This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. The numerical results on this page are restricted to the ClinicalTrials.gov record.
1. Trial at a Glance
GS-US-292-0104 was a randomized, double-blind, parallel phase 3 trial comparing E/C/F/TAF with E/C/F/TDF in HIV-1 positive, antiretroviral treatment-naive adults. The registered primary endpoint was the percentage of participants with HIV-1 RNA < 50 copies/mL at Week 48, analyzed using the snapshot algorithm. The posted formal comparison used a Cochran-Mantel-Haenszel analysis and reported a risk difference with a two-sided 95.002% confidence interval.
| Feature | GS-US-292-0104 |
|---|---|
| Trial name | GS-US-292-0104 |
| ClinicalTrials.gov identifier | NCT01780506 |
| Phase | Phase 3 |
| Status | Completed |
| Therapeutic area | Infectious Disease |
| Conditions | HIV; HIV Infections |
| Enrollment | 872 |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | Double |
| Primary purpose | Treatment |
| Start | December 26, 2012 |
| Primary completion | August 26, 2014 |
| Lead sponsor | Gilead Sciences |
| Sponsor type | Industry |
2. Clinical Question
The central statistical question was whether E/C/F/TAF was sufficiently similar to E/C/F/TDF with respect to virologic response at Week 48 to satisfy the prespecified non-inferiority criterion. The primary endpoint measured the percentage of participants achieving HIV-1 RNA < 50 copies/mL at Week 48.
Population
HIV-1 positive, antiretroviral treatment-naive adults.
Intervention
E/C/F/TAF, with E/C/F/TAF placebo also listed among the trial interventions.
Comparator
E/C/F/TDF, with E/C/F/TDF placebo also listed among the trial interventions.
Primary question
Is the E/C/F/TAF group less than 12% worse than the E/C/F/TDF group with respect to the Week 48 virologic response rate?
3. Trial Design
E/C/F/TAF
- Randomized treatment group.
- Double-blind trial design.
- Evaluated for HIV-1 RNA < 50 copies/mL at Week 48.
- Primary analysis used the Full Analysis Set.
E/C/F/TDF
- Randomized comparator group.
- Double-blind trial design.
- Evaluated for HIV-1 RNA < 50 copies/mL at Week 48.
- Primary analysis used the Full Analysis Set.
The registry data list three arms and four intervention entries: E/C/F/TAF, E/C/F/TDF, E/C/F/TDF placebo, and E/C/F/TAF placebo. The formal statistical analysis in the ClinicalTrials.gov record compares E/C/F/TAF directly with E/C/F/TDF.
4. Analysis Population and Primary Endpoint
The posted primary analysis used the Full Analysis Set, defined in the trial data as participants who were randomized and received at least one dose of study drug. This is important because the analyzed population is not described simply as everyone enrolled: the formal comparison is based on randomized participants who also received study drug.
| Feature | Registered / reported specification |
|---|---|
| Primary endpoint | Percentage of Participants With HIV-1 RNA < 50 Copies/mL at Week 48 |
| Time frame | Week 48 |
| Endpoint type | Binary |
| Endpoint definition | The percentage of participants achieving HIV-1 RNA < 50 copies/mL at Week 48 was analyzed using the snapshot algorithm, which defines a patient's virologic response status using only the viral load at the predefined time point within an allowed window of time, along with study drug discontinuation status. |
| Analysis population | Full Analysis Set: participants who were randomized and received at least 1 dose of study drug. |
| Groups compared | E/C/F/TAF vs E/C/F/TDF |
| Method | Cochran-Mantel-Haenszel test |
| Effect measure | Difference in percentages; normalized as risk difference |
| Hypothesis type | Non-inferiority or equivalence |
5. What the Snapshot Algorithm Means
The primary endpoint was not simply a laboratory measurement recorded at any time during follow-up. The registry definition specifies the snapshot algorithm, which classifies virologic response using the viral load at the predefined Week 48 time point within an allowed window together with study-drug discontinuation status.
This distinction matters statistically. A binary endpoint constructed by an algorithm can classify participants differently from an analysis that uses every viral-load measurement longitudinally. The analysis therefore asks a specific question: what percentage of participants meet the protocol-defined virologic response classification at the Week 48 assessment window?
The endpoint is binary: each participant contributes to the response comparison according to the prespecified snapshot classification rather than contributing a continuous viral-load trajectory.
6. Primary Result
The ClinicalTrials.gov record contains one formal statistical analysis, corresponding to the primary endpoint. The reported comparison was between E/C/F/TAF and E/C/F/TDF in the Full Analysis Set.
