Study of the Safety and Efficacy of Stribild Versus Atripla in Human Immunodeficiency Virus, Type 1 (HIV-1) Infected, Antiretroviral Treatment-Naive Adults: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of the Safety and Efficacy of Stribild Versus Atripla in Human Immunodeficiency Virus, Type 1 (HIV-1) Infected, Antiretroviral Treatment-Naive Adults (NCT00869557), a randomized phase 2 study. The primary outcome is The Percentage of Participants With HIV-1 Ribonucleic Acid (RNA) Less Than 50 Copies/mL at Week 24.

2. Clinical Question

3. Trial Design

The registry describes a Phase 2, randomized, parallel-group, active-controlled study of Stribild versus Atripla in adults with HIV-1 who were antiretroviral treatment-naive. Enrollment was 71. The brief summary describes a 2:1 randomization ratio favoring Stribild. Randomization was stratified by screening HIV-1 RNA level: 100,000 copies/mL or less versus more than 100,000 copies/mL. The posted primary outcome counts are 48 for Stribild and 23 for Atripla.

The registry records quadruple masking. Its brief summary describes the study as double-blinded, and the official title also uses double-blinded wording. The registry record does not explain the difference in masking descriptions. The planned treatment period described in the summary included blinded treatment and visits every 12 weeks after Week 48 until assignments were unblinded at Week 60. At the unblinding visit, participants could opt into an open-label rollover extension. The extension was scheduled to remain open until Stribild became commercially available or the sponsor elected to terminate the study.

The primary endpoint was assessed at Week 24. Secondary outcomes included HIV-1 RNA response at Week 48, change in HIV-1 RNA, CD4 cell-count changes at Week 24 and Week 48, and FDA-defined snapshot virologic success at Weeks 24 and 48. The record lists five posted secondary endpoints. The trial status is completed. The registry record does not report the original sample-size justification, the trial’s statistical analysis plan, or details of any interim analyses.

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.

Before assignment: 126 participants were screened; 71 were randomized (48 to the Stribild group and 23 to the Atripla group). All randomized participants received at least 1 dose of study medication and comprised the safety and intent-to-treat (ITT) analysis sets. No site enrolled more than 7% of participants.

Randomized Phase

Reasons for not completing this period:

Extension Phase

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: ITT analysis set (all participants who were randomized into the study and received at least 1 dose of study drug). The missing = failure (M = F) analysis method was used in which all missing data were considered as failure (HIV-1 RNA ≥ 50 copies/mL).

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.

Population: Safety Analysis Set: participants were randomized and received at least 1 dose of study medication.

6. Primary Endpoint

The registry lists the primary outcome as The Percentage of Participants With HIV-1 Ribonucleic Acid (RNA) Less Than 50 Copies/mL at Week 24, measured over Week 24.

The primary endpoint was the percentage of participants with plasma HIV-1 RNA below 50 copies/mL at Week 24. It is a binary response outcome: each participant is classified according to whether the viral-load threshold was met at that visit. The reported group percentage therefore describes the fraction classified as responding under the endpoint definition, rather than the size of an average change in viral load.

A viral-load threshold gives a clinically interpretable way to describe virologic status at a specified follow-up time. Comparing the response percentages between randomized groups addresses how often the defined threshold was reached under each assigned regimen in the study population. It does not, by itself, describe the full distribution of viral-load measurements, the timing of response, or outcomes beyond the measured time point.

The primary analysis used the ITT analysis set, defined in the registry as participants randomized and given at least 1 dose of study drug. Missing primary-outcome data were handled using missing equals failure: missing observations were classified as HIV-1 RNA at least 50 copies/mL. This makes the reported response percentage depend on both observed responses and the specified treatment of missing data. The registry description does not give further detail about the timing or amount of missing data.

7. Results Posted in the Registry

• Atripla: 87.0% (20/23) versus 89.6% (43/48) on control; risk difference -2.6 percentage points (95% CI -18.9 to 13.6), risk ratio 0.97 (0.81–1.17); unadjusted two-proportion z-test p = 0.743.

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.

