Study to Evaluate GSK Biologicals' Herpes Zoster Vaccine GSK1437173A in Human Immunodeficiency Virus (HIV)-Infected Subjects: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Evaluate GSK Biologicals' Herpes Zoster Vaccine GSK1437173A in Human Immunodeficiency Virus (HIV)-Infected Subjects (NCT01165203), a randomized phase 2 study. The primary outcome is Number of Subjects With Serious Adverse Events (SAEs).

2. Clinical Question

The study also recorded immunogenicity measures, CD4 count, HIV viral load, and herpes zoster cases and complications. Those outcomes provide context for the broader safety and immunogenicity evaluation, but the stated primary endpoint is the count of participants with SAEs. The registry record does not report a separate primary question about clinical efficacy against herpes zoster.

3. Trial Design

This was a randomized, triple-masked, parallel-group Phase 2 study sponsored by GlaxoSmithKline. The registry describes 123 enrolled participants. Its brief summary calls the study observer-blind; the masking field records triple masking. The registry does not identify which study roles were masked, so those roles cannot be inferred from the record.

Participants were assigned to GSK1437173A or placebo. Both groups were scheduled to receive three intramuscular doses at Months 0, 2 and 6. The study evaluated safety and immunogenicity in HIV-infected subjects. Enrollment was to proceed through groups defined by ART use and CD4 T-cell counts: ART-treated subjects with high counts first, followed by ART-treated subjects with low counts and ART-naïve subjects with high counts. The registry does not give group-specific enrollment totals or results for those strata in the primary comparison.

The primary endpoint covered Month 0 to Month 18 and counted participants with at least one SAE in the Total Vaccinated cohort. That cohort included vaccinated subjects with at least one vaccine administration documented. The posted arm counts are 6 participants with SAEs among 74 in the vaccine group and 2 among 49 in the placebo group. The record also includes a secondary herpes zoster endpoint over Month 0 until Month 18 and lists immunogenicity, CD4 count, and HIV viral load outcomes.

The study started on 2010-09-30, reached primary completion on 2012-07-06, and is recorded as completed. The protocol posting was updated following Amendment 1 of the protocol, August 2010; the summary says the impacted section was exclusion criteria. The registry record does not report the original sample-size justification or additional operational details beyond those.

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.

Active Phase

Reasons for not completing this period:

Extended Safety Follow-up Phase

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The analysis was performed on the Total Vaccinated cohort, which included all vaccinated subjects with at least one vaccine administration documented.

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 Subjects With Serious Adverse Events (SAEs), measured over From Month 0 to Month 18.

The primary endpoint is the number of participants with serious adverse events from Month 0 to Month 18. It is a participant-count outcome: each group’s value represents participants meeting the SAE definition, rather than the total number of separate SAE episodes. The definition includes medical occurrences that result in death, are life threatening, require hospitalization or prolong hospitalization, or result in disability or incapacity.

Counting participants with at least one serious event is a way to summarize serious safety outcomes over a specified observation period. It gives a direct account of how many participants met the registry’s event definition in each group. It does not, by itself, describe the timing, duration, severity within the category, or recurrence of events. Nor does a participant count convey the full clinical detail of each event.

The posted analysis uses the Total Vaccinated cohort, defined as vaccinated subjects with at least one vaccine administration documented. This matters when interpreting the denominator: the reported results concern that cohort, not necessarily every enrolled subject. The registry record does not report additional details about exclusions from the cohort or missing endpoint observations.

As a general statistical point, safety outcomes are often presented as counts and group comparisons because the occurrence of an event is a clinically interpretable endpoint. The comparison still requires attention to the number of participants observed in each group and to uncertainty. Here, the posted risk difference and its confidence interval help describe the estimated between-group contrast and its precision; they do not determine the cause of any event or establish that an observed difference is attributable to treatment.

7. Results Posted in the Registry

• GSK1437173A Group: 8.1% (6/74) versus 4.1% (2/49) on control; risk difference 4.0 percentage points (95% CI -4.3 to 12.4), risk ratio 1.99 (0.42–9.44); unadjusted two-proportion z-test p = 0.375.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Number of Subjects With Any Herpes Zoster (HZ) Cases and Complications

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • GSK1437173A Group: 1.4% (1/74) versus 0.0% (0/49) on control; risk difference 1.4 percentage points (95% CI -1.3 to 4.0); unadjusted two-proportion z-test p = 0.414.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between GSK1437173A Group and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes extend beyond serious adverse events to herpes zoster cases and complications, VZV- and gE-specific CD4 T-cell frequencies, anti-VZV and anti-gE antibody concentrations, CD4 count, and HIV viral load. Some immune measures are listed both overall and by HIV status. This collection reflects the study’s stated interest in both safety and immunogenicity in HIV-infected subjects.

