Acyclovir in Preventing Herpes Simplex Virus Infection in Patients With Neutropenia: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Acyclovir in Preventing Herpes Simplex Virus Infection in Patients With Neutropenia (NCT00855309), a randomized phase 3 study. The primary outcome is Number of Participants Experiencing Incidence of Nephrotoxicity, Defined as a Serum Creatinine ≥ 2 Times the Patient's Baseline.

2. Clinical Question

The registry record describes a randomized phase III comparison of two intravenous acyclovir regimens for herpes simplex virus prophylaxis in patients with neutropenia. The primary posted outcome was nephrotoxicity, measured by the number of participants whose serum creatinine reached at least twice their baseline. The outcome timeframe is recorded as 24 hours.

The posted result concerns this kidney-related safety outcome. It does not provide a primary posted measure of herpes simplex virus infection prevention. The registry record’s brief summary describes prevention as the trial’s purpose and also says the trial is studying side effects, but the primary outcome listed in the results is nephrotoxicity. The comparison therefore addresses a specific recorded safety endpoint rather than every possible benefit or harm of either regimen.

3. Trial Design

This was a randomized, parallel-group phase III trial sponsored by Wake Forest University Health Sciences. The registry record lists the trial as completed, with a start date of 2008-11 and primary completion in 2013-11. Enrollment is recorded as 112. The posted outcome groups contain 56 participants in Arm I and 55 in Arm II; these are the group sizes recorded for this endpoint.

Arm I received weight-based intravenous acyclovir sodium every 8 or 12 hours. Arm II received low-dose intravenous acyclovir sodium every 8 or 12 hours. The record names acyclovir sodium as the intervention but does not provide numerical doses. Allocation is listed as randomized, the model as parallel, and masking as none. Thus, the record describes random assignment to concurrent groups, without masking.

The listed primary outcome is the number of participants experiencing nephrotoxicity, defined as serum creatinine at least twice the participant’s baseline. Its timeframe is recorded as 24 hours. The outcome is a count of participants with an event, not a measurement of the average change in creatinine. The registry record lists one outcome measure and no secondary outcomes in the posted results.

Details such as eligibility criteria, randomization procedures, the original sample-size justification, and the trial’s full analysis plan are not reported in the registry record. The registry record also does not report how the 24-hour timeframe was operationalized or whether other follow-up periods were assessed. These gaps limit how fully the trial conduct and the relationship between the registered outcome and the posted comparison can be evaluated.

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

Reasons for not completing this period:

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 Number of Participants Experiencing Incidence of Nephrotoxicity, Defined as a Serum Creatinine ≥ 2 Times the Patient's Baseline, measured over 24 hours.

The primary endpoint counts participants whose serum creatinine reached at least twice their own baseline. Serum creatinine is a laboratory measure used in assessing kidney function, and the endpoint uses a threshold to classify whether a participant experienced the specified event. The registry record labels the outcome as nephrotoxicity and records its timeframe as 24 hours.

Using a participant count makes the endpoint binary at the individual level: a participant either meets the stated definition or does not. The group result is therefore reported as the number of participants with the event, alongside the number at risk in each arm. It is not a direct estimate of the average laboratory value, the size of any creatinine change, or the duration of an event.

General statistical context: a threshold-based endpoint can make groups straightforward to compare, but it also compresses laboratory information. Participants with changes that do not reach the threshold are not counted as events under this definition, while the endpoint does not distinguish among participants who do meet it. The threshold’s clinical interpretation and the reasons it was selected are not reported in the registry record.

The registry record’s stated trial purpose also mentions prevention of herpes simplex virus infection. That infection outcome is not the primary result posted in the outcome data. The recorded primary endpoint instead addresses nephrotoxicity, so it should be interpreted as a specific safety measure, not as a complete account of infection prevention or overall safety.

7. Results Posted in the Registry

• Arm II: 5.5% (3/55) versus 3.6% (2/56) on control; risk difference 1.9 percentage points (95% CI -5.8 to 9.6), risk ratio 1.53 (0.27–8.79); unadjusted two-proportion z-test p = 0.632.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary result is a binary outcome summarized as counts of participants with an event. The comparison reported for Arm II is a risk difference: the event proportion in Arm II minus the event proportion in Arm I. A positive value therefore points toward a higher event proportion in Arm II, while a negative value points toward a higher event proportion in Arm I. The posted point estimate is positive, but its interval extends across zero, so the observed direction is not precisely determined.

What does a risk difference communicate?