Difference in percentages
95.002% CI: -3.0 to 4.0 · P = 0.78
Cochran-Mantel-Haenszel analysis adjusted by baseline HIV-1 RNA and region stratum.
| Primary analysis component | Reported result |
|---|---|
| Endpoint | Percentage of Participants With HIV-1 RNA < 50 Copies/mL at Week 48 |
| Comparison | E/C/F/TAF vs E/C/F/TDF |
| Analysis population | Full Analysis Set |
| Method | Cochran-Mantel-Haenszel |
| Effect measure | Difference in percentages / risk difference |
| Estimate | 0.5 |
| Confidence interval | 95.002% CI -3.0 to 4.0 |
| CI type | Two-sided |
| P-value | 0.78 |
| Hypothesis | Non-inferiority or equivalence |
| Adjustment | Mantel-Haenszel proportions adjusted by baseline HIV-1 RNA and region stratum |
The reported risk difference of 0.5 means that the estimated difference in the Week 48 virologic-response percentages was 0.5 percentage points for E/C/F/TAF relative to E/C/F/TDF under the reported analysis.
The estimate does not mean that 0.5% of participants responded, nor does it mean that an individual participant had a 0.5% greater probability of response. It is a between-group difference in the percentage meeting the prespecified binary endpoint.
The two-sided 95.002% confidence interval extends from -3.0 to 4.0. Thus, the observed estimate is compatible with a modest difference in either direction within the uncertainty represented by the reported interval.
The P-value of 0.78 is evidence about the compatibility of the observed data with the relevant null hypothesis under the specified test; it is not a measure of the magnitude or clinical importance of the treatment difference. A large or small P-value should not be substituted for the effect estimate and its confidence interval.
For this trial, the central issue is non-inferiority rather than simply asking whether a conventional superiority test produced a small P-value. The reported non-inferiority margin was 12%, so the confidence interval must be interpreted relative to that prespecified margin.
7. The Non-Inferiority Question
The registry-reported analysis text states the hypotheses explicitly. The null hypothesis was that the E/C/F/TAF group was ≥ 12% worse than the E/C/F/TDF group with respect to the percentage of participants achieving HIV-1 RNA < 50 copies/mL at Week 48. The alternative hypothesis was that E/C/F/TAF was < 12% worse than E/C/F/TDF.
Null hypothesis
The E/C/F/TAF group is at least 12% worse than the E/C/F/TDF group for the primary virologic-response endpoint.
Alternative hypothesis
The E/C/F/TAF group is less than 12% worse than the E/C/F/TDF group for the primary virologic-response endpoint.
The reported lower confidence limit of -3.0 is above the -12% boundary specified by the non-inferiority hypothesis. On the registry-reported analysis, the confidence interval therefore excludes differences as unfavorable as the prespecified non-inferiority margin.
This is the key statistical distinction between a non-inferiority analysis and an ordinary superiority test. The question is not whether the estimated difference is statistically distinguishable from zero. Instead, the question is whether the uncertainty around the difference excludes a loss large enough to cross the prespecified non-inferiority margin.
8. Why the Cochran-Mantel-Haenszel Test Was Used
The primary endpoint is binary: each participant is classified according to whether the Week 48 snapshot criterion is met. The Cochran-Mantel-Haenszel framework is designed for comparing categorical outcomes while accounting for prespecified strata.
In this analysis, the Mantel-Haenszel proportions were adjusted by baseline HIV-1 RNA and region stratum. This allows the treatment comparison to account for those stratification variables rather than treating every participant as though the comparison were completely unstratified.
The registry reports the resulting effect as a difference in percentages, with the effect measure described as a risk difference.
9. Statistical Methods Explained
Why is a binary endpoint analyzed differently from a continuous measurement?
The Week 48 primary endpoint classifies participants into a virologic-response outcome based on the snapshot algorithm. Because the outcome is binary, the treatment comparison focuses on percentages and their difference rather than a mean or median viral-load value.
What does a risk difference of 0.5 mean?
A risk difference of 0.5 represents a 0.5-percentage-point difference in the proportion meeting the primary response definition between E/C/F/TAF and E/C/F/TDF under the reported analysis. It is an absolute rather than relative effect measure.
Why does the confidence interval matter more than the P-value for non-inferiority?
Non-inferiority is defined relative to a clinically specified margin. The relevant question is whether the confidence interval extends beyond that margin. Here, the reported interval is -3.0 to 4.0, while the non-inferiority boundary is -12%.
Why adjust for baseline HIV-1 RNA and region?
The reported Mantel-Haenszel analysis uses these variables as strata. Stratification permits the comparison to account for differences across the prespecified baseline HIV-1 RNA and region strata when estimating the treatment difference.