The Percentage of Participants With HIV-1 RNA Less Than 50 Copies/mL at Week 48

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Atripla: 87.0% (20/23) versus 89.6% (43/48) on control; risk difference -2.6 percentage points (95% CI -18.9 to 13.6), risk ratio 0.97 (0.81–1.17); unadjusted two-proportion z-test p = 0.743.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Atripla and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Cluster Determinant 4 (CD4) Cell Count at Week 24

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Atripla: mean 117.00 versus 161.00 on control; difference -44.00 (95% CI -118.27 to 30.27), standardized effect d = -0.31; z-test p = 0.246.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Atripla and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in CD4 Cell Count at Week 48

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Atripla: mean 166.00 versus 240.00 on control; difference -74.00 (95% CI -158.53 to 10.53), standardized effect d = -0.44; z-test p = 0.086.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Atripla and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the description beyond the Week 24 primary endpoint. They include the viral-load threshold at Week 48, changes in HIV-1 RNA, CD4 cell-count changes at Week 24 and Week 48, and FDA-defined snapshot virologic success at Weeks 24 and 48. Across these measures, the posted results offer additional descriptions of virologic and immunologic outcomes at later or different assessment points. They should be read as context for the primary comparison, not as a replacement for it.

The Week 48 response outcome resembles the primary endpoint in using a viral-load threshold, while CD4 change is a continuous measure and HIV-1 RNA change summarizes a different aspect of virologic response. Different endpoints need not produce identical comparisons because they measure different outcomes and time points. The registry record does not provide a sponsor-reported analysis for the posted Week 48 response or CD4 comparisons. The unadjusted summaries do not establish a consistent treatment advantage across outcomes.

In general, examining multiple outcomes creates multiplicity: the more comparisons considered, the greater the chance that at least one result appears notable by chance alone. The registry record does not report a multiplicity adjustment or a hierarchy specifying how secondary outcomes should be interpreted. Unadjusted secondary results therefore carry less weight as confirmatory evidence than a prespecified primary analysis, particularly when several endpoints and time points are considered together. This does not make the secondary results irrelevant; it means they are best treated as descriptive and hypothesis-generating unless a prespecified analysis plan supports stronger claims.

The registry lists five posted secondary endpoints, but the record does not provide all analysis details for them. Their findings can help characterize the observed data, while uncertainty, missing-data handling, and multiplicity remain relevant to interpretation.

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

• The Percentage of Participants With HIV-1 RNA Less Than 50 Copies/mL at Week 48
• Change From Baseline in HIV-1 RNA (log_10 Copies/mL)
• Change From Baseline in Cluster Determinant 4 (CD4) Cell Count at Week 24
• Change From Baseline in CD4 Cell Count at Week 48
• The Percentage of Participants With Virologic Success at Weeks 24 and 48 Using FDA-Defined Snapshot Analysis and HIV-1 RNA Less Than 50 Copies/mL

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary because a participant either met the HIV-1 RNA threshold at Week 24 or did not, according to the stated definition. A group response percentage summarizes the proportion classified as meeting that threshold. The percentage is not a mean viral-load change, and a difference between response percentages is not the same measure as a difference in the viral-load values themselves.

How to read the group comparison

The registry reports response percentages of 89.6 for Stribild and 87.0 for Atripla. The sponsor’s reported comparison is a difference in response rates (%) of 2.8. The unadjusted re-calculation uses the risk-difference scale and sets Atripla relative to Stribild, giving -0.026. The scales and stated comparison order differ, so the signed estimates should not be read as if they were identically oriented numbers. The registry record does not explain the difference in presentation or provide enough detail to attribute it to a particular method.

A confidence interval describes a range of values compatible with the observed data under the analysis and its assumptions. It is not a guarantee that the true value lies in the interval, nor does it measure the probability that one treatment is better. For the primary sponsor analysis, the 95% confidence interval runs from -14.5 to 20.1 percentage points. The unadjusted re-calculation has an interval from -0.189 to 0.136 on the risk-difference scale. Each includes the no-difference value for its respective scale. The width indicates that the data do not estimate the comparison with high precision.

What the p-value conveys

The unadjusted re-calculation reports p = 0.743. A p-value describes how unusual data at least as incompatible with a specified no-difference model would be if that model and the analysis assumptions were correct. It is not the probability that there is no difference, and it is not a measure of the size or clinical importance of a difference. The sponsor’s reported analysis has no p-value in the registry record. The unadjusted p-value should not be substituted for a sponsor-reported inferential result.

Missing outcome data

The registry states that missing primary-outcome observations were counted as failures, defined as HIV-1 RNA at least 50 copies/mL. This missing-equals-failure convention is part of the endpoint analysis, not a statement that a missing observation was actually measured at or above the threshold. The approach yields a defined classification for the reported response calculation, but interpretation still depends on how much data were missing and why. The amount and reasons for missing primary data are not reported in the registry record.

