Alkaline Water in Reducing Skin Toxicity in Women With Breast Cancer Undergoing Radiation Therapy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Alkaline Water in Reducing Skin Toxicity in Women With Breast Cancer Undergoing Radiation Therapy (NCT01487954), a randomized phase 2 study. The primary outcome is Acute and Grade 2 or Higher Radiation-related Skin Toxicity as Assessed by Common Terminology Criteria for Adverse Events (CTCAE) Version 3.0.

2. Clinical Question

The clinical question is whether the recorded frequency of radiation-related skin toxicity differed between the two water groups during radiation therapy and at the specified follow-up. Both groups received external beam radiation therapy; the water intervention was the contrast between arms. The primary outcome is a participant-level percentage, rather than a measure of how severe toxicity was on average or how long it lasted.

The registry identifies change in urine pH as a secondary outcome, but does not post a result for it. It also describes weekly toxicity summaries, as well as the primary assessment at 1 month after treatment. The detailed clinical question therefore centers on the recorded proportion with grade 2 or higher skin toxicity at that follow-up, not on a demonstrated effect on urine pH or on other unreported clinical outcomes.

3. Trial Design

This was a phase II, randomized, double-masked, parallel-group trial sponsored by Case Comprehensive Cancer Center. The registry lists an enrollment of 45 participants and a completed status. The listed trial start was May 2010, and primary completion was November 2012. The number of participants assigned to each arm was unequal: 29 in the alkaline-water arm and 16 in the distilled-water arm. The reason for the unequal arm sizes is not reported in the registry record.

Both groups underwent external beam radiation therapy once daily, 5 days a week for 6 weeks. Participants in the alkaline-water arm drank 8 ounces of alkaline water within 30 minutes immediately before and after each radiation treatment. Participants in the comparison arm followed the same schedule using 8 ounces of distilled water. Thus, the comparison was between two water regimens during radiation therapy, not between radiation therapy and no radiation therapy.

The primary outcome was the percentage of participants with acute radiation-related skin toxicity of grade 2 or higher at 1 month after treatment, assessed by CTCAE Version 3.0. The registry also describes frequency summaries of observed toxicity by severity and type during weekly radiation treatment and at 1 month after radiation treatment. Change in urine pH is listed as a secondary outcome, but a result for that outcome is not reported in the registry record.

The registry does not report the original sample-size justification, the intended allocation ratio, details of how masking was implemented, or the prespecified statistical analysis plan. It also does not report an analysis population definition or a participant flow accounting for exclusions and missing outcome data. Those omissions limit how fully the trial’s design and conduct can be reconstructed from the registry record.

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 Acute and Grade 2 or Higher Radiation-related Skin Toxicity as Assessed by Common Terminology Criteria for Adverse Events (CTCAE) Version 3.0, measured over at 1 month after treatment.

The primary endpoint is the percentage of participants with acute radiation-related skin toxicity of grade 2 or higher at 1 month after treatment. Toxicity was assessed using Common Terminology Criteria for Adverse Events, Version 3.0. A thresholded endpoint classifies participants according to whether they reached the specified grade; it does not describe the full distribution of toxicity grades or the duration of each event.

This kind of endpoint is used to express how commonly a defined event occurred in each group. It gives a direct participant-level summary of toxicity at a stated follow-up time and permits a comparison of the proportions in the two arms. The registry also describes collecting the type, severity, onset and resolution of toxicity, and its probable association with the study regimen. Those features can add clinical detail, but no corresponding detailed results are reported in the registry record.

The registry’s outcome description includes frequency summaries during weekly radiation treatment and at 1 month after radiation treatment. The primary result, however, is presented as the percentage at 1 month after treatment. No separate numerical results by week, toxicity type, or grade are reported in the registry record. Change in urine pH is listed as a secondary outcome, but its result is also not reported in the registry record.

General statistical context: a binary endpoint can be summarized with a proportion, while a difference between two proportions describes the absolute contrast between groups. Neither summary alone captures every aspect of toxicity, such as timing or duration. The registry’s stated endpoint is therefore best read as a comparison of participant proportions at the specified assessment, alongside recognition that other clinically relevant details are not available in the posted results.