Does P = 0.78 mean the treatments are equivalent?
No. A P-value does not establish equivalence or non-inferiority by itself. The non-inferiority conclusion is tied to the prespecified margin and the confidence interval. A P-value of 0.78 should therefore not be translated into a statement that the two treatments have exactly the same effect.
Why is the Full Analysis Set important?
The formal analysis was conducted in participants who were randomized and received at least one dose of study drug. Identifying the analysis population matters because treatment-effect estimates depend on which participants contribute data and how their outcomes are classified.
What does the snapshot algorithm contribute to the analysis?
It fixes the primary endpoint to a predefined Week 48 assessment framework and incorporates study-drug discontinuation status. This creates a prespecified binary classification rather than allowing investigators to select an arbitrary favorable viral-load measurement from follow-up.
10. Confidence Intervals and Precision
The reported confidence interval is -3.0 to 4.0 at the 95.002% level. The interval is centered around the reported estimate of 0.5, but its width communicates that the estimate is not known with unlimited precision.
Point estimate
The estimated risk difference is 0.5 percentage points.
Lower limit
The reported lower confidence limit is -3.0 percentage points.
Upper limit
The reported upper confidence limit is 4.0 percentage points.
Non-inferiority boundary
The specified boundary corresponds to being 12% worse than the comparator.
A confidence interval is an uncertainty statement about the estimated treatment effect under the statistical model and sampling framework. It is not the range of effects that individual participants experienced, and it does not imply that every value inside the interval is equally plausible.
11. Primary Result in Statistical Context
The primary analysis provides three pieces of information that should be read together: the effect estimate, the confidence interval, and the non-inferiority hypothesis.
| Question | Reported information | Statistical interpretation |
|---|---|---|
| What was estimated? | Difference in percentages / risk difference | The absolute difference in the proportion meeting the Week 48 response definition. |
| What was the estimate? | 0.5 | The estimated difference favored neither group by a large percentage-point amount. |
| How precise was it? | 95.002% CI -3.0 to 4.0 | The interval spans modest differences in either direction. |
| What was the non-inferiority boundary? | 12% worse | The relevant unfavorable boundary is -12 percentage points for the reported difference. |
| Does the CI cross that boundary? | No; lower limit -3.0 | The lower confidence limit remains above the non-inferiority boundary. |
| What was the P-value? | 0.78 | It does not measure effect size and is not the non-inferiority decision rule. |
The most important feature of this analysis is the relationship between the -3.0 lower confidence limit and the -12% non-inferiority boundary. The observed estimate is 0.5, and the entire reported confidence interval remains above the prespecified threshold for unacceptable loss of efficacy.
This does not establish that E/C/F/TAF and E/C/F/TDF are identical. The interval allows for differences in either direction. Rather, the analysis addresses whether the data exclude a treatment difference large enough to violate the stated non-inferiority criterion.
The result also should not be interpreted as evidence that every individual participant would have the same virologic outcome under either treatment. The analysis concerns a group-level binary endpoint in the specified Full Analysis Set.
12. Intention-to-Treat Principles and the Analysis Population
The registry-reported analysis text identifies intention-to-treat analysis as an additional concept and defines the Full Analysis Set as participants who were randomized and received at least one dose of study drug.
Randomization is important because it creates the basis for a treatment-group comparison that is less vulnerable to systematic baseline selection than a non-randomized comparison. At the same time, the exact analysis population still matters. A reader should not silently replace the reported Full Analysis Set with a different population and assume that the resulting estimate would be identical.
13. Safety Results
The ClinicalTrials.gov record includes serious adverse event counts by arm. These data should be kept separate from the primary efficacy analysis because safety and efficacy answer different statistical questions.
| Trial group | Serious adverse events affected / at risk | Design context |
|---|---|---|
| E/C/F/TAF | 73 / 435 | Double-blind |
| E/C/F/TDF | 65 / 432 | Double-blind |
| E/C/F/TAF to E/C/F/TAF | 0 / 90 | Open-label |
| E/C/F/TDF to E/C/F/TAF | 1 / 94 | Open-label |
The double-blind groups provide the principal randomized treatment comparison represented in the ClinicalTrials.gov record. The open-label cohorts are listed separately and should not be combined with the double-blind groups as though they represented the same randomized comparison.
14. What the Risk Difference Does — and Does Not — Mean
The reported risk difference of 0.5 is an absolute comparison of the percentages meeting the Week 48 binary response endpoint. Unlike a relative risk or odds ratio, it is expressed directly as a difference in percentages.
