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HIV Prevention Phase 3 Randomized Trial NCT01473472

IPERGAY: Complete Statistical Analysis of On-Demand PrEP for HIV Prevention

An independent statistical review of the randomized phase 3 IPERGAY trial evaluating on-demand antiretroviral pre-exposure prophylaxis for prevention of HIV infection in men who have sex with men.

IPERGAY · NCT01473472

Scope of this record

This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record.

1. Trial at a Glance

IPERGAY was a phase 3 randomized, quadruple-masked, parallel-design prevention trial evaluating on-demand antiretroviral pre-exposure prophylaxis for HIV infection.

400
Enrollment
2
Arms
3
Phase
2012-01
Start Date
FeatureIPERGAY
ConditionHIV Infection
Primary purposePrevention
AllocationRandomized
Design modelParallel
MaskingQuadruple
Lead sponsorANRS, Emerging Infectious Diseases

2. Clinical Question

Population

Men who have sex with men evaluated for prevention of HIV infection.

Intervention

Truvada (drug).

Comparator

Placebo (drug).

Primary Question

Does on-demand antiretroviral pre-exposure prophylaxis affect the occurrence of HIV-1 or HIV-2 infection?

3. Trial Design

Randomization

Participants were assigned using a randomized allocation.

Masking

The trial used quadruple masking.

Study Arms

The trial included two intervention arms: Truvada and placebo.

Follow-up

The trial end date was set by the scientific committee when the necessary number of primary endpoints had been reached without exceeding 5 years of follow-up.

4. Endpoints

EndpointDefinitionTime Frame
Contamination with HIV-1 or -2 First diagnostic proof of infection: positive HIV serum test using combined latest-generation tests HIV-1 + 2 or positive HIV-1-RNA Polymerase Chain Reaction (PCR) in plasma. From randomization to the end of the trial. The trial end date was set by the scientific committee when the necessary number of primary endpoints had been reached without exceeding 5 years of follow-up.

5. Planned Analysis

The registry identifies contamination with HIV-1 or HIV-2 as the primary endpoint but does not report posted statistical analyses or trial results.

For a randomized prevention trial with an infection endpoint, the statistical analysis would typically compare the incidence of infection between randomized groups using methods appropriate for time-to-event or risk-based outcomes. The choice of analysis depends on the prespecified statistical analysis plan, including event definitions, follow-up structure, censoring rules, and hypothesis framework.

No formal statistical analyses were posted to ClinicalTrials.gov. The registry reports the planned primary endpoint but does not provide posted estimates, confidence intervals, or p-values.

6. Statistical Methodology

The key statistical principle in this trial is the randomized comparison of infection outcomes between two groups. Randomization creates the framework for estimating the effect of the intervention while balancing measured and unmeasured factors on average.

Event-based analysis

The primary outcome is an infection event. Analyses of this type commonly focus on the difference in infection occurrence between randomized groups over follow-up, accounting for the timing of events and participants who do not experience infection during observation.

7. Statistical Methods Explained

Why is randomization important?

Randomization allows the comparison between intervention and placebo groups to be interpreted as a comparison created by the study design rather than by participant selection.

Why does the endpoint definition matter?

The primary endpoint depends on a specific diagnostic confirmation of HIV-1 or HIV-2 infection. Clear endpoint definitions prevent inconsistent classification of outcomes.

Why is follow-up time important?

Prevention trials measure events occurring over time. The length and structure of follow-up determine how much information is available for statistical comparison.

What does a confidence interval provide?

A confidence interval describes uncertainty around an estimated treatment effect. It does not describe the outcomes of individual participants.

Why are p-values not enough?

A p-value addresses compatibility of the observed data with a statistical model and null hypothesis. It does not measure clinical importance or the size of an effect.

8. Limitations

9. Why This Trial Matters Statistically

ConceptHow it appears in IPERGAY
Randomized designRandomized comparison of Truvada and placebo.
BlindingQuadruple masking.
Binary clinical outcomeHIV-1 or HIV-2 infection as the primary endpoint.
Prevention trial methodologyEvaluation of infection occurrence over follow-up.

10. Sources