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Multidrug-Resistant TB Phase 3 Completed NCT03896685

endTB-Q: Complete Statistical Analysis of Bedaquiline, Delamanid, Clofazimine and Linezolid in Multidrug-Resistant Tuberculosis

An independent statistical review of the randomized phase 3 endTB-Q trial evaluating newly approved drugs in combination regimens for multidrug-resistant tuberculosis with fluoroquinolone resistance.

NCT03896685  ·  Phase 3  ·  323 participants  ·  Completed
ClinicalTrials.gov record

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

1. Trial at a Glance

endTB-Q was a randomized, parallel, open-label phase 3 treatment trial enrolling 323 participants with multidrug-resistant tuberculosis and related tuberculosis conditions. The registry identifies two treatment arms and a primary efficacy endpoint based on the proportion of participants with a favorable outcome at Week 73 after randomization.

323
Enrollment
Randomized trial
2
Arms
Parallel design
3
Phase
Phase 3
73
Primary time point
Week 73 after randomization
FeatureendTB-Q
Trial acronymendTB-Q
ClinicalTrials.gov identifierNCT03896685
PhasePhase 3
StatusCompleted
AllocationRandomized
Design modelParallel
MaskingNone
Primary purposeTreatment
Enrollment323
Number of arms2
Start date2020-04-06
Primary completion date2024-10-04
Lead sponsorMédecins Sans Frontières, France

2. Clinical Question

The trial evaluates treatment regimens for multidrug-resistant tuberculosis, with the registry title specifically describing multidrug-resistant TB with fluoroquinolone resistance. The primary statistical question is whether the randomized treatment groups differ in the proportion of participants with a favorable outcome at Week 73 after randomization.

Population

The registered conditions include tuberculosis, multidrug-resistant tuberculosis, pulmonary tuberculosis, mycobacterial infections, bacterial infections, and gram-positive bacterial infections.

Intervention

Bedaquiline 100 MG, delamanid 50 MG oral tablet, clofazimine 100 MG oral capsule, and linezolid 600Mg Tab.

Comparator

Control arm MDR-TB regimen, designed according to latest WHO guidelines.

Primary question

What proportion of participants in each randomized treatment group has a favorable outcome at Week 73 after randomization?

3. Trial Design

01
Randomize323 participants
02
Two armsParallel treatment groups
03
Open-labelNo masking
04
Follow-upOutcome assessment through Week 73
05
Primary endpointFavorable outcome at Week 73
Allocation
Randomized
Participants were assigned to one of two parallel treatment arms.
Masking
None
The registered design is open-label rather than blinded.
Purpose
Treatment
The primary purpose recorded in the registry is treatment.
Enrollment
323 participants
The registry records 323 participants for the study.
INTERVENTION ARM

Newly approved drug combination

  • Bedaquiline 100 MG
  • Delamanid 50 MG oral tablet
  • Clofazimine 100 MG oral capsule
  • Linezolid 600Mg Tab
CONTROL ARM

MDR-TB regimen

  • Control arm MDR-TB regimen
  • Regimen designed according to latest WHO guidelines

The statistical structure is therefore a straightforward two-group randomized comparison at a prespecified follow-up time. The absence of masking is an important design feature because the primary endpoint incorporates bacteriological, radiological, and clinical evolution in addition to culture results.

4. Endpoints

EndpointRegistry definitionTime frame
Week 73 Efficacy Proportion of participants with favorable outcome at Week 73 Week 73 after randomization

Definition of a favorable outcome

The registry defines a participant's outcome as favorable at Week 73 if the outcome is not classified as unfavorable, and one of the specified favorable conditions is met.

Favorable-outcome pathwayRegistry definition
Pathway 1 The last two culture results are negative. These two cultures must be taken from sputum samples collected on separate visits, with the latest between Week 65 and Week 73.
Pathway 2 The last culture result from a sputum sample collected between Week 65 and Week 73 is negative, and either there is no other post-baseline culture result or the penultimate culture result is positive due to laboratory cross contamination; additionally, bacteriological, radiological and clinical evolution is favorable.
Pathway 3 There is no culture result from a sputum sample collected between Week 65 and Week 73, or the result of that culture is positive due to laboratory cross contamination; the most recent culture result is negative; and bacteriological, radiological and clinical evolution is favorable.

