This page separates reported trial results from statistical interpretation. Numerical results are restricted to the ClinicalTrials.gov trial data posted on ClinicalTrials.gov for ACTG A5279. Where the ClinicalTrials.gov record does not provide a result or design detail, that information is not reconstructed from external publications.
1. Trial at a Glance
ACTG A5279, also known as the Brief Rifapentine-Isoniazid Evaluation for TB Prevention (BRIEF TB), was a randomized phase 3 prevention trial comparing two tuberculosis-prevention regimens in a population with HIV infection. The registry reports 3000 enrolled participants, two arms, and a primary endpoint based on the incidence of active tuberculosis or specified deaths.
| Feature | ACTG A5279 |
|---|---|
| Brief title | Brief Rifapentine-Isoniazid Evaluation for TB Prevention (BRIEF TB) |
| Phase | Phase 3 |
| Status | COMPLETED |
| Conditions | Tuberculosis; HIV Infections |
| Allocation | RANDOMIZED |
| Design model | PARALLEL |
| Masking | NONE |
| Primary purpose | PREVENTION |
| Enrollment | 3000.0 |
| Arms | 2 |
| Start | 2012-05-23 |
| Primary completion | 2017-11-14 |
| Lead sponsor | National Institute of Allergy and Infectious Diseases (NIAID) |
| Sponsor type | NIH |
| ClinicalTrials.gov | NCT01404312 |
2. Clinical Question
The statistical question was whether the rifapentine-plus-isoniazid regimen could be shown to be non-inferior to the isoniazid regimen for the registered primary endpoint, while the registry also reports several secondary endpoints under superiority hypotheses.
Population
Participants enrolled in a phase 3 tuberculosis-prevention trial involving the conditions tuberculosis and HIV infections. The ClinicalTrials.gov record does not provide a more detailed baseline population description.
Intervention
Rifapentine (RPT) plus isoniazid (INH), with pyridoxine (Vitamin B6) listed as a dietary supplement.
Comparator
Isoniazid (INH) regimen.
Primary question
Is the incidence rate for the composite tuberculosis/death endpoint sufficiently close to the comparator rate that the RPT-plus-INH regimen satisfies the prespecified non-inferiority criterion?
3. Trial Design
RPT Plus INH Regimen
- Rifapentine (RPT)
- Isoniazid (INH)
- Pyridoxine (Vitamin B6)
INH Regimen
- Isoniazid (INH)
- Pyridoxine (Vitamin B6) is listed among the trial interventions
The ClinicalTrials.gov record identifies the study as randomized, parallel-group, and unmasked. It does not report a factorial design, crossover procedure, or treatment switching. Those features therefore are not incorporated into the statistical interpretation.
4. Enrollment, Timing, and Analysis Populations
| Characteristic | Registry information |
|---|---|
| Enrollment | 3000.0 |
| Start date | 2012-05-23 |
| Primary completion | 2017-11-14 |
| Primary efficacy analysis population | All participants who started study treatment |
| Secondary safety analysis population | All participants who started study treatment |
The distinction between the enrollment figure and the efficacy analysis population is important. The primary analysis is explicitly defined as including all participants who started study treatment. The ClinicalTrials.gov record does not provide a separate intention-to-treat count, per-protocol count, or modified intention-to-treat count.
5. Primary Endpoint
| Endpoint | Registry definition / time frame | Endpoint type | Analysis |
|---|---|---|---|
| Incidence of First Diagnosis of Active Tuberculosis, Death Related to Tuberculosis, or Death From Unknown Cause | From entry to occurrence of event, up to end of follow-up 3 years after last participant enrolled (median follow-up time: 3.3 years) | Count / rate | Cochran-Mantel-Haenszel test |
The registry defines the endpoint as an incidence rate measured in events per 100 person-years. The registry-reported definition states that the incidence rate was estimated and that a 95.1% confidence interval was used to account for interim analysis of the primary efficacy outcome.
