High Water Intake to Slow Progression of Polycystic Kidney Disease: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for High Water Intake to Slow Progression of Polycystic Kidney Disease (NCT00784030), a non-randomized na study. The primary outcome is Change in Urine cAMP Concentration and Urine Osmolality (UOsm).

2. Clinical Question

The study was motivated by the possibility that high water intake could affect processes associated with cyst growth in PKD. Its stated aim, however, was to examine changes in urine composition in people with PKD compared with healthy individuals. The primary outcome therefore concerns short-term urinary biomarkers, not kidney function, cyst growth, or disease progression over time.

The registry describes measurements before and after water loading, with the loading period lasting 2 hours. This makes the central question about a short-term response to water intake. The record does not report a numerical change for either group or a statistical comparison between groups. It is therefore not possible to establish from this record whether the biomarker measurements changed, how large any change was, or how precisely it was estimated.

3. Trial Design

This was a completed, nonrandomized, parallel-group study sponsored by NYU Langone Health. The registry lists an enrollment of 23 and identifies the study condition as autosomal dominant polycystic kidney disease. The study began in 2008-11, with primary completion in 2009-05. Its phase is listed as NA.

The registry distinguishes a group of patients with PKD from healthy controls. Because allocation was nonrandomized, the groups were not formed through random assignment. Differences between them may reflect characteristics other than PKD status; the record does not provide enough information to assess or adjust for such differences. The registry specifically flags that the arms are not a like-for-like control comparison. Masking is listed as none.

The intervention is water, and the primary outcome description specifies water loading with 2.5L over 2 hours. Urine cAMP concentration and urine osmolality were measured before and after loading. The parallel-group label describes the overall group structure, while the outcome description also specifies repeated measurements around the loading period. The record does not explain the detailed procedures or clarify all aspects of how the intervention was administered in each group.

The stated purpose was to examine urine-composition changes in people with PKD compared with healthy individuals. The primary endpoint is a continuous biomarker measure, reported as a mean with standard error. The record does not provide the numerical outcome estimates, a statistical analysis plan, or a sample-size justification. It says that participant numbers were deemed adequate for this pilot study, but gives no further rationale. The study is marked completed; the status alone does not supply its outcome findings.

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

Analysis population for the primary outcome, as defined in the registry: Number of participants was deemed to be adequate for the purposes of this pilot 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 Change in Urine cAMP Concentration and Urine Osmolality (UOsm), measured over pre- and post-water loading (2 hours).

The primary endpoint is described as change in urine cAMP concentration and urine osmolality (UOsm), with the unit expressed as fold change in cAMP/UOsm (umol/UOsm). Urine cAMP and UOsm were measured before and after water loading, which consisted of 2.5L over 2 hours. The registry specifies a mean as the summary measure and standard error as the dispersion measure.

These measures are urinary biomarkers: they characterize urine composition around the water-loading period. The registry’s stated rationale is to investigate urine-composition changes in people with PKD compared with healthy individuals. In general, a biomarker can offer information about a biological response or process, but it is not automatically a direct measure of a clinical outcome. In this study, the endpoint is not a measure of kidney failure, cyst growth, or long-term disease progression.

The short pre- and post-loading timeframe makes the endpoint relevant to an immediate response to water intake, rather than sustained effects. To interpret such a measure, readers would need the actual group estimates, the change from baseline, and an uncertainty estimate or other comparison. Numerical primary outcome results are not reported in the registry record, so the size and precision of any change cannot be assessed from the information recorded.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: urine cAMP concentration and urine osmolality are expressed through a fold change in cAMP/UOsm. A continuous outcome can take a range of values rather than representing only a category such as event or no event. The registry identifies the mean as the summary and the standard error as the measure of dispersion. These choices describe how the outcome was intended to be presented; they do not provide the missing estimates themselves.

What does a mean describe?

In general, a mean summarizes the central value of measurements in a group. It can be useful for comparing average biomarker values, but it does not show the full distribution of individual responses. Participants may have different values and different changes, even when the group mean is known. A mean is most informative when paired with a clear account of the population measured and a measure of uncertainty. The registry record does not report the primary means or changes.

What does standard error describe?

In general, the standard error describes the precision of an estimated quantity, such as a mean. It is not a description of the spread of individual measurements in the same way that a standard deviation is. A smaller standard error generally indicates a more precise estimate, while a larger one indicates more uncertainty about the estimate. The registry names standard error as the dispersion measure, but does not report its numerical value for the primary outcome.