This endpoint is more informative than a simple culture-positive versus culture-negative comparison because the favorable classification integrates culture information with bacteriological, radiological, and clinical evolution. The statistical analysis therefore concerns a composite clinical classification, even though several of its components are microbiological.

5. Statistical Methodology

The registry identifies one primary endpoint: the proportion of participants with favorable outcome at Week 73 after randomization. No posted statistical analyses are listed in the ClinicalTrials.gov record.

Binary endpoint structure

The primary endpoint is binary at the participant level: at Week 73, each participant's outcome is classified as favorable or not favorable according to the registered definition. The primary descriptive quantity is therefore a proportion within each randomized treatment group.

Basic estimand structure
p1 = favorable participants in intervention arm / all participants evaluated in intervention arm
p0 = favorable participants in control arm / all participants evaluated in control arm

A between-group analysis would compare the probability of a favorable Week 73 outcome under the two randomized treatment assignments.

Measures of treatment effect

For a binary endpoint such as this one, several effect measures can be informative. The risk difference expresses the absolute difference in favorable-outcome proportions, while the risk ratio compares the proportions multiplicatively. An odds ratio compares the odds of a favorable outcome between groups.

MeasureConceptInterpretation
Risk difference p1 − p0 Absolute difference in the probability of a favorable Week 73 outcome.
Risk ratio p1 / p0 Relative probability of a favorable outcome in the intervention arm versus the control arm.
Odds ratio [p1/(1−p1)] / [p0/(1−p0)] Relative odds of a favorable outcome between the randomized groups.

The choice among these measures depends on the prespecified statistical analysis plan. The registry information available here identifies the endpoint but does not specify which effect measure, confidence-interval method, or hypothesis test was used.

Confidence intervals

A confidence interval around a treatment-effect estimate quantifies statistical uncertainty associated with the estimated difference, ratio, or odds ratio. For a binary endpoint, the interval should be constructed using a method appropriate to the endpoint and analysis population.

Why uncertainty matters

A point estimate alone describes the observed treatment-group contrast but does not show how precisely that contrast has been estimated. A confidence interval adds that information. Narrower intervals generally indicate greater statistical precision, while wider intervals indicate greater uncertainty.

Hypothesis testing

A conventional two-group analysis of a binary endpoint would test a null hypothesis corresponding to no difference between treatment groups, depending on the prespecified effect measure. A p-value from such a test would address compatibility with the null hypothesis; it would not itself describe the magnitude or clinical importance of the treatment effect.

6. Planned Analysis

The registry says the primary efficacy outcome will be measured as the proportion of participants with favorable outcome at Week 73 after randomization. Because this is a binary endpoint, a typical analysis would summarize the favorable-outcome proportion in each randomized arm and estimate a between-arm treatment effect with a corresponding confidence interval.

Primary descriptive analysis

Calculate the proportion of participants classified as having a favorable outcome at Week 73 in each treatment group.

Between-group comparison

Compare the two proportions using a prespecified binary-outcome method and report an appropriate treatment-effect estimate with uncertainty.

Analysis population

The choice of participants included in the primary analysis should follow the prespecified statistical analysis plan, particularly for participants without a Week 73 culture result or complete clinical information.

Endpoint timing

The primary assessment is fixed at Week 73 after randomization, with the favorable-outcome definition incorporating information from specified culture windows extending through Week 73.

Registry reporting status: no formal statistical analyses were posted to ClinicalTrials.gov for the primary endpoint in the record described here. Consequently, the registry information identifies the endpoint and its definition but does not provide an effect estimate, confidence interval, p-value, or arm-specific favorable-outcome result.

7. Statistical Methods Explained

What makes the Week 73 endpoint a binary outcome?

Although the favorable-outcome definition contains several clinical and microbiological components, the final Week 73 classification has two possible states for statistical analysis: favorable or not favorable. That converts the endpoint into a binary participant-level outcome.

Why use a proportion for the primary endpoint?