6. Primary Result: Tuberculosis or Specified Death Endpoint
Incidence rate difference
95.1% CI: -0.346 to 0.300 · two-sided
Effect measure: Arm A incidence rate − Arm B incidence rate
The reported estimate is the incidence rate in the RPT-plus-INH arm minus the incidence rate in the INH arm. Because the estimate is negative, the observed standardized incidence rate was lower in Arm A under the direction specified by the registry analysis notes.
| Primary analysis feature | Reported value |
|---|---|
| Analysis population | All participants who started study treatment |
| Groups compared | RPT Plus INH Regimen (Arm A) vs INH Regimen (Arm B) |
| Method | Cochran-Mantel-Haenszel test |
| Effect measure | Incidence Rate Difference |
| Estimate | -0.0231 |
| Confidence interval | 95.1% CI -0.346 to 0.300 |
| Hypothesis | Non-inferiority |
| Non-inferiority margin | 1.25 events per 100 person-years |
Clinical Biostats interpretation
The incidence rate difference of -0.0231 events per 100 person-years means that the estimated incidence rate in Arm A minus the estimated incidence rate in Arm B was -0.0231 events per 100 person-years. The registry explicitly defines a negative estimate as favoring Arm A.
It does not mean that the probability of tuberculosis or death was reduced by 0.0231, nor does it mean that 0.0231% of participants were prevented from experiencing the endpoint. The measure is a difference in incidence rates expressed per 100 person-years.
The 95.1% confidence interval extends from -0.346 to 0.300 events per 100 person-years. This interval describes statistical uncertainty around the estimated incidence-rate difference. It includes zero, so the interval is compatible with a small rate difference in either direction under an ordinary difference-in-rates interpretation.
For a non-inferiority trial, however, the relevant question is not simply whether the interval excludes zero. The key comparison is whether the unfavorable side of the interval crosses the prespecified non-inferiority margin.
The registry specifies a non-inferiority margin of 1.25 events per 100 person-years. The upper confidence limit of 0.300 is below that margin. Thus, using the reported estimate and confidence interval together with the registry's stated non-inferiority framework, the reported interval is consistent with satisfying the prespecified non-inferiority criterion.
The registry also states that sample-size determination assumed a primary endpoint rate of 2.0/100 person-years, used a one-sided 0.025 alpha level, and targeted at least 90% power. The resulting required sample size was approximately 2500.
7. Secondary Endpoint Results
The registry contains five secondary statistical analyses in addition to the primary analysis. These address serious adverse events, targeted adverse events, toxicity-related drug management, non-TB deaths, and deaths from any cause.
Serious Adverse Events
Risk difference for any serious adverse event
95% CI: -0.035 to 0.002 · P = 0.073
Fisher exact test; superiority hypothesis
| Arm | Participants with serious adverse events | Participants at risk |
|---|---|---|
| RPT Plus INH Regimen (Arm A) | 40 | 1496 |
| INH Regimen (Arm B) | 68 | 1504 |
The reported risk difference is defined as the proportion in Arm A minus the proportion in Arm B. The estimate of -0.016 therefore describes a lower observed proportion with an SAE in Arm A under that direction convention. The two-sided 95% confidence interval ranges from -0.035 to 0.002, and the reported superiority p-value is 0.073.
Targeted Adverse Events
Risk difference for any targeted adverse event
95% CI: -0.019 to 0.007 · P = 0.405
Fisher exact test; superiority hypothesis
The registry defines the estimate as the proportion of participants with a targeted adverse event in Arm A minus the corresponding proportion in Arm B. The confidence interval crosses zero, and the reported two-sided p-value is 0.405.
Toxicity-Related Study Drug Management
Proportional-odds analysis
95% CI: 1.315 to 3.332 · two-sided
Proportional odds (ordinal) regression; superiority hypothesis
The endpoint records the number of participants in each category of an ordered categorical variable indicating the most stringent level of study-drug management due to toxicity required during treatment. The registry describes the analysis as a proportional-odds model with covariate adjustment.
The analysis note states that the odds ratio is expressed as the odds of being in a higher category of toxicity-related management for Arm B compared with Arm A. Under that reported direction, an odds ratio of 2.093 indicates higher modeled odds of being in a more stringent management category for Arm B relative to Arm A.
Death Due to a Non-TB Event
Fine-Gray competing-risk hazard ratio
95% CI: 0.762 to 2.559 · P = 0.2802
Fine-Gray model; two-sided superiority hypothesis
This time-to-event analysis examined cumulative incidence of death due to a non-TB event. The registry specifies a Fine-Gray competing-risk analysis, treating TB-related deaths as competing risks and other deaths, including deaths of unknown cause, as the event of interest.