7. Results Posted in the Registry

• Arm II: Distilled Water: 37.5% (6/16) versus 37.9% (11/29) on control; risk difference -0.4 percentage points (95% CI -30.0 to 29.1), risk ratio 0.99 (0.45–2.17); unadjusted two-proportion z-test p = 0.977.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a participant percentage describe?

The primary endpoint is binary at the participant level: a participant either met the grade 2 or higher toxicity definition at the assessment or did not. A percentage summarizes the fraction of participants with the event in an arm. The posted values are 38.0% in each arm. The registry also supplies event counts of 11 among 29 participants in the alkaline-water arm and 6 among 16 in the distilled-water arm. A rounded percentage is a compact description, while the count and arm size show the amount of information behind it.

General statistical explanation: the percentage is an estimate of an underlying event probability, not a guarantee that the same percentage would occur in another sample. With limited observations, a few participants can materially affect the estimate. That is why interpretation should consider uncertainty around each group’s proportion and, especially, uncertainty around the difference between the groups.

What is a risk difference?

A risk difference subtracts one group’s event proportion from the other’s. It expresses an absolute contrast on the probability scale. The registry reports a risk difference of -0.004. Given the comparison’s arm ordering, the estimate is consistent with a slightly lower observed proportion in the distilled-water arm, but the estimate is very close to no difference. This point estimate should not be treated as a precise description of the true contrast, because its confidence interval is broad and includes zero.

General statistical explanation: zero is the null value for a risk difference. A confidence interval that includes zero means that the data are compatible with no absolute difference, as well as with values on either side of zero within the interval. This does not prove the null hypothesis or show that the treatments are equivalent. A prespecified equivalence or non-inferiority framework would require its own margin and analysis, neither of which is reported in the registry record.

How should the p-value be read?

The posted unadjusted p-value is 0.977. General statistical explanation: a p-value summarizes how unusual data at least as discrepant as those observed would be under a specified null model and its assumptions. It is not the probability that the null hypothesis is true, nor is it a measure of the probability that a treatment is beneficial. A large p-value does not establish that groups are equal. In a small trial, a large p-value can coexist with substantial uncertainty because the data may not distinguish among a range of possible effects.

The registry labels this p-value unadjusted. The record does not report whether other analyses were planned, whether any adjustment was used for multiple testing, or how the primary comparison was selected from the described toxicity summaries. Accordingly, the p-value should be interpreted as the posted comparison rather than as evidence about an unreported broader analysis plan.

Why do confidence intervals matter?

A confidence interval gives a range of effect estimates compatible with the data under the method used to calculate it. General statistical explanation: intervals are useful because they display both the direction and the precision of an estimate. A narrow interval indicates more precision; a wide interval indicates less. For this trial, the risk-difference interval reaches across zero, so it encompasses no difference as well as contrasts in either direction. The relative-risk interval likewise includes its null value. These intervals convey more about uncertainty than the point estimates or p-value alone.

Confidence intervals do not account automatically for every source of uncertainty. Their interpretation depends on the analysis method and on assumptions such as how participants were selected, whether outcomes were observed as intended, and whether the model is appropriate. The registry record does not provide the full statistical analysis plan or missing-data details, so those assumptions cannot be assessed completely from the posted information.

What does randomization contribute?

Randomization is intended to make assigned groups comparable, on average, with respect to factors that could influence outcomes. That supports interpreting a between-group contrast as an effect of assignment when randomization is implemented and the analysis is appropriate. The registry identifies the trial as randomized and double-masked, but does not report the randomization procedure, allocation concealment, who was masked, or whether masking was maintained. These implementation details are not reported in the registry record.

The trial used a parallel-group structure: participants were assigned to one water arm and followed under that regimen alongside radiation therapy. The arm sizes were not equal. The registry does not explain whether that imbalance arose from the allocation plan, enrollment, or missing observations, and it does not give a participant-flow account. Randomization is an important design feature, but it does not by itself resolve uncertainty from a small sample or incomplete reporting.

What does the endpoint leave out?