General statistical context: a risk difference expresses an absolute contrast between two event proportions. Unlike a relative measure, it is stated in the scale of the event proportion itself. The registry record also lists relative measures, but the posted comparison’s risk difference is the measure used for the interpretation above. The underlying arm counts are 2 events among 56 participants in Arm I and 3 among 55 in Arm II. No additional percentage or contrast needs to be inferred from those counts to understand the posted result.

The direction of a comparison depends on which arm is subtracted from which. Here, the record identifies Arm I as the control and presents the comparison for Arm II. Reading the estimate with that ordering is important: a positive risk difference means the recorded event proportion is higher in Arm II at the point estimate. It does not, by itself, establish a real underlying difference or its clinical importance.

How should the p-value be read?

The unadjusted p-value is 0.632. General statistical context: a p-value is calculated under a null hypothesis and statistical model, and describes how unusual the observed data, or data more extreme, would be if that null model were true. It is not the probability that the null hypothesis is true, and it is not a measure of the probability that the result will replicate. The registry record does not describe the test used or provide a fuller statistical analysis plan, so the p-value should be read as the unadjusted value posted rather than as a complete account of the analysis.

The value does not demonstrate equality between the regimens. Evidence for equivalence or non-inferiority generally depends on a prespecified margin and an analysis designed to assess that margin; such a margin and analysis are not reported in the registry record. A non-significant result can reflect limited information as well as a small underlying contrast. The interval’s span across values on both sides of zero reinforces that the result leaves uncertainty about direction.

Why do sparse events matter?

General statistical context: when only a few participants experience an event, each observed event can have substantial influence on an estimated group contrast. Sparse binary data can therefore produce imprecise estimates and broad intervals. This matters in the present comparison because the posted event counts are 2 and 3. The absence of a statistically decisive result should not be mistaken for evidence that a meaningful difference has been ruled out.

For a binary outcome, methods may use different approximations or exact procedures, and they may handle small counts differently. The registry record does not identify the procedure behind the posted risk difference, interval, or p-value. Accordingly, the posted comparison can be described, but its computational details cannot be reconstructed from the registry record alone.

What does randomization contribute?

General statistical context: random allocation is intended to make treatment groups comparable, on average, with respect to factors known and unknown at assignment. It supports a comparative interpretation when the allocation is implemented as planned and the analysis preserves the randomized comparison. The record identifies the trial as randomized and parallel, but does not report sequence generation, concealment, deviations from assigned treatment, or the analysis population. Those details are relevant to assessing how well the intended randomized comparison is represented in the posted result.

The registry record lists no analysis entries and does not describe whether the primary comparison was adjusted or whether an intention-to-treat analysis was used. The comparison is labeled unadjusted, but that label alone does not answer questions about which participants were included or how missing outcome information was handled. No secondary outcome measures are posted, and the record does not state how multiplicity was considered. These omissions are important when interpreting a single result within the wider trial record.

Finally, the endpoint is a threshold-based count recorded with a 24-hour timeframe. It does not give the distribution of creatinine changes or identify outcomes outside that definition. Statistical interpretation should remain tied to this particular endpoint and timeframe, rather than extending to all kidney outcomes, all adverse effects, or the trial’s stated infection-prevention purpose.

10. Confidence Intervals and Precision

The posted risk-difference interval extends from below zero to above zero. Because zero represents no difference on the risk-difference scale, an interval spanning zero is compatible with both a lower event proportion in Arm II and a higher event proportion in Arm II. The registry record does not report the confidence level for this interval, so a specific level should not be assumed from the record.

General statistical context: a confidence interval conveys uncertainty around an estimate under the method used to construct it. A narrow interval indicates more precision than a broad interval, while an interval that includes materially different possibilities leaves greater uncertainty about the true contrast. In this trial, the low event counts and the interval’s span across zero mean the direction and size of the contrast are not established precisely by the posted data.

The unadjusted p-value is 0.632. It is not a substitute for the interval: the p-value summarizes evidence relative to a null model, whereas the interval describes a range of contrast values compatible with the data under its construction method. Neither alone establishes equivalence. The registry record does not report an equivalence margin or a precision target for the original trial.

The event counts also constrain precision. The posted result is based on 2 events in Arm I and 3 in Arm II. With so few recorded events, the estimate is sensitive to individual outcomes, and further data could materially change the apparent contrast. The precision statement applies only to nephrotoxicity as defined by the creatinine threshold and recorded timeframe; it does not describe precision for infection prevention or other outcomes.

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 participants per arm for this binary endpoint, not total events. They are illustrations based on the observed effect, rather than the original trial’s design calculation. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect used for each illustration is the stated fraction of the observed effect.