The registry defines the hazard ratio as Arm B hazard divided by Arm A hazard, so an HR greater than 1 favors Arm A according to the analysis notes. The point estimate of 1.396 therefore points in that direction, but the 95% confidence interval is wide and includes 1. The reported two-sided p-value is 0.2802.
Death From Any Cause
Overall survival comparison
Log-rank test; two-sided superiority hypothesis
The registry defines this endpoint as the cumulative incidence of death from any cause, measured from entry to occurrence of the event through the stated follow-up period. The analysis used a log-rank test, with the null hypothesis that the survival curve in Arm A equals the survival curve in Arm B.
| Secondary endpoint | Method | Effect measure / result |
|---|---|---|
| Participants with one or more serious adverse events | Fisher exact test | RD -0.016; 95% CI -0.035 to 0.002; P = 0.073 |
| Participants with a targeted adverse event | Fisher exact test | RD -.0058; 95% CI -0.019 to 0.007; P = 0.405 |
| Ordered toxicity-related drug-management category | Proportional odds regression | OR 2.093; 95% CI 1.315 to 3.332 |
| Cumulative incidence of death due to a non-TB event | Fine-Gray competing-risks model | HR 1.396; 95% CI 0.762 to 2.559; P = 0.2802 |
| Cumulative incidence of death from any cause | Log-rank test | P = 0.3078 |
8. Safety Results
The ClinicalTrials.gov record provides serious adverse event counts by treatment arm. Both the count and the denominator are reported directly in the trial data.
| Safety measure | RPT Plus INH Regimen | INH Regimen |
|---|---|---|
| Participants with one or more serious adverse events | 40 / 1496 | 68 / 1504 |
| Analysis | Fisher exact test | |
| Risk difference | -0.016 (95% CI -0.035 to 0.002) | |
| P-value | 0.073 | |
The serious-adverse-event analysis asks whether the proportion of participants experiencing any SAE differed between the two randomized regimens. Fisher's exact test was used, and the registry specifies a superiority hypothesis for this endpoint.
The observed SAE counts were 40 of 1496 in Arm A and 68 of 1504 in Arm B. The reported risk difference of -0.016 is the Arm A proportion minus the Arm B proportion. The confidence interval extends from -0.035 to 0.002, so the reported uncertainty includes both a modest lower risk in Arm A and a small difference in the opposite direction.
The p-value of 0.073 is not a measure of the magnitude or clinical importance of the safety difference. It describes the compatibility of the observed data with the specified null hypothesis under the test procedure.
9. Statistical Methodology
Cochran-Mantel-Haenszel analysis
The primary analysis is reported as a Cochran-Mantel-Haenszel test. The analysis notes state that the Mantel-Haenszel method was used for estimating the standardized incidence rate in each arm and the incidence rate difference.
The registry reports the resulting estimate in events per 100 person-years. Negative values favor Arm A according to the registry-reported analysis notes.
Fisher exact test
Fisher's exact test was used for the two binary adverse-event endpoints. The method is designed for comparing categorical outcomes between two groups and is particularly useful when exact inference is desired rather than relying on a large-sample approximation.
Proportional-odds regression
The toxicity-management endpoint is ordered categorical rather than simply a two-level outcome. Proportional-odds regression uses the ordering of the categories and models the odds of being at or above progressively higher levels. The registry reports an odds ratio and identifies covariate adjustment as an analysis concept.
The analysis note gives this direction explicitly. An OR above 1 therefore corresponds to higher modeled odds of being in a more stringent toxicity-management category for Arm B.
Fine-Gray competing-risks model
For non-TB deaths, the registry specifies a Fine-Gray competing-risk analysis. This is important because a participant who experiences a competing event can no longer experience the event of interest in the same way as a participant who remains event-free.
The registry specifically treats TB-related deaths as competing risks, while other deaths, including deaths of unknown cause, are the event of interest. The reported hazard ratio is defined as Arm B hazard divided by Arm A hazard.
Log-rank test
The all-cause mortality endpoint uses the log-rank test to compare survival curves between the two randomized groups. This is a time-to-event method that incorporates the timing of events and accommodates right-censoring.