Continuous secondary outcomes

CD4 cell-count changes are reported as group means with standard deviations. A mean summarizes the average change, while a standard deviation describes the spread of participant-level changes around that average. The unadjusted comparison is a mean difference, and its confidence interval expresses uncertainty about that comparison. These outcomes answer a different question from the binary viral-load endpoint. The registry posts mean differences and intervals, but it does not report sponsor analyses for these comparisons.

Spread matters when interpreting a mean: substantial variation among participants can leave considerable uncertainty around a group comparison even when the group means differ. In general, standard deviations describe variability among observations, whereas standard errors describe uncertainty in an estimated mean. Neither is interchangeable with a confidence interval. The posted summary statistics should be interpreted according to the measure named for each outcome.

General considerations for small studies

In general, estimates from a study with limited enrollment may be imprecise, especially when outcomes are compared between separate groups. Randomization supports a fair comparison on average, but it does not ensure that every baseline characteristic is balanced in a particular trial. A confidence interval helps show the range of uncertainty rather than relying only on the point estimate. The registry record does not provide baseline balance details or the sponsor’s full analysis method, so neither should be inferred from the outcome summary alone.

All recalculated comparisons are unadjusted. They should be distinguished from any adjusted or prespecified analysis the sponsor may have conducted, details of which are not reported in the registry record. In general, an adjusted model may account for specified covariates or design features, while an unadjusted comparison uses the posted group summaries without such adjustment. The record does not identify which statistical test or model generated the sponsor’s primary estimate.

11. Confidence Intervals and Precision

The primary estimate is accompanied by a 95% confidence interval from the sponsor’s analysis: -14.5 to 20.1 for the reported difference in response rates. Because the interval covers values on both sides of zero, it is compatible with a difference favoring either group as well as no difference. Its width is important: the observed point estimate does not pin down the size or direction of the underlying comparison precisely.

The unadjusted re-calculation reports a risk difference of -0.026, with a confidence interval from -0.189 to 0.136. This interval also includes zero. Its scale and comparison order differ from the sponsor’s percentage-point presentation, so its endpoints should be interpreted on the risk-difference scale and not directly compared numerically with the sponsor interval as though they were expressed identically.

In general, a confidence interval reflects both the observed data and the assumptions of the calculation. It is not a range containing every plausible individual outcome, and a narrower interval would indicate greater precision for the estimated group contrast. Neither interval demonstrates equivalence simply because it includes zero. For a non-inferiority or equivalence claim, the relevant margin and analysis rules must be known. The registry record does not report the margin or the method behind the sponsor’s non-inferiority or equivalence classification.

The relatively limited enrollment and the interval widths counsel against interpreting the close point estimates as evidence that the groups are indistinguishable. The intervals leave room for meaningful differences in either direction. Precision concerns apply to the estimates reported for this trial; they do not establish how a future study would turn out.

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 illustrations give participants per arm, not total events. They are based on the observed effect and use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. For each scenario, the effect to detect is the stated fraction of the observed effect. The original trial’s own design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the number of participants per arm in a hypothetical study that would have an 80% chance of detecting the specified effect under the stated assumptions, if that effect and assumptions held. The 90% power column describes the corresponding planning target for a higher chance of detecting it. These are prospective planning calculations; they do not indicate the probability that the completed trial found a true effect. This is not observed power.

The planning rows shrink the effect being targeted from the full observed effect to 75% and 50% of the observed effect. As the target effect becomes smaller, more participants are needed per arm to distinguish it from random variation at the stated power and significance level. The figures are illustrations based on the observed data, not evidence that the original investigators planned the study using those assumptions. They also should not be interpreted as a recommendation or as a guarantee that a study of a given size will produce a particular result.

The binary primary outcome and the continuous CD4 outcomes have separate planning illustrations based on their respective observed estimates. Those assumptions make the calculations useful for understanding how sample size responds to the target effect, but the registry record does not report the full design assumptions used for the actual trial.

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 = 0.896; treatment proportion p₁ = 0.870; average p̄ = 0.883.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4551 = 0.8919.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4547 = 0.3827.
4. n = (0.8919 + 0.3827)² / (-0.0263)² = 2,354.4, rounded up to 2,355 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 <- 0.895833333333333                          # control proportion
p1 <- 0.869565217391304                          # 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(869557)
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 = 2,355 (80% power), 3,152 (90% power)
 75% of observed effect: n per arm = 4,085 (80% power), 5,468 (90% power)
 50% of observed effect: n per arm = 8,960 (80% power), 11,995 (90% power)
power.prop.test: 2354.4 
Simulated power at n = 2,355 per arm: 0.804 (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. Analyses Reported by the Sponsor

The registry’s own primary analysis reports a difference in response rates of 2.8 percentage points, with a 95% confidence interval from -14.5 to 20.1. It is classified in the record as a non-inferiority or equivalence analysis. The registry does not report a p-value for this analysis, its statistical method, or the margin used for the classification.