It does not mean that treatment changes the outcome probability by exactly 0.5 percentage points for every individual participant. It is an estimate for the populations represented by the analysis.
For a superiority analysis, a difference of zero is often the natural null value for a risk difference. For a non-inferiority analysis, the relevant question is different: how much worse can the new treatment be before the difference becomes unacceptable? Here, the registry-reported analysis defines that loss threshold as 12%.
The lower limit of the reported 95.002% confidence interval is -3.0. Because this remains above the prespecified -12% non-inferiority boundary, the interval does not include differences as unfavorable as the margin.
15. Multiplicity, Interim Analysis, Crossover, and Bayesian Methods
The ClinicalTrials.gov record does not report a formal multiplicity strategy, interim analysis procedure, crossover analysis, missing-data imputation method beyond the snapshot algorithm's treatment of discontinuation status, or Bayesian analysis. These topics therefore cannot be reconstructed from the ClinicalTrials.gov record without introducing information from outside the permitted trial data.
| Design topic | What the ClinicalTrials.gov record establishes |
|---|---|
| Multiplicity | No formal multiplicity procedure is provided in the ClinicalTrials.gov record. |
| Interim analysis | No interim-analysis method is provided in the ClinicalTrials.gov record. |
| Crossover | No crossover method or crossover analysis is provided in the ClinicalTrials.gov record. |
| Missing data / imputation | The primary endpoint definition specifies the snapshot algorithm and study-drug discontinuation status; no separate imputation model is provided. |
| Stratification | The primary analysis adjusts Mantel-Haenszel proportions by baseline HIV-1 RNA and region stratum. |
| Bayesian methods | No Bayesian method is reported in the ClinicalTrials.gov record. |
This distinction is important for an independent statistical analysis. Absence of a method from the ClinicalTrials.gov record is not evidence that a method was definitively absent from the full protocol or statistical analysis plan; it means that the method cannot be asserted here under the stated data rules.
16. Results Beyond the Primary Analysis
The registry record contains 24 posted outcome measures, but the ClinicalTrials.gov record contains only one formal statistical analysis, corresponding to the primary Week 48 virologic-response endpoint.
Accordingly, this page does not manufacture estimates, confidence intervals, or P-values for secondary outcomes. For a binary secondary endpoint, a categorical-data method such as a stratified comparison could be appropriate when specified by the protocol; however, the ClinicalTrials.gov record does not provide a formal secondary statistical comparison to report.
17. Limitations and Interpretation Issues
- Non-inferiority interpretation depends on the margin: the conclusion is meaningful only in relation to the prespecified 12% margin stated in the registry-reported analysis.
- The P-value is not the non-inferiority criterion: P = 0.78 should not be interpreted as a direct test of the -12% boundary.
- Binary endpoint: the primary outcome reduces Week 48 virologic response to a binary classification under the snapshot algorithm rather than modeling a continuous longitudinal viral-load trajectory.
- Analysis population: the formal result applies to the Full Analysis Set as defined in the ClinicalTrials.gov record: randomized participants who received at least one dose of study drug.
- Confidence-interval interpretation: the interval quantifies uncertainty around the estimated treatment difference; it does not describe individual-level treatment effects.
- Stratification: the reported treatment comparison was adjusted by baseline HIV-1 RNA and region stratum, so the estimate is not an unadjusted crude percentage difference.
- Safety evidence: serious adverse event counts are reported, but the ClinicalTrials.gov record does not provide formal statistical comparisons for these safety outcomes.
- Open-label cohorts: the ClinicalTrials.gov record contains open-label groups in addition to the double-blind groups. These should not be interpreted as another randomized comparison without additional design information.
- Limited formal analyses in the ClinicalTrials.gov record: the available statistical-analysis information contains one formal analysis, so secondary endpoints cannot be given the same quantitative treatment without additional data.
18. Why This Trial Matters Statistically
GS-US-292-0104 is a useful teaching case because its primary analysis illustrates a central principle of clinical-trial statistics: non-inferiority is a margin-based inference, not simply a test for a non-significant difference.