Kaplan-Meier estimation and time-to-event endpoints
Kaplan-Meier estimation is the standard descriptive framework for displaying survival over time when right-censored observations are present. The ClinicalTrials.gov record identifies death from any cause as a time-to-event endpoint and specifies a log-rank comparison, but it does not separately list Kaplan-Meier estimation as a posted statistical-analysis method for this endpoint.
10. Non-Inferiority Design
The primary endpoint is explicitly analyzed under a non-inferiority hypothesis. The registry specifies a non-inferiority margin of 1.25 events per 100 person-years.
The margin
The margin defines how much worse the RPT-plus-INH regimen could be, on the incidence-rate-difference scale, while still satisfying the trial's non-inferiority criterion.
The observed interval
The reported 95.1% confidence interval runs from -0.346 to 0.300 events per 100 person-years, with the upper limit below the 1.25-event margin.
Design assumptions
Sample-size determination assumed a primary endpoint rate of 2.0/100 person-years, a one-sided 0.025 alpha level, and at least 90% power.
Required enrollment
The registry states that these assumptions required a sample size of approximately 2500; the trial's reported enrollment was 3000.0.
Why the confidence interval is central
Non-inferiority is fundamentally about ruling out an unacceptable loss of efficacy, not necessarily about proving that the two treatments have identical effects. For an incidence-rate difference defined as Arm A minus Arm B, the unfavorable direction is a sufficiently positive difference. The prespecified margin establishes the boundary that the confidence interval must not cross under the trial's non-inferiority framework.
Here, the reported upper confidence limit is 0.300, while the non-inferiority margin is 1.25 events per 100 person-years. The upper limit therefore remains below the stated margin.
11. Interim Analysis and Confidence-Interval Level
The primary endpoint definition states that a 95.1% confidence interval was used to account for an interim analysis of the primary efficacy outcome. The registry therefore provides an important clue about the relationship between interim monitoring and the final inferential threshold.
The confidence interval level is reported by the registry as 95.1%. The ClinicalTrials.gov record does not provide the complete interim-monitoring schedule, stopping boundary, or alpha-spending function, so those details are not inferred here.
This distinction matters because a trial that permits an interim efficacy assessment cannot generally be interpreted as though the data were examined only once at the end. Adjusting the confidence level is one way a prespecified design can account for interim examination of the primary outcome.
12. Multiplicity
The trial has one registered primary endpoint and multiple secondary endpoints. The ClinicalTrials.gov record explicitly states that the proportional-odds toxicity-management analysis was not adjusted for multiple comparisons.
| Analysis family | Role | Multiplicity information in the ClinicalTrials.gov record |
|---|---|---|
| Active TB / TB-related or unknown-cause death endpoint | Primary | 95.1% CI used to account for interim analysis |
| Serious adverse events | Secondary | No multiple-comparison adjustment reported in the ClinicalTrials.gov record |
| Targeted adverse events | Secondary | No multiple-comparison adjustment reported in the ClinicalTrials.gov record |
| Toxicity-related drug management | Secondary | Analysis note explicitly says not adjusted for multiple comparisons |
| Non-TB death | Secondary | No multiple-comparison adjustment reported in the ClinicalTrials.gov record |
| All-cause death | Secondary | No multiple-comparison adjustment reported in the ClinicalTrials.gov record |
A nominal p-value from a secondary analysis should therefore not automatically be interpreted as though the trial had allocated a separate familywise error budget to that endpoint. The registry's explicit note concerning the toxicity-management analysis is especially important when interpreting its confidence interval and p-value.
13. Statistical Methods Explained
Why is the primary endpoint expressed per 100 person-years?
The primary endpoint is an incidence-rate outcome. Person-time allows participants to contribute follow-up even when their observation periods differ. Expressing the rate per 100 person-years provides a common scale for comparing the two randomized groups.
Why is the primary analysis a non-inferiority analysis?
The registry identifies the primary hypothesis as non-inferiority and provides a specific margin of 1.25 events per 100 person-years. The statistical objective is therefore to determine whether the RPT-plus-INH incidence rate is not unacceptably higher than the comparator rate according to that prespecified boundary.
Why does the confidence interval cross zero without preventing non-inferiority?