Why is a confidence interval useful?

In general, a confidence interval presents a range of values that are compatible with the data and the statistical method used. It helps readers assess both the direction and precision of an estimate. A point estimate alone can conceal substantial uncertainty, and a confidence interval can make that uncertainty easier to interpret. No confidence interval for the primary endpoint is reported in the registry record. Without an estimate and its uncertainty, the strength of evidence for a change cannot be assessed.

How should the pre- and post-loading measurements be understood?

The outcome description identifies measurements before and after water loading. General analysis of repeated measurements may account for the fact that measurements from the same participant are related; they are not equivalent to measurements from unrelated people. The registry does not report the statistical method used to analyze the pre- and post-loading values, or whether the primary comparison focused on within-group change, a difference in change between groups, or another contrast. Those details are not reported in the registry record.

Why does nonrandomized allocation matter?

In general, random allocation helps balance measured and unmeasured characteristics between treatment groups, on average. With nonrandomized allocation, groups may differ in characteristics that also relate to the outcome. That makes a group contrast harder to interpret as an effect of the intervention alone. Here, the registry identifies a PKD group and healthy controls and explicitly notes that the arms are not a like-for-like control comparison. It does not report an adjustment strategy that would address potential group differences.

What is over-dispersion?

In general, over-dispersion means that observed variation is greater than a statistical model assumes. It matters because standard errors and confidence intervals can be too narrow if the model understates variability. This concept is especially relevant to some count or categorical outcomes. The primary endpoint in this record is continuous, and no model or evidence of over-dispersion is reported. It would not be appropriate to assume that over-dispersion was assessed or that a particular model was used.

What do the planning assumptions mean?

The registry includes planning illustrations described as calculations based on an observed effect, not as the trial’s own design. The stated assumptions are a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation; the effect to detect is described as a stated fraction of the observed effect. These are planning assumptions, not observed trial results or evidence of observed power. The record says the participant number was deemed adequate for the pilot study, but does not report a sample-size justification. The numerical outcome needed to interpret any illustration is not reported in the registry record, so the planning material should not be read as a finding from the study.

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("Polycystic Kidney Disease Patients", "Healthy Controls")
n   <- c(13, 10)
m   <- c(-2.6, -2)
sp  <- c(0.2, 0.1)
sd  <- sp * sqrt(n)      # standard errors converted to SDs
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  Polycystic Kidney Disease Patients  13  -2.600  0.721  -3.036  -2.164
CARM  Healthy Controls  10  -2.000  0.316  -2.226  -1.774

11. Multiplicity, Missing Data and Analysis Populations

The registry lists one outcome measure and zero analyses. It does not report a multiplicity plan, such as how statistical interpretation would account for testing multiple outcomes or contrasts. Although the primary outcome description includes urine cAMP concentration and urine osmolality, the record does not clarify the detailed analysis of each component or how they contribute to the stated fold-change measure. A correction for multiple testing should not be assumed.

Missing-data procedures are not reported in the registry record. The record does not state whether any measurements were missing, how missing measurements would be handled, or whether the analysis included all enrolled participants or a specified subset. The enrolled participant number alone does not answer these questions. Without a description of missingness and the analysis population, the completeness of the primary outcome data cannot be assessed.

The registry does not report an analysis plan, an analysis population, or whether the primary outcome was analyzed according to a prespecified method. It also does not provide numerical primary outcome results. These omissions limit assessment of how the endpoint was analyzed and whether the reported findings, if any, correspond to the stated primary question. No assumptions about interim analyses, protocol-defined populations, or methods for handling missing data can be made from the registry record.

12. 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 1% reporting threshold.

The registry reports serious adverse events for the PKD group with 13 participants at risk and zero affected, and for healthy controls with 10 participants at risk and zero affected. It also records zero other adverse events in each group. No serious adverse-event terms are listed. Death counts are not reported in the registry record.

These figures describe the adverse-event entries in the registry; they do not establish that no events of any kind occurred outside the reported categories or that all possible harms were assessed. The record does not provide event definitions, collection procedures, or further detail about the observation period for safety outcomes. The groups were nonrandomized, and the safety entries should not be interpreted as a controlled comparison of risk.

A zero affected count in a registry entry is not, by itself, proof that an intervention is free of risk. It should be read as the reported count for the specified category and group, alongside the limits of the available safety information. The record does not provide further safety analyses or numerical estimates of uncertainty.