The endpoint asks for the proportion of participants who meet the favorable-outcome definition at a specific time point. The proportion therefore directly describes the frequency of the desired outcome within each treatment arm.

Why might risk difference be useful?

Risk difference is directly interpretable on the probability scale. If two treatment groups had favorable-outcome proportions of p1 and p0, the risk difference would be p1 − p0. It answers how much the observed probability differs in absolute terms.

Why might risk ratio be useful?

Risk ratio places the two probabilities on a relative scale. A value above 1 would indicate a higher probability of a favorable outcome in the intervention group, while a value below 1 would indicate a lower probability, assuming the intervention group is placed in the numerator.

Why does the endpoint definition matter statistically?

The favorable classification is not determined solely by one culture result. It depends on specified culture timing, the possibility of laboratory cross contamination, and favorable bacteriological, radiological, and clinical evolution. Changing any of those classification rules could change the resulting proportion, so the endpoint definition is part of the statistical estimand rather than merely a clinical footnote.

Why is missing Week 73 information important?

A participant without sufficient information to establish the registered favorable-outcome criteria creates an analysis-population question. Whether such participants are classified as unfavorable, excluded from a particular analysis, or handled through another prespecified strategy can affect the estimated treatment effect. The appropriate rule should come from the statistical analysis plan rather than being chosen after observing the results.

Why is randomization important for this comparison?

Randomization creates the basis for comparing outcomes between treatment assignments without relying on observational adjustment for every possible prognostic factor. It does not guarantee identical groups in every characteristic, but it provides the core design framework for causal comparison between the randomized strategies.

8. Interpretation of the Primary Endpoint

What the endpoint would mean

The primary endpoint is the probability that a randomized participant meets the registered definition of a favorable outcome at Week 73. It is therefore a fixed-time treatment outcome, rather than a time-to-event endpoint such as overall survival.

What a treatment effect would mean

A positive between-arm difference in favorable-outcome proportions would indicate that the intervention group had a higher observed probability of satisfying the Week 73 favorable-outcome definition. It would not mean that every component of the composite definition improved by the same amount.

What a p-value would not mean

If a formal hypothesis test were reported, its p-value would quantify evidence against the specified null hypothesis under the statistical model and testing procedure. It would not measure the size of the treatment effect, the probability that the treatment works, or the probability that the null hypothesis is true.

Why the confidence interval matters

A confidence interval around a treatment-effect estimate would show the statistical precision of the estimated difference or ratio. It should be interpreted together with the point estimate and the clinical meaning of the Week 73 endpoint rather than as a substitute for either.

9. Endpoint Timing and Censoring Considerations

The primary endpoint differs from a conventional time-to-event endpoint because the registered outcome is evaluated at a specified follow-up point: Week 73 after randomization. The definition nevertheless uses longitudinal information, including cultures collected between Week 65 and Week 73 and the most recent culture result in specified circumstances.

Timing componentStatistical relevance
Randomization Defines the starting point for the primary endpoint's time frame.
Week 65 to Week 73 Defines the principal late culture window used in two of the favorable-outcome pathways.
Week 73 Defines the primary efficacy assessment point.
Separate sputum visits The first favorable pathway requires the last two negative cultures to come from sputum samples collected on separate visits.
Laboratory cross contamination The favorable definition explicitly addresses culture results classified as positive due to laboratory cross contamination.

This structure illustrates why the endpoint cannot be reduced to a single culture result at one visit. The statistical classification depends on a sequence of observations and prespecified clinical and microbiological conditions.

10. Open-Label Design and Endpoint Assessment

The registry records no masking. In an open-label randomized trial, participants and study personnel know the assigned treatment. That design feature is particularly relevant when an endpoint incorporates radiological and clinical evolution, because some components of the classification may involve assessment rather than being determined solely by an automated laboratory measurement.

Strength of randomization

Random allocation remains the central mechanism for comparing treatment strategies and helps establish a causal framework for the randomized comparison.

Assessment considerations

Because masking is absent and the favorable endpoint incorporates clinical and radiological evolution, assessment procedures are relevant to interpretation.

Microbiological component

Culture results provide objective components of the endpoint, including explicit rules for negative cultures and laboratory cross contamination.