The primary endpoint captures whether participants crossed a specified toxicity-grade threshold at 1 month after treatment. General statistical explanation: converting a graded outcome into a thresholded binary measure can make a result easier to summarize, but it loses information about differences within the categories and about outcomes at other times. The registry describes recording severity, type, onset and resolution, and probable association, and mentions weekly toxicity summaries. The corresponding detailed results are not reported in the registry record.

The secondary outcome, change in urine pH, is named but has no posted numerical result. The record does not report whether all secondary outcomes were measured for every participant, how missing measurements were handled, or whether the primary endpoint was assessed for all enrolled participants. Therefore, conclusions should stay close to the posted primary percentages and comparison rather than extending to unreported endpoints or analyses.

The analysis is a comparison of observed participant proportions, with the registry reporting a risk difference, a relative risk, an odds ratio, confidence intervals, and an unadjusted p-value. General statistical explanation: risk differences express absolute contrasts, whereas relative measures express contrasts as ratios. The measures answer related but distinct questions. When event frequencies are not extremely low, a ratio measure and an absolute difference may convey different impressions of the size of a contrast. Here, both types of interval include their respective null values, reinforcing that the posted data do not sharply distinguish the groups.

10. Confidence Intervals and Precision

The primary outcome percentages are 38.0% in both arms, but similar rounded point estimates do not mean the underlying event probabilities are known to be identical. The confidence intervals are important because they describe uncertainty in the estimates and in the contrast between arms. The reported risk-difference interval includes zero and extends in both directions; the relative-risk interval includes its null value. The registry therefore leaves considerable uncertainty about the size and direction of a possible difference.

The arm sizes were 29 participants with alkaline water and 16 with distilled water. These sample sizes constrain precision: fewer observations generally leave more uncertainty around proportions and their difference. The imbalance also means the two percentages are based on different amounts of information. In particular, the percentage in the smaller arm can be sensitive to the outcome status of individual participants. The reported comparison should be read together with its interval, rather than by comparing rounded percentages alone.

General statistical explanation: a confidence interval is not a guarantee that the true value lies inside the calculated range. It is a method-based range whose long-run coverage depends on the analysis procedure and assumptions. Nor does an interval that includes no difference establish equivalence. To support an equivalence claim, a study would need a defined margin and an analysis designed for that question; these are not reported in the registry record.

The registry does not report the original sample-size justification, the intended precision, or the study’s original assumptions for power. The planning estimates displayed for future sample sizes are separate illustrations based on the observed effect, not descriptions of the trial’s original design. Thus, the trial’s observed result is best characterized as a close point estimate with limited precision, not as a precise demonstration that the two arms have the same outcome frequency.

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 sample-size estimates are planning illustrations based on the observed effect, not the trial’s original design assumptions. They use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row considers detecting a stated fraction of the observed effect: 100%, 75%, or 50%. As the target effect becomes smaller, the required number of participants per arm increases.

The estimates are participants per arm, not total participants across both arms and not total events. For planning for 100% of the observed effect, the estimates are 198,478 participants per arm for 80% power and 265,705 participants per arm for 90% power. For planning for 75% of the observed effect, they are 353,048 participants per arm for 80% power and 472,631 participants per arm for 90% power. For planning for 50% of the observed effect, they are 794,804 participants per arm for 80% power and 1,064,017 participants per arm for 90% power.

In plain terms, the 80% power column gives the illustrated number per arm for a design with an 80% chance of detecting the specified effect under the stated assumptions; the 90% power column gives the number per arm for a 90% chance. Higher target power requires more participants for the same assumed effect. Smaller effects also require more participants because they are harder to distinguish from random variation.

These are not observed power. They are forward-looking planning calculations, and their size is driven by the very small observed contrast in this trial. They should not be read as a recommendation or as a reconstruction of the original sample-size plan, which is not reported in the registry record.