| Concept | How it appears in GS-US-292-0104 |
|---|---|
| Randomization | The trial uses randomized allocation in a parallel design. |
| Blinding | The trial is double-blind and lists active and placebo interventions. |
| Binary endpoint | Week 48 virologic response is defined as HIV-1 RNA < 50 copies/mL under the snapshot algorithm. |
| Non-inferiority | The primary hypothesis specifies a 12% allowable loss relative to E/C/F/TDF. |
| Risk difference | The reported treatment effect is a difference in percentages, normalized as a risk difference. |
| Confidence interval | The 95.002% CI is -3.0 to 4.0. |
| Cochran-Mantel-Haenszel method | The primary analysis uses a stratified categorical-data comparison. |
| Stratification | Baseline HIV-1 RNA and region stratum are incorporated into the Mantel-Haenszel adjustment. |
| Intention-to-treat principle | Intention-to-treat analysis is identified as a concept in the primary analysis. |
| Analysis population | The Full Analysis Set consists of randomized participants who received at least one dose of study drug. |
| P-values | The reported P-value is 0.78 and must be interpreted separately from the non-inferiority margin. |
| Safety analysis | Serious adverse events are reported separately by double-blind and open-label groups. |
19. A Worked Reading of the Primary Analysis
A useful way to read the result is to proceed in the same order that a statistical reviewer would.
Step 1 · Identify the endpoint
The endpoint is the percentage of participants with HIV-1 RNA < 50 copies/mL at Week 48 using the snapshot algorithm.
Step 2 · Identify the estimand
The reported effect is the difference in percentages between E/C/F/TAF and E/C/F/TDF.
Step 3 · Read the estimate
The estimated risk difference is 0.5.
Step 4 · Read the uncertainty
The two-sided 95.002% CI is -3.0 to 4.0.
Step 5 · Apply the margin
The lower confidence limit of -3.0 remains above the -12% non-inferiority boundary.
Step 6 · Keep P separate
P = 0.78 does not replace the margin-based non-inferiority assessment.
This sequence prevents a common interpretive error: starting with the P-value and only afterward asking what the trial was actually designed to establish. In a non-inferiority trial, the margin and confidence interval are central to the statistical argument.
20. Statistical Interpretation vs Clinical Interpretation
Statistical interpretation
The reported risk difference was 0.5, with a two-sided 95.002% confidence interval of -3.0 to 4.0. The lower confidence limit remained above the -12% non-inferiority boundary specified in the analysis.
Clinical interpretation
The ClinicalTrials.gov record supports interpretation of the primary Week 48 endpoint through the stated non-inferiority framework. The page does not translate that statistical result into treatment recommendations or broader clinical claims.
21. What the Trial Design Tells Us About the Evidence
The combination of randomized allocation, double masking, a parallel design, and a prespecified binary Week 48 endpoint creates a structured comparison between the two principal treatment groups. Randomization provides the design basis for comparing treatment assignments, while blinding reduces the potential for knowledge of assignment to influence trial conduct.
The statistical method then adds another layer: rather than simply comparing two crude percentages, the reported Cochran-Mantel-Haenszel analysis adjusts the Mantel-Haenszel proportions by baseline HIV-1 RNA and region stratum. The final effect measure is a risk difference, allowing the non-inferiority margin to be expressed on the same absolute scale.
These pieces should be read together. A numerical estimate cannot be interpreted independently of the endpoint definition, analysis population, stratification, hypothesis, and margin.
22. Related Tutorials
Learn more about the methods used in this trial:
23. Related Calculators
The primary analysis also provides a natural pathway into calculations involving binary endpoints, absolute treatment effects, and non-inferiority margins.
24. Sources
- ClinicalTrials.gov: NCT01780506 — GS-US-292-0104.
- Linked publication: PubMed 25890673.
- Linked publication: PubMed 28282300.
- Linked publication: PubMed 28076335.
- Linked publication: PubMed 26892863.
- Linked publication: PubMed 27742226.
Continue through Clinical Biostats
Use the related tutorials and calculators to explore the statistical concepts underlying randomized, non-inferiority, and categorical-endpoint analyses.
25. Record Summary
GS-US-292-0104 provides a clear example of how a randomized phase 3 trial can frame a binary efficacy endpoint as a non-inferiority question. The primary endpoint was the percentage of participants with HIV-1 RNA < 50 copies/mL at Week 48 under the snapshot algorithm. The formal analysis used the Full Analysis Set and a Cochran-Mantel-Haenszel method, with the Mantel-Haenszel proportions adjusted by baseline HIV-1 RNA and region stratum.
The reported effect was a 0.5 risk difference, with a two-sided 95.002% confidence interval of -3.0 to 4.0 and a P-value of 0.78. The central non-inferiority comparison is between the lower confidence limit of -3.0 and the prespecified 12% worse boundary: the confidence interval does not extend to that boundary. The statistical interpretation therefore depends on the non-inferiority framework rather than on the P-value alone.
The ClinicalTrials.gov record additionally report serious adverse events separately for double-blind E/C/F/TAF, double-blind E/C/F/TDF, and two open-label cohorts. Because the available statistical-analysis record contains one formal analysis, this page deliberately does not manufacture secondary endpoint estimates or unsupported safety comparisons.