For the posted herpes zoster comparison, the registry records one participant with an HZ case in the GSK1437173A group and none in the placebo group. The estimated risk difference is 0.013, with a confidence interval from -0.013 to 0.040 and an unadjusted p-value of 0.414. The small number of observed cases and interval spanning zero leave substantial uncertainty. This outcome is distinct from the primary SAE endpoint and does not substitute for the primary safety comparison.

The secondary outcomes add useful descriptive context, but they do not change what the primary endpoint measures. Immune-response measures assess laboratory outcomes, while the HZ endpoint records participants with clinical cases and complications. The registry record does not report enough detail to infer that changes in immune measures correspond to clinical protection. Nor should an immune-response result be treated as equivalent to an SAE finding.

As a general statistical concern, multiple outcomes create multiple opportunities for apparently notable findings. If no multiplicity strategy is specified, unadjusted secondary results are less conclusive than results interpreted under a prespecified approach that accounts for the family of questions. The registry record does not report such a strategy. Secondary results are therefore best read as exploratory or descriptive evidence unless additional analysis details are reported; they should not be treated as independent confirmation of the primary result.

The posted record lists 7 secondary outcomes, including outcomes broken out by HIV status. It does not report a complete set of subgroup estimates or analysis details for all listed measures. The overall pattern should thus be viewed as a collection of different endpoint types, with differing meanings and precision, rather than as a single combined test of benefit or harm.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• -Frequencies of Varicella-Zoster Virus (VZV)- and gE-specific CD4 T-cells
• -Frequencies of Varicella-Zoster Virus (VZV)- and gE-specific CD4 T-cells, by HIV Status
• -Anti-VZV and Anti-gE Antibody Concentrations
• -Anti-VZV and Anti-gE Antibody Concentrations, by HIV Status
• Number of Subjects With Any Herpes Zoster (HZ) Cases and Complications
• CD4 Count
• HIV VL

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is binary at the participant level: a participant either had at least one SAE during the stated period or did not. The registry reports counts of participants with an event and the number of participants in each group. This supports a direct comparison of the observed event risks. The posted results give the risk difference, which expresses the difference between the groups’ event risks on an absolute scale. In this comparison, the placebo group is the reference and the estimate is reported for GSK1437173A relative to placebo.

What does the risk difference represent?

As a general statistical explanation, a risk difference subtracts one group’s event risk from the other group’s event risk. A value above zero indicates a higher observed risk in the group named in the comparison; a value below zero indicates a lower observed risk. The posted estimate is 0.040. The registry also reports group risks of 0.041 for placebo and 0.081 for GSK1437173A. These are the posted values and are not additional calculations. An absolute contrast is useful because it retains the scale of the outcome, although its interpretation depends on the event and follow-up period being compared.

What does the confidence interval add?

As a general explanation, a confidence interval describes uncertainty around an estimate under a statistical procedure. It helps readers assess which values remain reasonably compatible with the observed data and the method’s assumptions. The posted interval for the primary risk difference extends from -0.043 to 0.124. Since it includes zero, the posted data do not rule out a zero difference under that interval procedure. Its width also shows that a range of different magnitudes remains compatible with the comparison. The registry record does not state the confidence level, so no confidence level should be inferred from the interval alone.

How should the p-value be understood?

As a general statistical explanation, a p-value measures the compatibility of data with a specified null model, assuming that model and the test’s assumptions. It is not the probability that the null model is true, nor is it the probability that the result arose by chance in an everyday sense. The posted unadjusted p-value is 0.375. The registry record does not report a multiplicity adjustment for this comparison. A p-value also does not measure clinical importance, quantify the range of plausible effects, or replace assessment of the estimate and its interval.

The comparison is described as unadjusted. The registry record does not report a covariate-adjusted model, a stratified primary analysis, or a detailed statistical analysis plan. The allocation is randomized, but the existence of randomization does not establish that every possible analytic choice or assumption is documented in the registry. No adjustment details beyond the posted unadjusted result are reported in the registry record.