The unadjusted re-calculation from the posted summary statistics gives a risk-difference estimate of -0.026, with an interval from -0.189 to 0.136 and an unadjusted p-value of 0.743. This calculation is a simple comparison using the posted group summaries; it does not reproduce an undocumented sponsor model. The direction is expressed as Atripla relative to Stribild, while the sponsor’s estimate is presented as a difference in response rates. The registry record does not explain the methodological or scaling reasons for the difference in their presentations.

The sponsor’s reported analysis should remain distinct from the recalculation. The recalculation is useful for a transparent, unadjusted comparison, but it cannot establish which unreported choices underlie the sponsor’s analysis or replace it. The registry record does not provide enough detail to reconstruct the sponsor’s primary analysis or determine whether its non-inferiority or equivalence criterion was met.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes, time points, or statistical comparisons are examined. In general, repeated testing increases the chance of a seemingly unusual result under a no-effect model. A prespecified hierarchy or adjustment can help control how the collection of results is interpreted. The registry record lists five secondary endpoints in addition to the primary endpoint but does not report a multiplicity strategy, any adjustment for secondary analyses, or an endpoint hierarchy beyond identifying the primary outcome.

The primary analysis uses the ITT analysis set, defined as participants randomized and given at least 1 dose of study drug. The registry also specifies missing equals failure for the primary endpoint, classifying missing results as HIV-1 RNA at least 50 copies/mL. This is a specific rule for the binary response outcome. The amount of missing primary data, reasons for missingness, and sensitivity analyses using alternative assumptions are not reported in the registry record.

The record does not specify how missing observations were handled for the secondary outcomes. It does not report detailed analysis populations for those endpoints, or whether any adjusted models were used. Those details matter because the analyzed participants and handling of missing values can affect estimates, particularly when outcomes are measured at different visits.

The registry identifies a non-inferiority or equivalence analysis for the primary comparison, but does not report its margin or method. Without that information, the classification cannot be fully evaluated from the record. The original sample-size assumptions, statistical plan, and interim-analysis details are also not reported in the registry record. These omissions limit reconstruction of the planned inferential framework and caution against treating unadjusted secondary findings as confirmatory.

16. Safety Results

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

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: appendicitis (4.8%), febrile neutropenia (4.3%), pyrexia (4.3%), vaccination site cellulitis (4.3%), platelet count decreased (4.3%).

The registry reports serious adverse events among 2 of 48 participants in the Stribild group and 1 of 23 in the Atripla group. It also reports 9 of 62 for the group labeled “All Stribild.” That is a separately listed group in the record; its relationship to the treatment-specific groups is not explained, so it should not be combined with them or treated as an additional randomized arm.

For other adverse events, the record reports 39 of 48 in the Stribild group, 20 of 23 in the Atripla group, and 57 of 62 for “All Stribild.” The listed serious-event terms include appendicitis at 4.8%, and febrile neutropenia, pyrexia, vaccination site cellulitis, platelet count decreased, and white blood cell count decreased at 4.3% each. Death counts are not reported in the registry record.

These are observed counts in the reported groups. They do not by themselves show whether a regimen caused an event or establish a comparative safety difference. The registry record does not provide additional details about event severity beyond the serious-event classification, exposure time, or the analysis used for safety comparisons.

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

The result describes the percentage of participants in each randomized group who met the Week 24 HIV-1 RNA threshold under the registry’s missing-equals-failure rule. The posted percentages are close, and the sponsor’s reported interval spans zero. The unadjusted re-calculation likewise has an interval including zero. These results show that this trial’s estimates do not precisely establish the direction or size of a difference between groups.

That uncertainty is not evidence that the treatments are identical. A failure to distinguish groups statistically is different from demonstrating equivalence. The registry labels the sponsor analysis as non-inferiority or equivalence, but the margin and method needed to assess that conclusion are not reported in the registry record. The posted estimates therefore should not be stretched into a claim of equivalence based solely on the close percentages.