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

This study addresses whether water loading is associated with short-term changes in urine cAMP concentration and urine osmolality in people with PKD, in comparison with healthy controls. The registry describes water loading with 2.5L over 2 hours and identifies the primary measure as a fold change in cAMP/UOsm. These details define the study question and endpoint, but numerical results are not reported in the registry record.

Consequently, the record does not show the direction or size of a biomarker change, whether the PKD and healthy groups differed, or how precisely any estimate was measured. It does not support a conclusion about whether water loading changed the primary endpoint. A completed study status is not itself an outcome result.

The endpoint is a short-term biomarker, not a direct measure of kidney failure, cyst growth, or long-term progression of PKD. In general, a biomarker can be biologically informative without establishing that a clinical outcome changes. The registry’s background discusses a hypothesis about water intake and abnormal cyst growth, but the listed primary endpoint concerns urine composition around a brief loading period. No long-term progression outcome is listed as the primary measure.

The nonrandomized design also limits causal interpretation. The registry notes that the arms are not a like-for-like control comparison. Differences in the measured outcomes could reflect group characteristics as well as the loading procedure, and the record does not report an adjustment method. The posted information is therefore best read as a description of a pilot study’s aim and design, rather than evidence of a treatment effect or a long-term clinical benefit.

14. Why This Trial Matters Statistically

Statistically, this study is notable for the distinction between a mechanistic question and a clinical outcome question. It examines urine biomarkers after a defined water-loading period. Such measurements can be relevant to understanding biological responses, but they do not automatically answer whether a disease progresses more slowly or whether a patient-important outcome changes.

The design also illustrates why the comparison structure matters. The registry identifies a PKD group and healthy controls, but allocation is nonrandomized and the record cautions that the arms are not a like-for-like comparison. A contrast between these groups cannot be interpreted as though randomization had made them comparable. Careful interpretation needs to consider possible baseline differences and the analysis used to address them; those details are not reported in the registry record.

Finally, a clearly specified endpoint is not enough to evaluate a finding. Readers also need numerical estimates and their uncertainty, along with information about the analysis population, missing data, and statistical methods. The registry names the primary biomarker measure and its summary approach but does not report the numerical results or analyses. This limits what can be learned statistically from the record, even though the study’s short-term question and pilot purpose are described.

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 principal limitation for interpreting this specific record is the absence of numerical results for the primary endpoint. The record describes measurements of urine cAMP concentration and urine osmolality before and after water loading, but does not report estimates, uncertainty, or a statistical comparison. The direction, magnitude, and precision of any change therefore cannot be assessed.

The registry identifies nonrandomized allocation and warns that the arms are not a like-for-like control comparison. It does not provide enough detail about group characteristics or statistical adjustment to assess comparability. Any observed contrast, if available elsewhere, would need to be interpreted with this design limitation in mind.

The outcome is measured around water loading over 2 hours. It does not directly assess long-term kidney function, cyst growth, or disease progression. The registry does not report follow-up for those outcomes. It also does not report detailed eligibility criteria, the administration procedures for each group, an analysis plan, missing-data handling, or the analysis population. The participant number is described as adequate for a pilot study, but a sample-size justification is not reported in the registry record.

Safety reporting is limited to the adverse-event entries recorded for the groups. The record does not give further event definitions, collection details, or a numerical death count. These limitations mean the registry supports a narrow description of the study’s design and measured outcome, but not a full assessment of efficacy, precision, or safety.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: High Water Intake to Slow Progression of Polycystic Kidney Disease — NCT00784030.
• Registry record last updated 2016-04-06; status last verified 2016-03.
• Results first posted 2016-04-06.
• 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

NCT00784030, titled “High Water Intake to Slow Progression of Polycystic Kidney Disease,” is a completed, nonrandomized, parallel-group study sponsored by NYU Langone Health. It lists an enrollment of 23 and compares a PKD group with healthy controls. Masking is listed as none.

The intervention is water loading with 2.5L over 2 hours. The primary outcome is a fold change in urine cAMP/UOsm, based on pre- and post-loading measurements, summarized as a mean with standard error. The registry describes the study as a pilot and states that the participant number was deemed adequate for its purposes.

Numerical primary outcome results, analyses, and a statistical analysis plan are not reported in the registry record. The record cautions that the nonrandomized arms are not a like-for-like control comparison. Adverse-event entries list zero serious and zero other events affected in each group; death counts are not reported in the registry record.