The estimate is a difference, so zero represents no rate difference. The confidence interval extends across zero, meaning the data are compatible with both a small negative and a small positive difference. Non-inferiority uses a different boundary: the prespecified unfavorable margin of 1.25 events per 100 person-years. The entire reported interval remains below that margin.
What does the odds ratio of 2.093 mean?
For the ordered toxicity-management endpoint, the registry defines the odds ratio as the odds of being in a higher category for Arm B compared with Arm A. An OR of 2.093 therefore represents higher modeled odds of being in a more stringent category for Arm B under that definition. It is not a risk ratio and should not be read as saying that the probability of an event was 2.093 times higher.
Why was Fisher's exact test used for adverse events?
The two adverse-event endpoints are binary comparisons between treatment groups. Fisher's exact test provides an exact test of the association between treatment assignment and the binary outcome rather than relying on a large-sample approximation.
Why is a Fine-Gray model used for non-TB death?
Non-TB death is analyzed in the presence of competing risks. A TB-related death changes the participant's ability to experience the non-TB death endpoint. The Fine-Gray framework directly addresses the cumulative-incidence setting specified in the registry analysis.
Why does a p-value not measure effect size?
A p-value describes how compatible the observed data are with a specified null hypothesis under the statistical test. It does not quantify how large or clinically important an effect is. The effect estimate and its confidence interval are needed to understand magnitude and precision.
14. Understanding the Primary Estimate
The incidence-rate difference of -0.0231 events per 100 person-years is a standardized difference between the two randomized groups. The negative sign indicates that the estimated rate was lower in Arm A under the registry's stated direction convention.
The 95.1% confidence interval of -0.346 to 0.300 events per 100 person-years shows that the point estimate is not known exactly. The width of the interval reflects uncertainty in estimating the underlying difference from the trial data.
The relevant comparison is between the upper confidence limit, 0.300, and the non-inferiority margin, 1.25 events per 100 person-years. Because the upper limit is below the margin, the reported result is consistent with the registry's non-inferiority framework.
The result does not establish that the two regimens have identical risks, does not provide an individual patient's probability of developing tuberculosis, and does not convert the incidence-rate difference into a percentage reduction in risk.
15. Interpreting the Secondary Time-to-Event Analyses
Fine-Gray hazard ratio
The non-TB death analysis reports an HR of 1.396, with a 95% CI of 0.762 to 2.559 and P = 0.2802. Because the registry defines the ratio as Arm B hazard divided by Arm A hazard, values above 1 favor Arm A according to the registry-reported analysis convention.
The confidence interval is broad relative to the point estimate and crosses 1. The p-value is 0.2802. These quantities should be considered together rather than treating the point estimate alone as a definitive description of the treatment difference.
Log-rank comparison of all-cause death
The all-cause death endpoint was analyzed using the log-rank test, with the null hypothesis that the survival curve in Arm A equals the survival curve in Arm B. The reported p-value was 0.3078.
16. Covariate Adjustment and Stratification
The ClinicalTrials.gov record identifies covariate adjustment as an analysis concept associated with the proportional-odds regression for toxicity-related drug management. It does not provide the covariates or their parameter estimates.
The primary analysis is described as a Mantel-Haenszel analysis used to estimate standardized incidence rates and their difference. The ClinicalTrials.gov record does not identify specific stratification variables. Consequently, no stratification factors are asserted for ACTG A5279 beyond the standardized-analysis description provided by the registry.
17. Censoring and Time-to-Event Interpretation
Several endpoints are defined from entry to the occurrence of an event during follow-up. Time-to-event analyses differ from simple binary analyses because both the occurrence and timing of events contribute information, and participants who have not experienced the event by the end of observation can contribute censored follow-up.
All-cause death
Analyzed with a log-rank test comparing the survival curves between Arm A and Arm B.
Non-TB death
Analyzed with a Fine-Gray competing-risks model because TB-related deaths are treated as competing risks.
Primary endpoint
Reported as an incidence rate in events per 100 person-years rather than as a median event time.
Follow-up
The registered primary endpoint is followed through 3 years after the last participant was enrolled.
The ClinicalTrials.gov record does not specify a particular censoring rule, missing-data imputation method, or sensitivity analysis for censoring. These topics are therefore not assigned a trial-specific method beyond the endpoint and analysis descriptions actually reported.
