Patient-Reported Outcome Measurement in Heart Failure Clinic: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Patient-Reported Outcome Measurement in Heart Failure Clinic (NCT04164004), a randomized na study. The primary outcome is Kansas City Cardiomyopathy Questionnaire-12 Score.

2. Clinical Question

The trial addresses whether making standardized, patient-reported heart failure health-status information routinely available during clinic care is associated with a difference in later reported health status. It also examines treatment rates and doses among secondary outcomes. The intervention is a measurement and information-sharing strategy: clinicians could see survey results, while continuing to manage participants according to standard treatment practice. It is not described as assigning a particular medication or other clinical treatment.

The planned primary comparison concerns the first KCCQ-12 score collected one year after randomization. The registry specifies collection at the first heart failure clinic visit at least one year after randomization or by telephone interview 15 months after randomization. It describes adjustment for baseline KCCQ-12 scores in both arms. The registry record does not report further details about the eligible population, such as additional entry criteria, so the result should be interpreted for the trial participants and setting rather than assumed to apply to a more narrowly defined group.

3. Trial Design

NCT04164004, titled “Patient-Reported Outcome Measurement in Heart Failure Clinic,” is recorded as a completed randomized, parallel-group trial with no masking. The registry lists an enrollment of 1249 and Stanford University as sponsor. The study began on 2021-08-30, and primary completion is recorded as 2023-10-10. Its phase is listed as not applicable.

Participants were assigned to routine KCCQ-12 collection or usual care. In the routine-collection arm, participants were to complete the questionnaire at each heart failure clinic visit beginning at the start of the trial, with results available to clinicians in the electronic health record. In usual care, the questionnaire was not completed in the electronic health record during clinic visits; the arm description says participants completed a baseline questionnaire that was unavailable to the treating clinician. The study summary describes delayed implementation for the usual-care arm, with collection starting one year later.

The primary outcome is the KCCQ-12 score collected at least one year after randomization, or through the specified telephone interview at 15 months. Secondary outcomes concern treatment percentages and median doses for selected heart failure medication classes, including analyses described for participants with reduced or preserved/mid-range ejection fraction. The registry lists 34 outcome measures and 32 posted secondary outcomes. It does not report a statistical analysis record for the primary result, and the original design assumptions, including any planned sample-size justification, are not reported in the registry record. The randomized structure supports a comparison between assigned study strategies, but the posted result alone does not establish which specific analysis procedures were used beyond what the outcome description states.

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.

Overall Study

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 Kansas City Cardiomyopathy Questionnaire-12 Score, measured over Collected at the first heart failure clinic visit at least one year post-randomization or via telephone interview 15 months post-randomization.

The primary endpoint is the KCCQ-12 score, a patient-reported measure of heart failure health status. The registry describes a comparison of the first score collected one year after randomization between the routine-collection and usual-care arms, with baseline scores intended to be accounted for in both arms. The collection timeframe allows for a clinic visit at least one year after randomization or a telephone interview 15 months after randomization.

The KCCQ-12 includes four domains: Physical Limitation, Symptom Frequency, Quality of Life, and Social Limitation, as well as a Summary Score. Domain scores are scaled from 0 to 100, and the overall score is the average of the domain scores. The registry describes 0 as the lowest reportable health status and 100 as the highest; higher values represent a better reported outcome. This kind of patient-reported endpoint captures participants’ accounts of their health status rather than relying only on clinical events or treatment records.

For this question, the endpoint is relevant because the intervention is routine collection and clinician access to patient-reported information. A score measured after implementation can describe health status in each randomized arm. It does not, by itself, explain which parts of the intervention or subsequent care might account for any difference. The registry record does not report further details about how the questionnaire’s component scores were handled in the posted primary comparison.

7. Results Posted in the Registry

• Routine Collection of Patient-Reported Health Status (KCCQ-12 Arm): mean 79.40 versus 79.70 on control; difference -0.30 (95% CI -3.07 to 2.47), standardized effect d = -0.01; z-test p = 0.832.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: each participant’s KCCQ-12 score is represented on a numerical scale. A mean summarizes the average score within an arm. The registry reports an arm mean of 79.4 in the routine-collection arm and 79.7 in usual care, alongside a standard error of 1.0 for each. The standard error describes the estimated precision of an arm mean, not the spread of individual participants’ scores. It should not be read as a standard deviation.

The posted comparison is a mean difference of -0.3. A difference is formed by comparing the arm means in the stated direction; a negative value corresponds to a lower displayed mean in the routine-collection arm than in usual care. The comparison includes an interval from -3.072 to 2.472 and an unadjusted p-value of 0.832. These comparison statistics are recalculated from the posted summary statistics. The record does not provide a statistical analysis entry describing the estimator or model behind an adjusted primary analysis.