The 80% power column gives the number of participants per arm the planning calculation estimates would be needed for an 80% chance of detecting the chosen effect under those assumptions. The 90% power column gives the corresponding estimate for a 90% chance. These are planning targets under the stated model, not guarantees about the outcome of a future trial. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The planning display includes calculations for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For 80% power, the listed figures are 1,907, 3,222, and 6,868 participants per arm, respectively. For 90% power, the listed figures are 2,552, 4,312, and 9,193 participants per arm, respectively. The pattern illustrates the general principle that smaller effects require more participants to detect under otherwise unchanged assumptions.

These calculations are not observed power. They are planning illustrations derived from the observed effect, and the original design rationale is not reported in the registry record. Their interpretation depends on the stated assumptions and on whether a future study’s population, endpoint, and analysis are sufficiently similar.

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 = 0.036; treatment proportion p₁ = 0.055; average p̄ = 0.045.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.2936 = 0.5754.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.2933 = 0.2468.
4. n = (0.5754 + 0.2468)² / (0.0188)² = 1,906.4, rounded up to 1,907 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 <- 0.0357142857142857                          # control proportion
p1 <- 0.0545454545454545                          # 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(855309)
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 = 1,907 (80% power), 2,552 (90% power)
 75% of observed effect: n per arm = 3,222 (80% power), 4,312 (90% power)
 50% of observed effect: n per arm = 6,868 (80% power), 9,193 (90% power)
power.prop.test: 1906.4 
Simulated power at n = 1,907 per arm: 0.801 (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 record lists one outcome measure and no secondary outcomes in the posted results. It also lists no analysis entries. The comparison result for the primary endpoint is posted, but the registry record does not provide a full statistical analysis plan or describe how outcomes and analyses were selected.

Multiplicity arises when multiple outcomes, comparisons, timepoints, or analyses are considered. General statistical context: examining multiple results can increase the chance of finding an apparently unusual result by chance, so a prespecified strategy may address how results are interpreted or adjusted. Whether such a strategy was used in this trial is not reported in the registry record. The presence of one posted outcome measure does not establish that only one outcome or analysis was considered during the trial.

The registry record identifies the comparison’s p-value as unadjusted. It does not state whether any adjustment was planned, whether other comparisons were made, or whether the result was selected from a larger set of analyses. No multiplicity correction should be inferred from the absence of posted secondary results.

Handling of missing data is also not reported in the registry record. The record does not describe whether all randomized participants had outcome data, how missing creatinine measurements were handled, or whether participants were excluded from the analysis. The posted groups list 56 and 55 participants at risk, but those counts alone do not establish the analysis population or explain missingness.

The analysis population is not reported in the registry record. There is no stated intention-to-treat, per-protocol, or other population definition, and no account of treatment discontinuation or crossover. These details matter because the group contrast may depend on which participants and measurements were included. Without them, the posted count comparison can be described, but the handling of incomplete data and the exact analytic population cannot be independently assessed.

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 0% reporting threshold.

Most frequent non-serious adverse event terms

The serious adverse event record lists 0 participants with serious adverse events in Arm I and 0 in Arm II. It lists 56 participants at risk in Arm I and 55 in Arm II. The record gives no serious adverse event terms. These entries describe the posted serious-event counts; they do not show that every possible adverse effect was assessed or reported.

The same adverse-event record lists 2 participants with other adverse events in Arm I and 3 in Arm II. Those entries are separate from the serious adverse event counts. The registry record does not provide descriptions of the other adverse events, so their nature and severity cannot be characterized from these figures.

Death counts are not reported in the registry record. The serious-event figures should be read alongside, not in place of, the primary nephrotoxicity outcome. The primary endpoint is a specific creatinine-threshold event, while the adverse-event listing is a separate record of serious and other adverse events. Neither listing alone provides a comprehensive account of safety.

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

The posted data show 2 participants meeting the nephrotoxicity definition in Arm I and 3 in Arm II. The estimated risk difference is positive in the comparison for Arm II, but the posted interval includes values on both sides of zero, and the unadjusted p-value is 0.632. Together, these results do not precisely establish the direction or size of a difference between the regimens for this endpoint.

They also do not establish that the regimens are equivalent. Equivalence is a specific statistical claim that requires a defined margin and a suitable analysis; neither is reported in the registry record. A result that does not provide clear evidence of a difference is not the same as evidence that differences are absent or sufficiently small.