18. Safety and Efficacy Use Different Statistical Questions
One useful feature of ACTG A5279 as a statistical teaching example is the contrast between its primary non-inferiority analysis and its secondary superiority analyses.
| Question | Endpoint | Effect / test | Hypothesis |
|---|---|---|---|
| Is the incidence rate acceptably close to the comparator? | Active TB / specified death endpoint | Incidence rate difference | Non-inferiority |
| Do SAE proportions differ? | Any serious adverse event | Risk difference; Fisher exact | Superiority |
| Do targeted AE proportions differ? | Any targeted adverse event | Risk difference; Fisher exact | Superiority |
| Do toxicity-management categories differ? | Ordered toxicity-management variable | Odds ratio; proportional odds regression | Superiority |
| Do non-TB death rates differ in competing-risk analysis? | Non-TB death | Hazard ratio; Fine-Gray model | Superiority |
| Do all-cause survival curves differ? | Death from any cause | Log-rank p-value | Superiority |
These are not interchangeable questions. A non-inferiority incidence-rate analysis, a binary risk-difference analysis, an ordinal regression, and competing-risk survival analysis each target a different statistical estimand.
19. Limitations
- Registry-level reporting: the ClinicalTrials.gov record contains six statistical analyses but does not provide every underlying event count, rate, survival estimate, or model coefficient.
- Incomplete follow-up descriptor: the registered time-frame text reported here ends after “median follow-up time” and therefore does not provide a complete median follow-up value.
- No median survival values: the ClinicalTrials.gov record reports a log-rank p-value for all-cause death but does not report median survival.
- Non-inferiority interpretation depends on the prespecified margin: the primary result is meaningful only in relation to the stated 1.25 events per 100 person-years margin.
- Interim-analysis adjustment: the primary endpoint uses a 95.1% confidence interval specifically to account for interim analysis, so it should not be silently replaced by an ordinary 95% interval.
- Secondary multiplicity: the toxicity-management analysis explicitly states that it was not adjusted for multiple comparisons.
- Competing risks: the non-TB death endpoint cannot be interpreted as an ordinary survival endpoint because TB-related deaths are treated as competing risks.
- Direction conventions differ: the primary incidence-rate difference is Arm A minus Arm B, whereas the Fine-Gray hazard ratio is defined as Arm B hazard divided by Arm A hazard. The direction must be checked before comparing numerical effect measures.
- Limited covariate information: the ClinicalTrials.gov record identifies covariate adjustment for the proportional-odds model but does not specify the adjusted covariates.
- No imputation method reported: the ClinicalTrials.gov record does not identify a missing-data or imputation procedure.
20. Why This Trial Matters Statistically
ACTG A5279 is a useful statistical case study because it places several distinct clinical-trial methods within the same randomized comparison. The primary question is non-inferiority on an incidence-rate scale, while secondary analyses move across binary outcomes, ordinal regression, competing risks, and conventional time-to-event comparison.
| Concept | How it appears in ACTG A5279 |
|---|---|
| Randomization | Randomized, parallel-group phase 3 design |
| Non-inferiority | Primary hypothesis with a margin of 1.25 events per 100 person-years |
| Incidence rates | Primary endpoint expressed as events per 100 person-years |
| Cochran-Mantel-Haenszel | Primary analysis method for standardized incidence rate and incidence rate difference |
| Confidence intervals | 95.1% CI for the primary efficacy outcome and 95% CIs for secondary effect estimates |
| Fisher exact test | Binary serious-adverse-event and targeted-adverse-event comparisons |
| Risk difference | Secondary binary safety effect measure |
| Proportional odds regression | Ordered toxicity-related drug-management outcome |
| Fine-Gray model | Non-TB death with TB-related deaths as competing risks |
| Log-rank test | All-cause death time-to-event comparison |
| Interim analysis | 95.1% CI used for the primary efficacy outcome to account for interim analysis |
| Multiplicity | Toxicity-management analysis explicitly reported as not adjusted for multiple comparisons |
21. A Practical Reading Strategy for This Trial
A statistically disciplined reading of ACTG A5279 starts with the estimand rather than the p-value.
- Identify the endpoint. The primary outcome is an incidence-rate endpoint combining first active tuberculosis diagnosis with specified deaths.