General statistical explanation: A confidence interval conveys a range of values reasonably compatible with the observed data under the assumptions used to construct it. It is not a guarantee that the true effect lies in that range, and it is not a direct measure of the probability that one treatment strategy is better. When an interval crosses zero for a difference, the data are compatible with no difference as well as with differences in either direction. The width of the interval matters: a wide interval leaves more uncertainty about the magnitude than a narrow interval.

General statistical explanation: A p-value measures how unusual data at least as incompatible with a null hypothesis would be under that null hypothesis and the test’s assumptions. It is not the probability that the null hypothesis is true. Nor does a large p-value demonstrate that two arms are equivalent. Equivalence requires a question framed around an acceptable range of differences and an analysis designed to assess that range; such an approach is not reported in the registry record.

There is an important distinction between the endpoint description and the available comparison. The primary outcome description says scores will be adjusted for baseline KCCQ-12 in both arms. Adjustment can account for baseline differences in score when estimating a follow-up contrast. However, no analysis record is posted to specify whether the means and mean difference shown are adjusted, what model was used, or how baseline scores entered that model. The unadjusted comparison is therefore best described as the posted summary-statistic recalculation, not assumed to be the prespecified adjusted result.

The score scale has a defined interpretation: each domain ranges from 0 to 100, and the overall score is the average of the domain scores. Higher values indicate better reported health status. That scale context helps readers understand the units of the mean difference, but it does not determine whether a particular difference is clinically important. The registry record does not report a threshold for clinical importance or a decision rule for interpreting score changes.

General statistical explanation: Randomization is intended to make assignment groups comparable, on average, with respect to factors that could influence outcomes. In practice, interpretation still depends on the participants included in the analysis, follow-up completeness, outcome measurement, and the analysis method. A randomized design does not eliminate the need to report these details. The registry record does not report the primary analysis population, the amount or pattern of missing outcome data, or the method used to handle missingness.

The posted sample-size illustration is based on the observed effect rather than on the trial’s original design. It uses a two-sided significance level of 0.05, equal allocation, and a normal approximation, with the effect to detect expressed as a fraction of the observed effect. These are assumptions for an illustration, not evidence about the trial’s planned calculations. The original sample-size justification and its assumptions are not reported in the registry record.

General statistical explanation: Over-dispersion occurs when outcome variability is greater than a model assumes. If ignored, standard errors and tests can be misleading. This primary endpoint is continuous, and the posted summary gives standard errors, but the registry does not describe a count model or an over-dispersion assessment. Therefore, over-dispersion is not a reported issue for the primary comparison. The broader principle is useful for count outcomes: the model should reflect how variable the data are, rather than relying on a restrictive variance assumption without checking it.

The registry lists 34 outcome measures, including the primary KCCQ-12 score and treatment-related secondary measures. It also lists 32 posted secondary outcomes, while no analysis records are reported. The record does not describe multiplicity control, interim analyses, or the statistical plan used to select or prioritize reported analyses. These omissions limit what can be concluded about the intended analysis hierarchy and the interpretation of results across multiple outcomes.

10. Confidence Intervals and Precision

The unadjusted mean difference is -0.3, with an interval from -3.072 to 2.472. The interval spans zero, so it is compatible with a small difference favoring either arm as well as with no difference. Its width indicates that the posted estimate is not precise enough to isolate a narrow range around the observed mean difference. The registry does not state the confidence level for this interval, so it is described simply as the posted interval.

General statistical explanation: Precision concerns how narrowly an estimate is bounded by its uncertainty interval. More precise estimates typically have narrower intervals, while less precise estimates have wider ones. An interval should be considered together with the scale and the question being asked; its endpoints are not separate estimates of what happened, but boundaries for values compatible with the data and method under stated assumptions.

Both displayed arm means have a standard error of 1.0, but that does not replace the interval for the between-arm contrast. The precision of a difference depends on the uncertainty in the comparison, not just on reading one arm’s standard error in isolation. In addition, the posted arm counts are 528 and 513, while the overall enrollment is 1249. The registry record does not explain which participants contributed to the primary endpoint or why the counts differ from enrollment.

Because the comparison is not accompanied by an analysis record, the interval should not be assumed to reflect the baseline adjustment described in the endpoint plan. The displayed interval is a recalculation from posted summary statistics. Missing-data handling, any covariate adjustment, and any additional sources of uncertainty are not reported in the registry record. Those details could affect how readers judge the precision of an adjusted primary estimate.

11. 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 participant counts per arm, not total event counts. They are an illustration based on the observed effect and use the assumptions stated for the calculation: a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. These calculations are separate from the original trial design; the trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the approximate participants per arm for a design with an 80% chance of detecting the specified effect under the calculation assumptions, if that effect were the true effect. The 90% power column gives the corresponding planning count for a 90% chance. For the full observed effect, the illustration lists 90,805 participants per arm for 80% power and 121,562 participants per arm for 90% power. Planning for 75% of the observed effect requires 161,430 participants per arm for 80% power and 216,109 participants per arm for 90% power. Planning for 50% of the observed effect requires 363,218 participants per arm for 80% power and 486,245 participants per arm for 90% power.

