Electronic Patient-Reported Outcomes in Clinical Kidney Practice (ePRO Kidney): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Electronic Patient-Reported Outcomes in Clinical Kidney Practice (ePRO Kidney) (NCT03149328), a non-randomized na study. The primary outcome is Symptoms - Trajectory of Change.

2. Clinical Question

3. Trial Design

This completed, parallel-group study compared clinical programs using different approaches to patient-reported outcomes in home dialysis care. The Northern Alberta Renal Program was the intervention group: it used an electronic tool to collect patient-reported outcomes and return feedback in real time, and clinicians received educational support about routine use of those outcomes. The Southern Alberta Renal Program was the usual-care comparator; its clinicians did not receive the feedback or education sessions.

Allocation was nonrandomized and masking was none. The groups were therefore defined by program rather than by random assignment. The registry lists enrollment of 594. It records the study start as 2017-08-28, primary completion as 2019-10-31, and status as completed. Phase is listed as NA. The sponsor was the University of Alberta.

The primary outcome was symptoms/problems score trajectory over up to 24 months, from the start of enrollment to study completion. The primary outcome population is described as intent to treat, including all participants assigned to clinician support and education and those receiving usual care, and is based on an imputed dataset. The registry does not describe the allocation process in greater detail, the number of participants in each primary analysis group, or the statistical model used to compare trajectories. These details are not reported in the registry record.

Because the programs were not randomized, differences between them may reflect other distinctions between sites or patient groups in addition to the intervention. The registry record does not establish that the groups were otherwise comparable. The posted comparison should therefore be read as a nonrandomized program-level contrast, not as though allocation had been randomized.

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 were recruited and placed into their arm based on the clinic they were attending - there was no random assignment. 51 participants were clinicians (48) and family caregivers (3), these 2 participants groups were not part of the trial portion of the study.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Intent to treat population (all participants assigned to Clinician Support and Education as well as Usual Care). Based on Imputed dataset.

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 Symptoms - Trajectory of Change, measured over Trajectories of up to 24 months from start of enrollment to study completion.

The primary endpoint is the trajectory of symptoms/problems scores measured with the symptoms/problems domain of the Kidney Disease Quality of Life 36-Item Short Form Survey (KDQOL-36). The domain contains 12 items. Each asks about a symptom or side effect of kidney disease over the past 4 weeks, with response values ranging from “Not Bothered at all = 100” to “Extremely Bothered = 0.” The stated minimum score is 0 and the maximum is 100; a higher score indicates better health.

A trajectory describes how scores change over time rather than focusing only on a single measurement. The registry specifies trajectories of up to 24 months, beginning at enrollment and continuing to study completion. It identifies the outcome parameter as a mean and the dispersion measure as a standard deviation. A mean can describe the average score in a group, while the standard deviation describes variation in individual scores around that mean.

Patient-reported symptoms are relevant to the study’s stated aim of incorporating patients’ perspectives into routine care. However, the registry record does not report the numerical score estimates, the between-group contrast, or its uncertainty. The trajectory’s direction and size therefore cannot be characterized from the registry information available.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry describes a mean outcome and a standard deviation. These are complementary summaries for a continuous measure such as the KDQOL-36 symptoms/problems score. The mean represents the average score in the analyzed group. The standard deviation describes how widely scores vary around that average. A standard deviation is not the uncertainty of the mean; uncertainty in an estimated mean or group contrast is usually described with a standard error or confidence interval, neither of which is reported for the primary outcome in the registry record.

What does a trajectory analysis address?

General statistical explanation: repeated measurements can be used to study whether an outcome changes over time and whether its pattern differs between groups. Such analyses need to account for the fact that observations from the same participant are related, rather than independent. The choice of model also affects how time is represented and what group contrast is estimated. The registry calls the outcome a trajectory of change over up to 24 months, but the analysis model, measurement schedule, and time-specific estimates are not reported in the registry record. It would be inappropriate to infer a particular repeated-measures method from the word “trajectory.”

How should a group difference be read?

General statistical explanation: a between-group estimate expresses the size and direction of the contrast on the outcome scale. Its confidence interval communicates the precision of that estimate, subject to the model and its assumptions. A p-value addresses compatibility between the observed data and a specified null hypothesis under a statistical model; it does not describe the size of an effect or the probability that a hypothesis is true. The registry record does not report a numerical primary contrast, confidence interval, or p-value, so these interpretations cannot be applied to a specific result.

Why does nonrandomized allocation matter?

Random allocation is one way to balance both measured and unmeasured characteristics across groups, on average. Here, the intervention and comparator correspond to different Alberta programs, and allocation is identified as nonrandomized. General statistical explanation: when groups are formed through existing sites or programs, baseline differences and contextual factors may be associated with both group membership and outcome. Adjustment for measured covariates can address some differences, but does not automatically remove unmeasured confounding. The registry does not report the covariates, adjustment strategy, or analysis model, so the degree to which confounding was addressed is not reported in the registry record.