Composite classification

The final favorable classification integrates several conditions rather than representing a single isolated measurement.

11. Missing Data and Endpoint Classification

The registered definition explicitly addresses situations in which there is no culture result from a sputum sample collected between Week 65 and Week 73. It also specifies circumstances in which a culture result is considered positive because of laboratory cross contamination.

These provisions are statistically important because missingness and measurement-quality issues can otherwise create ambiguity in a binary endpoint. By defining specific circumstances under which a favorable outcome can still be established, the endpoint attempts to specify how available longitudinal information contributes to the Week 73 classification.

Analysis-plan distinction: the registry endpoint definition describes how a favorable outcome is classified, but the available registry information does not specify a separate missing-data imputation model, multiple-imputation procedure, or sensitivity-analysis strategy. Those are distinct statistical decisions and should not be inferred from the endpoint definition alone.

12. Limitations

13. Why This Trial Matters Statistically

endTB-Q is a useful statistical teaching case because its primary endpoint illustrates a common but easily misunderstood type of clinical-trial outcome: a fixed-time binary classification built from multiple longitudinal clinical and microbiological observations.

ConceptHow it appears in endTB-Q
Randomization Participants were randomized to one of two parallel treatment arms.
Binary endpoint The primary outcome classifies participants as having a favorable outcome or not at Week 73.
Fixed follow-up time The primary assessment occurs at Week 73 after randomization.
Composite clinical definition Favorable status can depend on culture results together with bacteriological, radiological and clinical evolution.
Longitudinal information The endpoint incorporates culture results from defined periods and, in one pathway, requires negative cultures from separate visits.
Measurement quality The endpoint explicitly addresses positive culture results attributed to laboratory cross contamination.
Open-label design The registry records no masking.
Treatment comparison The intervention combines bedaquiline, delamanid, clofazimine and linezolid; the control is an MDR-TB regimen designed according to latest WHO guidelines.

14. Statistical Questions for Readers

What is the estimand?

The primary outcome concerns the proportion of randomized participants who meet the favorable-outcome definition at Week 73 after randomization.

What is being compared?

The randomized treatment strategies are compared through their Week 73 favorable-outcome proportions.

What is the key scale?

The endpoint is naturally expressed as a proportion, with risk difference and risk ratio among the possible measures of treatment effect.

Where can bias enter?

The absence of masking is particularly relevant because clinical and radiological evolution contributes to the endpoint classification.

15. Trial Timeline

2020-04-06

Trial start

The registered study start date is April 6, 2020.

Phase 3

Randomized treatment comparison

The study is registered as a phase 3, randomized, parallel, open-label treatment trial with two arms and an enrollment of 323 participants.

Week 73 after randomization

Primary efficacy assessment

The primary endpoint is the proportion of participants with favorable outcome at Week 73 after randomization.

2024-10-04

Primary completion

The registered primary completion date is October 4, 2024.

16. Sources

Continue through the Clinical Biostats knowledge graph

Clinical-trial endpoints become easier to interpret when their definitions are connected to the underlying statistical concepts: proportions, treatment effects, confidence intervals, randomization, and analysis populations.

17. Record Summary

endTB-Q is a randomized phase 3, parallel, open-label treatment trial with 323 participants and two treatment arms. Its primary endpoint is the proportion of participants with favorable outcome at Week 73 after randomization, with a detailed definition based on culture results, culture timing, laboratory cross contamination, and favorable bacteriological, radiological and clinical evolution.

From a statistical perspective, the endpoint is a fixed-time binary outcome embedded within a longitudinal clinical assessment. The most natural summary is therefore an arm-specific favorable-outcome proportion followed by a prespecified between-group treatment-effect measure and confidence interval. The absence of posted statistical analyses in the ClinicalTrials.gov record means that the registry identifies the outcome and its classification rules but does not provide the corresponding numerical treatment effect or formal hypothesis test.

Clinical Biostats interpretation: The central statistical lesson from endTB-Q is that an apparently simple proportion can represent a sophisticated clinical estimand. Before comparing two percentages, the analyst must understand exactly how each participant is classified, which observations determine that classification, when those observations are collected, and which analysis population and statistical method are specified in the analysis plan.