The pattern reflects a general property of study planning: smaller effects are harder to distinguish from random variation, so detecting them at a chosen power generally requires more participants. These counts are not the number enrolled or analyzed in this trial. They are not observed power; they are hypothetical planning illustrations based on the observed effect and stated assumptions. The registry does not report whether its original trial planning used these assumptions or a different approach.

12. 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 = -0.300; pooled standard deviation σ = 22.817.
2. n = 2 × (1.96 + 0.842)² × 22.817² / -0.300² = 90,804.3, rounded up to 90,805 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 <- -0.299999999999997                      # observed difference in means
sigma <- 22.8168419635498                     # 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(4164004)
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 = 90,805 (80% power), 121,562 (90% power)
 75% of observed effect: n per arm = 161,430 (80% power), 216,109 (90% power)
 50% of observed effect: n per arm = 363,218 (80% power), 486,245 (90% power)
power.t.test: 90805.2 
Simulated power at n = 90,805 per arm: 0.798 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary KCCQ-12 score outcome and numerous secondary outcomes, including medication-use percentages and median doses for different heart failure medication classes and ejection-fraction groups. It also records 32 posted secondary outcomes. When a study examines multiple outcomes, the chance of obtaining at least one apparently unusual result can increase if each is interpreted separately without accounting for the number of comparisons.

General statistical explanation: Multiplicity refers to the challenges created by making many statistical comparisons. Some analysis plans address this by defining a hierarchy of outcomes or by adjusting the criteria used to interpret multiple tests. The registry record does not report a multiplicity adjustment, a testing hierarchy, or a prespecified strategy for handling multiple comparisons. It therefore cannot establish how secondary-outcome findings should be interpreted collectively.

The registry record does not report how missing follow-up KCCQ-12 scores were handled, whether imputation was used, or what assumptions were made about participants without a follow-up score. The posted arm counts are 528 and 513, but the record does not identify the analysis population or explain the relation between those counts and total enrollment. This matters because a result among participants with recorded scores may differ from one based on all randomized participants if follow-up is incomplete in a way related to health status or study arm.

The endpoint description says the primary scores will be adjusted for baseline KCCQ-12 in both arms. However, the registry does not post an analysis record detailing the model, covariates, or analytic population. It also does not report interim analyses, the handling of protocol deviations, or whether results were analyzed according to assigned arm. These items are not reported in the registry record; they should not be inferred from the randomized design alone.

These gaps do not invalidate the descriptive arm summaries, but they limit assessment of whether the posted comparison follows the planned adjusted analysis and how robust it is to missing data or multiple testing. A fuller statistical record would be needed to evaluate those aspects.

14. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

The registry reports 624 participants at risk for serious adverse events in each arm. It lists 0 participants affected by serious adverse events in the routine-collection arm and 0 in usual care. No serious adverse event terms are listed. These are the posted counts; they do not by themselves establish that no serious events occurred outside the recorded definitions or reporting period.

The record also lists 23 deaths in the routine-collection group and 21 in usual care. These are reported counts and should be read separately from the serious-adverse-event affected counts. The registry information does not explain how deaths relate to the serious-event categories, when they occurred, or whether they were considered related to the study intervention. No causal conclusion should be drawn from these figures alone.

Adverse-event counts need context, including definitions, observation time, ascertainment methods, and the population included in each safety summary. The registry record does not report additional details on those matters. The reported zero affected counts therefore describe the registry entries, rather than proving the absence of all possible harms or establishing a comparative safety difference between groups.

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

The posted primary summaries show mean KCCQ-12 scores of 79.4 in the routine-collection arm and 79.7 in usual care. The unadjusted mean difference is -0.3, and the interval from -3.072 to 2.472 includes zero. In descriptive terms, the two displayed averages are close, and the interval does not pinpoint a clear difference in one direction.

This result does not establish that the two strategies are equivalent. A non-significant test, including p = 0.832, does not prove that an effect is absent. The interval allows a range of possible differences, and the registry record does not report an equivalence margin or an analysis designed to demonstrate equivalence. Likewise, the result does not establish that routine assessment is ineffective, nor does it show that it improves health status. It describes the posted comparison and its uncertainty.

The intervention combines repeated patient reporting with making scores available to clinicians. The primary endpoint is a later patient-reported score, not a direct measure of whether clinicians reviewed the results, changed their decisions, or acted on them. The trial summary states that clinicians continued standard treatment practice. Secondary outcomes concern treatment rates and doses, but their numerical results are not reported in the registry record discussed for the primary comparison. No conclusion about changes in treatment decisions follows from the primary score alone.