The findings apply to the trial’s studied population and endpoint definition: antiretroviral treatment-naive adults with HIV-1, with response assessed at Week 24. They do not establish outcomes for populations not represented in the trial, outcomes at other times, or all aspects of treatment benefit and harm. The secondary outcomes and adverse-event counts add descriptive information but do not resolve the uncertainty in the primary comparison.

In general, a trial result is an estimate with uncertainty, not a guarantee about an individual participant’s outcome. The group percentages do not predict whether any particular person would meet the viral-load threshold. The registry record also does not provide enough information to infer the effect of missing-data patterns beyond the stated classification rule, or to reconstruct all elements of the sponsor’s inferential analysis.

18. Why This Trial Matters Statistically

This trial illustrates why an endpoint definition and missing-data rule belong alongside a headline response percentage. The primary outcome is not simply a measured viral-load value: it is whether a participant met a specified threshold at Week 24, with missing results classified as failures. That rule affects what the response percentages represent and makes the analysis definition central to interpretation.

It also illustrates the distinction between an observed estimate and its precision. The two posted response percentages are close, but the sponsor’s confidence interval is broad and includes values in both directions. The unadjusted recalculation leads to the same broad lesson: the data do not sharply determine the direction or magnitude of the comparison. A point estimate alone would obscure that uncertainty.

The registry’s non-inferiority or equivalence classification raises a further statistical issue. Such claims require a defined margin and suitable analysis; neither is reported in the registry record. A close pair of percentages or a confidence interval containing no difference is not enough on its own to demonstrate equivalence. The record therefore shows why labels should be interpreted together with the design and analysis details supporting them.

Finally, multiple endpoints and time points make the secondary results useful context but require caution. Without a reported multiplicity plan, unadjusted secondary comparisons should not be treated as independent confirmation. The trial offers a practical example of how randomization, endpoint construction, uncertainty, missing data, and multiplicity all shape what can be concluded from clinical-trial results.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The primary comparison comes from a Phase 2 trial with enrollment of 71. The registry reports group counts of 48 for Stribild and 23 for Atripla for the primary outcome. The confidence intervals are broad, limiting precision. The study therefore provides a relatively uncertain estimate of the group contrast rather than a sharply determined effect.

The registry’s own analysis is described as non-inferiority or equivalence, but the margin and statistical method are not reported. The sponsor’s result cannot be fully evaluated or reproduced from the registry record. The unadjusted recalculation is not a substitute for the sponsor’s analysis and does not address unreported modeling choices.

The primary endpoint uses a missing-equals-failure rule, but the amount and reasons for missing primary data are not reported. The registry record does not describe sensitivity analyses for missingness. It also does not provide the analysis populations or missing-data methods for the secondary outcomes. These omissions constrain assessment of how robust results may be to analysis choices.

Five secondary endpoints are posted, but a multiplicity approach is not reported. Secondary comparisons should therefore be interpreted cautiously. The registry record also does not report the original sample-size justification, the full statistical analysis plan, or interim-analysis details. Finally, the safety record lists a separate “All Stribild” group without explaining how it relates to the treatment-specific groups, and deaths are not reported in the registry record. These limitations restrict what can be inferred from the safety summaries.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study of the Safety and Efficacy of Stribild Versus Atripla in Human Immunodeficiency Virus, Type 1 (HIV-1) Infected, Antiretroviral Treatment-Naive Adults — NCT00869557.
• Registry record last updated 2014-06-04; status last verified 2014-05.
• Results first posted 2012-10-22.
• 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.

23. Record Summary

The registry record describes NCT00869557 as a completed Phase 2 randomized, parallel-group, active-controlled study of Stribild versus Atripla in antiretroviral treatment-naive adults with HIV-1. Enrollment was 71. The primary endpoint was the percentage with HIV-1 RNA below 50 copies/mL at Week 24, analyzed in participants randomized and given at least 1 dose, with missing observations classified as failures.

The posted Week 24 response percentages were 89.6 for Stribild and 87.0 for Atripla. The sponsor reported a difference in response rates of 2.8 percentage points, with a 95% confidence interval from -14.5 to 20.1. The simple unadjusted recalculation was -0.026 on the risk-difference scale, with an interval from -0.189 to 0.136 and p = 0.743. The confidence intervals include zero and leave uncertainty about the direction and magnitude of the comparison.

The record also posts secondary outcomes and safety counts, but does not report a multiplicity strategy, the non-inferiority or equivalence margin, or the full statistical analysis plan. Those omissions limit interpretation of the secondary findings and the sponsor’s inferential claim.