The finding applies to the registry’s defined endpoint: participants with serum creatinine at least twice baseline, with a timeframe recorded as 24 hours. It does not describe smaller creatinine changes, the duration of any change, or all possible kidney effects. The adverse-event listing contains separate serious and other adverse-event counts, but does not supply descriptions of the other events. Death counts are not reported in the registry record.

The trial’s stated purpose includes herpes simplex virus prophylaxis, but the primary outcome posted in the registry record is nephrotoxicity. The result therefore does not establish whether either regimen prevented herpes simplex virus infection. Nor does this single safety endpoint summarize all possible benefits and harms of the regimens.

The randomized parallel-group design provides a comparative framework, but important analytic details—including the analysis population, missing-data handling, and statistical plan—are not reported in the registry record. The results are best understood as a limited comparison of a specific safety outcome, with substantial uncertainty about the contrast and without a posted primary infection-prevention result.

16. Why This Trial Matters Statistically

This trial illustrates an important distinction between an observed difference and a precisely estimated difference. The posted event counts are 2 in the weight-based arm and 3 in the low-dose arm. Although the point estimate is positive for the comparison of Arm II against Arm I, the interval extends across zero and the unadjusted p-value is 0.632. The data therefore leave uncertainty about both the direction and size of the contrast.

That distinction matters in clinical research because a result that is not statistically decisive can be misread as proof that two groups are the same. The registry record does not report an equivalence margin or a design intended to demonstrate equivalence. The posted result should not be treated as establishing that the regimens have identical nephrotoxicity risk, nor as proving that one has greater risk.

The endpoint also demonstrates how a threshold affects interpretation. A participant is counted as having the event when serum creatinine reaches at least twice baseline; the result does not reflect the full range of laboratory changes. A binary count is useful for a defined event comparison, but it cannot show how far values moved or what happened outside the stated threshold and timeframe.

Finally, the planning illustrations connect the observed effect to future study planning while making clear that design assumptions matter. Smaller effects require more participants under the listed assumptions. These calculations are not the trial’s original sample-size rationale and are not observed power. The registry record’s missing analysis details also show why a result’s numerical summary and its underlying methods should be considered together.

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 registry record provides limited detail for evaluating trial conduct and analysis. It does not report eligibility criteria, baseline participant characteristics, numerical doses, randomization procedures, or the original sample-size justification. Masking is listed as none, which is relevant when considering outcome assessment and other trial processes, although the extent of any influence is not reported.

The primary endpoint is defined using a creatinine threshold and a timeframe of 24 hours. The registry record does not explain how the timeframe was applied, whether additional measurements were assessed, or how changes below the threshold were handled. The outcome therefore provides a narrow account of nephrotoxicity rather than a complete description of kidney effects.

The posted counts are sparse: 2 events in Arm I and 3 in Arm II. The risk-difference interval spans zero, leaving considerable uncertainty about the direction and size of the contrast. The registry record does not report the confidence level, the statistical procedure used to construct the interval, or the test underlying the unadjusted p-value.

Further analysis details are not reported in the registry record, including the analysis population, missing-data methods, treatment adherence, and whether any protocol deviations occurred. The record lists no secondary outcomes and no analysis entries, so it does not provide a broader outcome profile or a full account of analyses. Death counts are not reported, and the other adverse events are not described.

Although the trial’s stated purpose includes herpes simplex virus prophylaxis, the primary posted outcome is nephrotoxicity. No primary infection-prevention result is included in the outcome data. These limitations restrict conclusions to the posted safety endpoint and leave important questions about broader efficacy and safety unanswered by the registry record.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Acyclovir in Preventing Herpes Simplex Virus Infection in Patients With Neutropenia — NCT00855309.
• Registry record last updated 2018-07-06; status last verified 2018-07.
• Results first posted 2013-11-25.
• 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

NCT00855309 is a completed randomized phase III parallel-group trial sponsored by Wake Forest University Health Sciences. The registry record lists a start date of 2008-11, primary completion in 2013-11, and enrollment of 112. Masking is listed as none.

Arm I received weight-based intravenous acyclovir sodium every 8 or 12 hours, and Arm II received low-dose intravenous acyclovir sodium every 8 or 12 hours. The primary posted outcome was the number of participants with nephrotoxicity, defined as serum creatinine at least twice baseline, with a timeframe recorded as 24 hours.

The posted outcome counts were 2 in Arm I and 3 in Arm II. The risk-difference estimate for Arm II was positive, the interval extended across zero, and the unadjusted p-value was 0.632. The registry record lists no secondary outcome measures or analysis entries. Its posted primary result concerns nephrotoxicity, not herpes simplex virus infection prevention.