What does imputation mean for this outcome?

The primary outcome population is described as based on an imputed dataset. General statistical explanation: imputation is a way to handle missing values by replacing or estimating them under an explicit procedure, so that incomplete observations can contribute to an analysis. The validity of the resulting estimate depends on the method and its assumptions about why data are missing and how missing values relate to observed information. Different methods can lead to different uncertainty estimates. The registry record does not report the imputation procedure, assumptions, number of imputed datasets, or sensitivity analyses. The statement that the analysis used an imputed dataset is therefore not enough to evaluate the effect of missing data on the result.

What do the sample-size illustrations represent?

The stated sample-size assumptions describe planning illustrations based on the observed effect, not the trial’s own design. They use a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation, with the effect to detect specified as a proportion of the observed effect. The illustrations are participants per arm for 80% power for non-time-to-event outcomes; time-to-event illustrations instead use the total number of events. Such calculations are prospective planning aids under assumptions. They are not observed power, do not establish that the trial was adequately powered, and do not replace the missing outcome estimate and its uncertainty. The registry record does not report the trial’s own sample-size justification.

General statistical explanation: over-dispersion occurs when the observed variability is greater than a model expects. When present, a model that assumes too little variability can understate uncertainty and make evidence appear more precise than it is. The primary endpoint is described with a mean and standard deviation, but no model or variance assessment is reported, and the registry does not report that over-dispersion was evaluated. There is therefore no basis for claiming that it occurred or that a particular correction was used.

10. Confidence Intervals for Each Arm

No two-arm comparison is shown for this trial, but each arm's mean can be given with a t-based 95% confidence interval computed from the posted mean, spread and number of participants.

R code and output

arm <- c("Clinician Support and Education Around Use of PROs", "Usual Care")
n   <- c(284, 259)
m   <- c(77.2, 76.2)
sp  <- c(14.2, 15.1)
sd  <- sp      # posted standard deviations
for (i in seq_along(n)) {
  se <- sd[i] / sqrt(n[i]); h <- qt(0.975, n[i] - 1) * se
  cat(sprintf("CARM|%s|%d|%.3f|%.3f|%.3f|%.3f\n", arm[i], n[i], m[i], sd[i], m[i] - h, m[i] + h))
}

CARM  Clinician Support and Education Around Use of PROs  284  77.200  14.200  75.541  78.859
CARM  Usual Care  259  76.200  15.100  74.352  78.048

11. Multiplicity, Missing Data and Analysis Populations

The registry lists six outcome measures and seven analyses. It names secondary outcomes that include health-service utilization, satisfaction with care, and trajectories for mental health and quality of life. When several outcomes or analyses are considered, the chance of obtaining at least one apparently notable result can increase if each is assessed separately. General statistical explanation: prespecified outcome hierarchies, adjustment procedures, or a clear distinction between primary and exploratory analyses can help readers interpret multiple tests. The registry record does not report a multiplicity adjustment, testing hierarchy, or detailed statistical analysis plan. It is not possible to determine how multiplicity was handled.

For the primary outcome, the record states that the intent-to-treat population includes all participants assigned to clinician support and education and those in usual care, and that analysis was based on an imputed dataset. It does not report the amount or pattern of missing data, reasons for missingness, imputation method, assumptions, or sensitivity analyses. The term “intent to treat” indicates the stated analysis population, but does not by itself specify how missing outcome values were treated.

The record does not provide the numerical primary or secondary outcome results, the model specifications, or the analysis populations for each outcome. These details are not reported in the registry record. Without them, multiplicity, missing-data assumptions, and the robustness of the analyses cannot be evaluated.

12. 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 0% reporting threshold.

The registry lists serious adverse events affecting 0 of 284 participants at risk in the clinician support and education group, and 0 of 259 participants at risk in usual care. It also lists 0 other adverse events affecting participants at risk in each group. These are counts recorded in the adverse-event summary; they do not, by themselves, establish that no event occurred outside the registry’s reporting definitions or observation procedures.

The registry separately lists 23 deaths in the clinician support and education group and 12 in usual care. These figures should be read as reported counts, not as evidence that the intervention caused or prevented deaths. The record does not provide timing, causes, attribution, follow-up denominators for deaths, or a comparative analysis of mortality. It also does not describe the criteria used to classify serious adverse events or the collection and reporting procedures. Those details are not reported in the registry record.

Safety counts from nonrandomized programs are especially limited as comparative evidence. The groups may differ in ways that affect the chance of an event being observed or reported. These figures describe what the registry records, but do not support a causal safety comparison.

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

The study addresses whether electronic patient-reported outcome feedback combined with clinician education can be incorporated into home dialysis practice, with symptoms and problems reported by patients as the primary outcome. The registry record provides the group descriptions, outcome definition, and broad study design. It does not report numerical outcome estimates for the primary endpoint. The posted information therefore cannot show the direction, size, or precision of any difference in symptom scores between programs.

