 and primary completion was 2012-09.

The primary endpoint was change in fecal sodium content, and change in fecal weight was posted as a secondary endpoint. The registry reports sponsor ANCOVA p-values but does not provide model estimates or confidence intervals for those analyses. An unadjusted recalculation of the primary summaries gives a mean difference of -133.2 mg with a 95% confidence interval from -401.0 to 134.7 mg. Interpretation is limited by the small enrollment, incomplete crossover and analysis details, and missing-data and multiplicity information not reported in the registry record.