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

Worked calculation for this trial

1. Control proportion p₀ = 0.379; treatment proportion p₁ = 0.375; average p̄ = 0.377.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6854 = 1.3434.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6854 = 0.5769.
4. n = (1.3434 + 0.5769)² / (-0.0043)² = 198,477.4, rounded up to 198,478 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.379310344827586                          # control proportion
p1 <- 0.375                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1487954)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 198,478 (80% power), 265,705 (90% power)
 75% of observed effect: n per arm = 353,048 (80% power), 472,631 (90% power)
 50% of observed effect: n per arm = 794,804 (80% power), 1,064,017 (90% power)
power.prop.test: 198477.4 
Simulated power at n = 198,478 per arm: 0.799 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Multiplicity, Missing Data and Analysis Populations

The registry describes more than one type and time point of toxicity information: weekly assessments during radiation treatment and an assessment at 1 month after treatment. It names a primary endpoint at the 1-month assessment and lists change in urine pH as a secondary outcome. However, the registry does not report a full statistical analysis plan explaining how these outcomes and assessments were prioritized or analyzed.

Multiplicity arises when multiple outcomes, time points, grades, or comparisons are tested. General statistical explanation: testing many hypotheses can increase the chance that at least one result appears notable by chance. Analysts may address this through a prespecified hierarchy or an adjustment, but the registry record does not report whether any such approach was planned or used. The posted p-value is identified as unadjusted, and no adjustment procedure is described. The result should therefore be read as the unadjusted comparison reported for the primary outcome, without assuming it accounts for other possible tests.

Missing-data handling and the analysis population are also not reported in the registry record. The record gives the arm sizes for the reported outcome and event counts, but does not describe participant flow, exclusions, withdrawals, or whether every randomized participant contributed an observed primary outcome. It does not specify whether the analysis followed an intention-to-treat principle or another population definition.

General statistical explanation: missing outcome data can affect both the precision and interpretation of a group comparison, particularly if the chance of missingness differs between groups or relates to outcome status. Without information about completeness and handling, readers cannot assess whether the posted percentages represent all randomized participants or a subset. This is a reporting limitation, not evidence that data were missing.

The registry also does not report interim analyses, stopping rules, or the original sample-size justification. These are not inferable from the completed status or from the planning illustration. The posted result can be described as recorded, but the analysis decisions beyond those explicitly stated remain unclear.

14. Safety Results

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

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: skin infection (6.2%), alanine aminotransferase increased (3.4%), aspartate aminotransferase increased (3.4%), chest wall pain (3.4%).

The adverse-event summary lists one participant with a serious adverse event in each arm: one of 29 in the alkaline-water arm and one of 16 in the distilled-water arm. Other adverse events are listed for 26 of 29 participants in the alkaline-water arm and 13 of 16 participants in the distilled-water arm. These are separate registry categories; the record does not explain overlap between serious and other events or provide a detailed event-by-participant account.

The registry lists skin infection at 6.2%, alanine aminotransferase increased at 3.4%, aspartate aminotransferase increased at 3.4%, and chest wall pain at 3.4% among the top serious adverse-event terms. These listed percentages are not presented with arm-specific counts in the posted record, so they should not be used to compare arms or infer which regimen was associated with a term. Death counts are not reported in the registry record.

General statistical explanation: adverse-event counts describe events recorded during the trial; by themselves, they do not establish that an event was caused by a study intervention. Small groups also make comparative safety estimates imprecise. The registry summaries are descriptive and do not report a formal comparative analysis of adverse events. They should be read as safety reporting for the enrolled participants, not as proof of causation or as a complete profile of risks outside this trial.

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

The results describe the frequency of acute grade 2 or higher radiation-related skin toxicity recorded at 1 month after treatment in this phase II trial. The posted percentage was 38.0% in each arm. The reported risk difference is close to zero, and the unadjusted p-value is 0.977. These observations do not show a clear separation in the primary outcome between the alkaline-water and distilled-water groups in this sample.

That does not establish that the groups are equivalent. The trial included 29 participants in one arm and 16 in the other, and the confidence intervals leave room for differences in either direction. A failure to identify a statistically persuasive difference is not the same as demonstrating no difference. Nor can the result establish what would happen in a larger or different population.

The endpoint is limited to a particular toxicity threshold and assessment time. It does not summarize all toxicity grades, the full course of symptoms, or each weekly assessment. Although the registry describes collecting information about onset, resolution, severity and type, detailed results for those features are not reported in the registry record. A secondary outcome, change in urine pH, is listed without a posted result.

The trial compares two water regimens while participants received the same described radiation therapy schedule. It therefore cannot be interpreted as a comparison of radiation therapy with no radiation therapy. The registry’s safety summaries record adverse events but do not establish that they were caused by the water regimen, and they do not provide a formal comparative safety analysis.