Why do sparse event counts matter?

As a general statistical point, estimates based on relatively few events tend to have substantial uncertainty. A small change in the number of participants with an event can shift the estimated risk difference, and interval estimates may be wide. This is relevant to the SAE comparison because the posted counts are 6 and 2. The interval reflects uncertainty in the contrast; it should not be read as proof that every value within it is equally likely or that values outside it are impossible.

The risk difference focuses on absolute contrast. Other measures, such as a risk ratio or odds ratio, describe relative contrast and can behave differently, particularly when event counts are small. The registry comparison also lists a risk ratio of 1.986 with interval values 0.418 and 9.444, and an odds ratio of 2.074 with interval values 0.401 and 10.72. These measures are not interchangeable with the absolute risk difference. They provide alternative scales for describing the same group comparison and remain uncertain in this study.

For count outcomes of this kind, the denominator and event definition are essential. The primary analysis was performed on the Total Vaccinated cohort, and the event definition concerns participants meeting the SAE criteria. The registry record does not give further detail on handling missing observations, event adjudication, or repeated events. As a general principle, if participants have different amounts of observed follow-up or incomplete outcome information, the analysis approach can affect interpretation; the registry record does not report enough detail to assess those possibilities.

The registry lists 28 outcome measures and 0 separately reported analyses. That does not erase the posted group counts and comparison estimates, but it means the record does not give a complete account of formal analysis specifications for all outcomes. The evidence should therefore be read as the posted summaries and estimates, without attributing undocumented modeling choices or decision rules to the investigators.

11. Confidence Intervals and Precision

The primary estimate is a risk difference of 0.040, with a confidence interval from -0.043 to 0.124. The interval includes zero and extends to negative and positive values. It therefore leaves uncertainty about whether the underlying difference is below zero, near zero, or above zero. Its span also permits differences larger than the point estimate. The estimate alone is not a precise description of the underlying contrast.

As a general explanation, a confidence interval communicates uncertainty in an estimate using a statistical procedure. It is not a guarantee that the true value lies inside the interval, and its interpretation depends on the method and assumptions used. The confidence level and interval-construction method are not reported in the registry record. That missing information limits a more specific assessment of the interval’s calibration.

The arm counts are 6 participants with SAEs among 74 in the GSK1437173A group and 2 among 49 in the placebo group. With relatively few observed events, the risk estimates can be sensitive to small changes in the event counts. This is one reason the interval is important alongside the point estimate. The listed risk ratio and odds ratio also have broad intervals, consistent with substantial uncertainty on those relative scales.

The posted comparison is unadjusted, and the registry record does not give a multiplicity procedure, missing-data method, or detailed analysis plan. Those omissions make it difficult to evaluate whether the reported uncertainty accounts for every analytic choice relevant to the broader outcome set. The interval should be read as precision for the reported comparison, not as a complete summary of all possible sources of uncertainty.

12. 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 80% power and participants per arm for 90% power. They are not total event counts. The registry’s planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is specified as a fraction of the observed effect. The original trial design assumptions are not reported in the registry record.

For planning for 100% of the observed effect, the figures are 553 participants per arm for 80% power and 740 participants per arm for 90% power. For planning for 75% of the observed effect, they are 908 participants per arm for 80% power and 1,215 participants per arm for 90% power. For planning for 50% of the observed effect, they are 1,870 participants per arm for 80% power and 2,502 participants per arm for 90% power.

In general, power is the probability that a study would meet its specified statistical criterion if a particular effect were the true effect and the planning assumptions held. The 80% and 90% columns represent different target probabilities under those assumptions; the higher target requires more participants in these illustrations. The listed values are planning illustrations based on the observed effect, not the trial’s original design justification. Smaller effects require more participants to detect under the stated assumptions. This is not observed power.

13. 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 = 0.041; treatment proportion p₁ = 0.081; average p̄ = 0.061.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3383 = 0.6631.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3371 = 0.2837.
4. n = (0.6631 + 0.2837)² / (0.0403)² = 553.0, rounded up to 553 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 <- 0.0408163265306122                          # control proportion
p1 <- 0.0810810810810811                          # 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(1165203)
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 = 553 (80% power), 740 (90% power)
 75% of observed effect: n per arm = 908 (80% power), 1,215 (90% power)
 50% of observed effect: n per arm = 1,870 (80% power), 2,502 (90% power)
power.prop.test: 553 
Simulated power at n = 553 per arm: 0.809 (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.

14. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a multiplicity adjustment or a prespecified hierarchy for the primary and secondary outcomes. It lists multiple outcome measures, including safety, clinical herpes zoster, immunogenicity, CD4 count, and HIV viral load. As a general statistical point, examining multiple outcomes can increase the chance that at least one result appears notable even when none represents a clear underlying effect. Adjustment methods or a prespecified testing sequence can address that issue, but the record does not say whether any such approach was used.

The posted p-values are described as unadjusted. They should not be interpreted as accounting for the full set of outcome questions. This is especially relevant for secondary endpoints, where an isolated result may be less persuasive if many outcomes were considered. The registry record does not report which outcomes, if any, were designated for formal confirmatory testing beyond the stated primary endpoint.

Details about missing data are not reported in the registry record. It does not describe how missing outcome measurements were handled, whether all participants had complete follow-up through Month 18, or how withdrawals and incomplete observations were treated in the analyses. The Total Vaccinated cohort is defined, but the record does not provide further analysis-population definitions for each outcome.

The record does not report a detailed statistical analysis plan, methods for adjustment of baseline characteristics, or sensitivity analyses. It also does not specify how recurrent events, if any, were handled for the participant-count endpoint. These omissions do not invalidate the posted counts, but they limit assessment of the full analytic process and of how robust results may be to alternative assumptions.

As a general explanation, a clear analysis plan helps distinguish prespecified questions from analyses chosen after data review, and transparent missing-data methods clarify how incomplete observations affect estimates. Without those details in the registry record, interpretation should stay close to the posted outcome definitions, counts, estimates, and stated cohort. No undocumented method or decision rule should be assumed.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: drug abuse (2.0%), peripheral vascular disorder (2.0%), anal abscess (1.4%), coronary artery disease (1.4%), epididymitis (1.4%).

The primary safety result counts participants with at least one serious adverse event during Month 0 to Month 18. The registry reports 6 participants among 74 in the GSK1437173A group and 2 among 49 in the placebo group. The posted risk difference is 0.040, with a confidence interval from -0.043 to 0.124 and an unadjusted p-value of 0.375. These figures describe the observed comparison in the Total Vaccinated cohort, not the total number of separate SAE episodes.

The registry also records zero deaths in each group. For other adverse events, it reports 72 participants among 74 in the vaccine group and 29 among 49 in the placebo group. Those figures are distinct from the SAE count and should not be combined with it. The record lists serious-event terms including Drug abuse, Peripheral vascular disorder, Anal abscess, Coronary artery disease, Epididymitis, and Laryngeal cancer recurrent; the listed percentages are 2.0%, 2.0%, 1.4%, 1.4%, 1.4%, and 1.4%, respectively.

These summaries do not show event timing, duration, severity detail, or causality. The estimated difference is uncertain, and a group comparison alone cannot establish that an event was caused by an intervention.

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

The posted results describe outcomes among participants in a randomized Phase 2 study of GSK1437173A and placebo. The primary comparison counts participants with SAEs in the Total Vaccinated cohort over Month 0 to Month 18. The point estimate is higher in the vaccine group, but the confidence interval includes zero and extends to differences in either direction. The data therefore do not give a precise estimate of the underlying group difference.

This result does not establish that GSK1437173A caused the observed events, nor does it establish that the groups had identical safety outcomes. The unadjusted p-value is not a probability that a treatment effect exists or does not exist. Interpretation should consider the event counts, the uncertainty interval, the cohort definition, and the fact that the registry record does not report details such as the missing-data method or multiplicity strategy.

The secondary herpes zoster endpoint recorded few cases, and its estimate is also uncertain. The immune-response outcomes address different questions from clinical events. They should not be treated as interchangeable with the primary safety endpoint or as proof of clinical effect. The registry record does not report a separate conclusion establishing clinical efficacy against herpes zoster.

More broadly, these results apply to the study’s enrolled HIV-infected adult population, the Total Vaccinated analysis cohort for the primary endpoint, and the stated observation period. They do not, by themselves, determine what would occur in other populations, under different treatment schedules, or over other follow-up periods. The registry record also does not provide detailed subgroup results for the ART and CD4 categories described in the study summary.