The registry describes an intended adjustment for baseline KCCQ-12, but the posted comparison is a recalculation from summary statistics and is not accompanied by an analysis record confirming that adjustment. The arm counts also do not match the overall enrollment, and the registry record does not report the analysis population or missing-data procedures. Those limitations make it important to distinguish the displayed summaries from a fully documented adjusted analysis.

More broadly, the findings relate to this randomized study in heart failure clinic settings. The record does not report enough population detail to determine how results might vary across clinical settings or participant subgroups. The appropriate interpretation is therefore bounded: the available summary shows similar arm averages at the recorded follow-up, with uncertainty around the between-arm contrast, while important analysis and follow-up details remain unreported.

16. Why This Trial Matters Statistically

This trial raises a statistical question about an intervention that changes how information enters clinical care rather than assigning a drug or procedure. That distinction makes the measurement pathway important: routine questionnaire completion, clinician access to results, and subsequent care are parts of a sequence, while the primary endpoint is a later patient-reported score. Separating these stages helps avoid treating a score difference as direct evidence about clinician behavior or a particular treatment decision.

The endpoint also illustrates why the outcome scale and the estimand matter. KCCQ-12 scores measure reported health status, and higher scores represent better status. The registry describes a comparison at follow-up adjusted for baseline score, but the posted summary comparison does not come with an analysis record that clarifies whether the adjustment was implemented. A clear distinction between the planned adjusted question and the available unadjusted recalculation is essential for statistical interpretation.

The result is also a useful example of the difference between a p-value and precision. The p-value is 0.832, while the interval ranges from -3.072 to 2.472. Neither statistic alone settles whether a meaningful effect exists. The interval shows uncertainty in both directions, and the registry does not report a threshold for clinical importance or an equivalence margin. Thus, the interpretation should avoid turning a failure to distinguish a difference into a claim of sameness.

Finally, the posted planning illustration highlights how strongly planning counts can depend on the effect selected for detection. Smaller target effects correspond to larger participant requirements under the stated assumptions. Such illustrations are distinct from the trial’s original design rationale, which is not reported in the registry record. Keeping those planning calculations separate from observed results prevents the mistaken interpretation that a retrospective planning count is an observed power calculation or a description of the trial’s actual design.

17. 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 primary comparison is not accompanied by a statistical analysis record. Although the endpoint description says the scores will be adjusted for baseline KCCQ-12, the record does not clarify whether the posted means and contrast reflect that adjustment, nor does it identify the model or covariates. The reported unadjusted mean difference and interval are recalculated from posted summary statistics, so they should not be treated as a documented adjusted primary estimate.

The registry reports overall enrollment of 1249, while the arm summaries list 528 and 513 participants. The relationship between these counts is not explained. The primary analysis population, follow-up completion, missing-data amount, and missing-data handling are not reported in the registry record. Without these details, it is difficult to assess whether the comparison represents all randomized participants or a subset with available scores.

The study is unmasked, and the intervention makes questionnaire results available to clinicians. This is intrinsic to the study strategy, but it means the comparison is not blinded to assignment. The registry record does not describe procedures to assess or mitigate potential influences on questionnaire completion, outcome collection, or clinical behavior. It also does not report how treatment-related secondary outcomes were analyzed or whether multiplicity was addressed.

Other limitations of interpretation include the absence of a reported threshold for a clinically important score difference and the lack of detail about the analysis population and participant characteristics. The outcome description specifies a clinic or telephone collection timeframe, but the record does not report the distribution of collection modes or timing. These omissions do not change the numerical summaries, but they constrain conclusions about their precision, clinical meaning, and generalizability.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Patient-Reported Outcome Measurement in Heart Failure Clinic — NCT04164004.
• Registry record last updated 2026-04-08; status last verified 2026-03.
• Results first posted 2025-04-04.
• 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.

21. Record Summary

NCT04164004 is a completed randomized, parallel-group, unmasked trial sponsored by Stanford University. It enrolled 1249 participants and compared routine KCCQ-12 collection with usual care in a heart failure clinic setting.

The primary endpoint was the KCCQ-12 score collected at least one year after randomization or by telephone interview at 15 months. Posted mean scores were 79.4 for routine collection and 79.7 for usual care. The unadjusted mean difference was -0.3, with an interval from -3.072 to 2.472 and p = 0.832. The registry describes baseline adjustment but does not post a statistical analysis record confirming how the displayed comparison was analyzed.

Important details about the primary analysis population, missing data, multiplicity, and the original sample-size rationale are not reported in the registry record. The planning illustration uses the stated assumptions and is not observed power. The posted summaries therefore support a cautious description of similar average scores, while leaving uncertainty about the adjusted analysis and its interpretation.