In short, the posted primary data are compatible with little difference, but their precision is limited. The result is a description of what was recorded in this trial, not a general conclusion about efficacy, an equivalence finding, or a basis for medical advice.

16. Why This Trial Matters Statistically

This trial is statistically instructive because the two posted primary percentages are both 38.0%, yet the interpretation still depends on sample size and uncertainty. Matching rounded percentages can look decisive at first glance, but the arms contain 29 and 16 participants, and the intervals for the comparative estimates include their null values. The example shows why a point estimate should be read alongside its uncertainty rather than treated as a complete answer.

The endpoint also illustrates a common trade-off in clinical research. Defining an event as grade 2 or higher makes the outcome easy to express as a participant percentage, while compressing information about other grades, timing, and duration. The registry describes collecting richer toxicity details and weekly summaries, but does not report those results. A carefully defined primary endpoint helps focus a comparison, while unavailable secondary detail limits how broadly that comparison can be interpreted.

The planning illustration highlights a different statistical issue: when the observed contrast is very small, planning to detect a fraction of that contrast can imply very large sample sizes. Those figures are not the trial’s original design assumptions and are not observed power. They make clear that effect size, target power, and sample size are linked, and that a trial with few participants may leave substantial uncertainty even when its point estimates are similar.

Finally, the record demonstrates the value of transparent reporting. Randomization and masking are identified, but the allocation procedure, analysis population, missing-data approach, multiplicity plan, and original sample-size rationale are not reported in the registry record. Those omissions do not invalidate the posted outcome, but they limit independent assessment of how the analysis was planned and how fully the results represent all randomized participants.

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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

Several trial-specific limitations affect interpretation. The enrolled sample was 45, with 29 participants in the alkaline-water arm and 16 in the distilled-water arm. These small, unequal groups produce limited precision for a binary outcome and make the arm percentages sensitive to individual observations. The registry does not report why the arm sizes differed or provide participant flow information.

The trial’s original sample-size justification and design assumptions are not reported in the registry record. The large sample-size figures are planning illustrations based on the observed effect, not evidence of the original target or a retrospective measure of study success. The full analysis plan, including any prespecified handling of multiple outcomes and time points, is also not reported. The posted p-value is unadjusted.

The record does not describe missing-data methods or define the analysis population. It is therefore unclear from the registry record whether every randomized participant contributed to the primary comparison and how any unavailable outcomes were handled. Details of the randomization procedure, allocation concealment, and masking implementation are also not reported.

The primary outcome is limited to grade 2 or higher acute skin toxicity at 1 month after treatment. Weekly summaries and toxicity features such as onset and resolution are described, but their results are not reported in the registry record. Change in urine pH is listed as a secondary outcome without a posted result. These omissions prevent assessment of the full range and timing of measured outcomes.

Finally, the posted safety summaries are descriptive. The registry does not give arm-specific detail for the listed serious-event terms or a comparative adverse-event analysis, and deaths are not reported in the registry record. These limitations constrain what can be concluded from the record without changing the basic description of the posted primary percentages.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Alkaline Water in Reducing Skin Toxicity in Women With Breast Cancer Undergoing Radiation Therapy — NCT01487954.
• Registry record last updated 2015-06-18; status last verified 2015-06.
• Results first posted 2015-06-18.
• 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

NCT01487954 is a completed randomized, double-masked, parallel-group phase II trial sponsored by Case Comprehensive Cancer Center. It enrolled 45 participants. Both arms received external beam radiation therapy; one arm used alkaline water and the other distilled water around treatment sessions.

The primary endpoint was the percentage of participants with acute grade 2 or higher radiation-related skin toxicity at 1 month after treatment, assessed with CTCAE Version 3.0. The posted percentages were 38.0% in each arm. The reported comparison has an unadjusted p-value of 0.977, and its confidence interval includes no difference while allowing contrasts in either direction.

The registry also lists change in urine pH as a secondary outcome, but a result is not reported in the registry record. Detailed weekly toxicity results, the original sample-size justification, missing-data handling, and the analysis population are not reported in the registry record.