The appropriate reading is descriptive and cautious: the registry reports the observed participant counts and an uncertain unadjusted comparison. It does not support a definitive claim that the intervention improves or worsens health outcomes. Nor does the absence of a statistically notable result demonstrate equivalence or rule out meaningful differences. Those conclusions would require evidence and analyses beyond what the registry record reports.

17. Why This Trial Matters Statistically

This trial illustrates why safety comparisons need more than a point estimate. The primary endpoint is understandable as a count of participants with serious events, but the group counts are limited and the resulting interval is broad. Reporting the risk difference alongside its uncertainty makes clear that the observed contrast is not a precise estimate of a single underlying value.

It also illustrates that different outcomes answer different questions. SAEs, herpes zoster cases, laboratory immune responses, CD4 count, and HIV viral load are not interchangeable measures. A pattern in an immunogenicity measure would not by itself establish a clinical effect, and a participant-level safety count does not summarize every aspect of tolerability. Reading each outcome according to its definition prevents one type of evidence from being used as a substitute for another.

The registry’s planning illustrations show how strongly required sample size depends on the assumed effect. The figures rise as the target effect becomes a smaller fraction of the observed effect, under the stated planning assumptions. This is a useful statistical reminder that planning around a possibly unstable observed estimate can produce illustrations that are sensitive to the effect chosen. These calculations are not the trial’s original design justification.

Finally, the record makes the limits of registry reporting visible. It documents randomization, masking, cohort definition, outcomes, and posted comparisons, while leaving the multiplicity strategy, missing-data methods, detailed analysis plan, and original sample-size assumptions unreported. Those gaps matter when judging how fully the reported estimates capture uncertainty and how confidently multiple outcomes can be interpreted. A careful reading separates directly reported results from conclusions that would require additional methodological information.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The primary endpoint has few observed events, which limits precision. The confidence interval for the risk difference spans zero and a range of positive and negative values. The study’s enrollment and the primary analysis cohort are distinct concepts: the registry reports 123 enrolled participants, while the primary analysis is defined as the Total Vaccinated cohort. Further details about exclusions and endpoint completeness are not reported in the registry record.

The study summary describes sequential enrollment across ART and CD4 T-cell categories, but the posted primary comparison does not provide category-specific estimates. The registry record does not report whether the primary comparison adjusted for these characteristics or how the composition of the analysis groups relates to those categories. Generalizing the overall comparison to any subgroup is therefore not supported by the posted primary result.

The record does not report the original sample-size justification, a detailed statistical analysis plan, multiplicity handling, missing-data procedures, or sensitivity analyses. The planning illustrations are based on the observed effect and stated assumptions, not the trial’s own design. The registry also does not provide detailed event-level information, such as timing, duration, or repeated-event patterns, for the primary endpoint.

There is a broad set of secondary outcomes, but not all estimates and analysis details are present in the record. The secondary HZ endpoint has few cases, and immune-response measures address different constructs from clinical events. Without a reported multiplicity strategy, secondary results have less confirmatory weight. Finally, the posted comparison is unadjusted; the registry record does not report whether other analyses were performed outside the posted summaries.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Study to Evaluate GSK Biologicals' Herpes Zoster Vaccine GSK1437173A in Human Immunodeficiency Virus (HIV)-Infected Subjects — NCT01165203.
• Registry record last updated 2018-04-30; status last verified 2017-10.
• Results first posted 2017-06-07.
• 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.

22. Record Summary

NCT01165203 is a completed randomized, triple-masked, parallel-group Phase 2 study sponsored by GlaxoSmithKline. It enrolled 123 HIV-infected adults and compared three intramuscular doses of GSK1437173A with three doses of placebo, administered at Months 0, 2 and 6. The primary safety outcome was the number of participants with SAEs from Month 0 to Month 18 in the Total Vaccinated cohort.

The registry reports 6 participants with SAEs among 74 in the vaccine group and 2 among 49 in the placebo group. The unadjusted risk difference is 0.040, with a confidence interval from -0.043 to 0.124 and p = 0.375. The interval is broad and includes zero. Secondary outcomes cover herpes zoster, immune-response measures, CD4 count, and HIV viral load. The registry record does not report the original sample-size justification, a detailed analysis plan, multiplicity handling, or missing-data methods.