- Identify the effect measure. The primary comparison is an incidence-rate difference in events per 100 person-years.
- Check the direction. The estimate is Arm A minus Arm B, with a negative value favoring Arm A.
- Find the non-inferiority margin. The prespecified margin is 1.25 events per 100 person-years.
- Read the confidence interval against the margin. The upper limit is 0.300, below the 1.25 margin.
- Separate secondary endpoints. Their hypotheses are labeled superiority and use different estimands and methods.
- Account for competing risks. The non-TB death analysis specifically treats TB-related deaths as competing events.
- Check multiplicity. At least one secondary analysis is explicitly reported without adjustment for multiple comparisons.
22. What the P-Values Do — and Do Not — Mean
Primary endpoint
The registry-reported primary result is framed as non-inferiority, so the central inferential comparison is the confidence interval with the 1.25 events-per-100-person-years margin rather than a conventional superiority p-value.
Serious adverse events
P = 0.073 describes the Fisher-exact test under the stated equality null hypothesis. It does not measure the size of the SAE difference.
Targeted adverse events
P = 0.405 is the reported two-sided Fisher-exact result. It does not imply that the two proportions are mathematically identical.
Non-TB death
P = 0.2802 accompanies the Fine-Gray hazard-ratio analysis. It does not describe the size of the competing-risk effect by itself.
The same principle applies across all endpoints: a p-value is evidence relative to a null hypothesis and statistical model. It is not a universal measure of treatment effect, clinical importance, or precision.
23. Overall Statistical Interpretation
The primary incidence-rate difference was -0.0231 events per 100 person-years, with a 95.1% CI of -0.346 to 0.300. Because the upper confidence limit of 0.300 is below the prespecified non-inferiority margin of 1.25 events per 100 person-years, the reported result is consistent with the trial's stated non-inferiority criterion.
The reported SAE risk difference was -0.016, with a 95% CI of -0.035 to 0.002 and P = 0.073. The targeted-adverse-event risk difference was -.0058, with a 95% CI of -0.019 to 0.007 and P = 0.405.
The proportional-odds analysis reported an OR of 2.093 with a 95% CI of 1.315 to 3.332, using the registry's convention of Arm B relative to Arm A for higher toxicity-management categories. The analysis note states that it was not adjusted for multiple comparisons.
The Fine-Gray analysis of non-TB death reported HR 1.396, 95% CI 0.762 to 2.559, P = 0.2802. The log-rank analysis of all-cause death reported P = 0.3078. These endpoints address different time-to-event questions and should not be collapsed into a single effect measure.
24. Related Tutorials
Learn more about the methods used in this trial:
25. Related Statistical Calculators
Explore calculators aligned with the main estimands and methods in this trial:
26. Sources
- ClinicalTrials.gov: ACTG A5279 (NCT01404312), the official registry record used as the source for the trial data presented on this page.
- PubMed: PMID 35943252.
- PubMed: PMID 32815870.
- PubMed: PMID 31414121.
- PubMed: PMID 30865794.
- PubMed: PMID 26082504.
The numerical results and trial-design facts on this page are restricted to the ClinicalTrials.gov record. The PubMed records are provided as source links identified in that trial data; no additional numerical results from those publications have been incorporated.
Continue through the Clinical Biostats trial-analysis library
Use the related tutorials and calculators to study the estimands, tests, confidence intervals, and survival methods illustrated by this trial.
27. Record Summary
ACTG A5279 provides a compact but methodologically diverse example of randomized clinical-trial statistics. Its primary endpoint uses an incidence-rate difference and a prespecified non-inferiority margin, with a 95.1% confidence interval accounting for interim analysis. Secondary endpoints then illustrate Fisher's exact testing and risk differences for binary safety outcomes, proportional-odds regression for an ordered toxicity-management outcome, Fine-Gray competing-risk analysis for non-TB death, and a log-rank test for all-cause death.
The most important statistical distinction is between non-inferiority and superiority. The primary result is interpreted against a 1.25 events-per-100-person-years margin, whereas the secondary analyses are framed under superiority hypotheses. Reading the effect measure, direction convention, confidence interval, hypothesis type, and analysis population together provides a more informative interpretation than focusing on p-values alone.