Even if a numerical contrast were available, this design would require cautious interpretation. The Northern Alberta Renal Program received the intervention and the Southern Alberta Renal Program served as usual care; allocation was nonrandomized. Observed differences could reflect the intervention or other program-level and participant-level differences. The registry record does not report the adjustment strategy or enough analysis detail to judge how well such differences were addressed.

General statistical explanation: statistical uncertainty and causal uncertainty are distinct. A confidence interval can describe precision under an analysis model, but cannot by itself remove confounding caused by nonrandom allocation. Likewise, a p-value cannot establish that an intervention caused an observed difference. In this record, the numerical primary outcome analysis is not reported, so neither statistical precision nor an outcome association can be assessed.

The listed adverse-event counts are descriptive, and the death counts are not accompanied by causes, timing, attribution, or comparative analysis. They should not be interpreted as proving a safety effect. The study record also does not establish whether the electronic tool or educational support changed care processes or patient experience, because results for those questions are not reported in the registry record.

The evidence is therefore about the study’s design and intended measurement, rather than a demonstrated outcome effect. It does not establish that the intervention improves symptoms, fails to improve symptoms, or changes safety outcomes.

14. Why This Trial Matters Statistically

Patient-reported outcomes can capture symptoms and experiences that may not be fully represented by clinical measures alone. This study focuses on whether patient reports can be collected electronically, fed back in routine home dialysis practice, and used alongside clinician education. Its primary endpoint is a patient-reported symptoms/problems domain, making the outcome directly relevant to the stated focus on patients’ perspectives.

Statistically, the study also illustrates the importance of separating intervention evaluation from implementation context. The comparison is between two programs, not randomized groups. This makes the distinction between observed association and causal effect particularly important. Regional or program-level differences may accompany the intervention, so outcome interpretation depends on information about baseline characteristics, analysis adjustment, and uncertainty.

The outcome is described as a trajectory rather than a single endpoint at one time. Repeated measurements can characterize change, but the analysis must account for within-participant dependence and clarify what pattern or contrast is being estimated. The registry record does not report the model, time-specific estimates, or numerical results, leaving those important interpretive questions open.

The record’s description of an imputed primary analysis also highlights that missing-data handling is part of the statistical evidence, not a minor technical detail. Without the imputation method and missingness information, readers cannot assess the assumptions supporting the analysis. The trial’s subject is important for understanding how patient feedback might be integrated into care, while the registry record’s missing outcome estimates and methods limit what can be concluded statistically.

15. 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 limitation for interpreting the trial from the registry record is that numerical primary outcome results are not reported. There is no mean trajectory, between-group estimate, confidence interval, or p-value available for the symptoms/problems outcome. The size and precision of any observed difference cannot be evaluated.

The comparison is nonrandomized and program-based. The record does not establish baseline comparability between the Northern and Southern Alberta programs, and it does not report the variables included in any adjustment. Residual confounding and differences in program context therefore remain concerns. The registry record does not describe allocation in enough detail to determine how participants entered the two groups.

The analysis methods are also incompletely described. Although the outcome is a trajectory over up to 24 months and the primary analysis uses an imputed dataset, the measurement schedule, statistical model, imputation method, missingness pattern, and sensitivity analyses are not reported in the registry record. The multiplicity approach for the listed outcomes and analyses is also not reported.

The registry does not provide numerical findings for the secondary outcomes in the information. For safety, it lists adverse-event and death counts but does not report event timing, causes, attribution, ascertainment procedures, or a comparative analysis. These omissions limit interpretation of both effectiveness and safety. They do not show that a particular analysis or event was absent; they mean the relevant detail is not reported in the registry record.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Electronic Patient-Reported Outcomes in Clinical Kidney Practice (ePRO Kidney) — NCT03149328.
• Registry record last updated 2021-10-05; status last verified 2021-09.
• Results first posted 2021-03-05.
• 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.

19. Record Summary

Electronic Patient-Reported Outcomes in Clinical Kidney Practice (ePRO Kidney) is a completed, nonrandomized, parallel-group study sponsored by the University of Alberta. It enrolled 594 participants and compared electronic patient-reported outcome feedback plus clinician education in the Northern Alberta Renal Program with usual care in the Southern Alberta Renal Program. Masking is listed as none, and phase is listed as NA.

The primary outcome was the trajectory of the KDQOL-36 symptoms/problems score over up to 24 months. The domain includes 12 items, uses a score range of 0 to 100, and assigns higher scores to better health. The primary population is described as intent to treat and based on an imputed dataset. Numerical outcome results and detailed analysis methods are not reported in the registry record. The record lists 0 serious adverse events affecting participants in either group and deaths of 23 and 12, respectively; it does not provide a causal safety analysis.