This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. Numerical trial results on this page are restricted to the ClinicalTrials.gov record.
1. Trial at a Glance
IMbrave050 was a randomized, parallel-group phase 3 trial comparing atezolizumab plus bevacizumab with active surveillance as adjuvant therapy in patients with hepatocellular carcinoma at high risk of recurrence after surgical resection or ablation.
| Feature | IMbrave050 |
|---|---|
| Trial name | IMbrave050 |
| NCT ID | NCT04102098 |
| Phase | Phase 3 |
| Status | COMPLETED |
| Condition | Carcinoma, Hepatocellular |
| Population | Patients with hepatocellular carcinoma at high risk of recurrence after surgical resection or ablation |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | None |
| Primary purpose | Treatment |
| Enrollment | 668.0 |
| Intervention | Atezolizumab plus bevacizumab |
| Comparator | Active surveillance |
| Primary endpoint | Recurrence-Free Survival (RFS), as Determined by IRF |
| Primary endpoint type | Time-to-event |
| Primary analysis method | Log-rank test |
| Effect measure | Hazard ratio |
| Hypothesis type | Superiority |
| Lead sponsor | Hoffmann-La Roche |
2. Clinical Question
The primary statistical question was whether atezolizumab plus bevacizumab, compared with active surveillance, was associated with a difference in recurrence-free survival among patients with hepatocellular carcinoma at high risk of recurrence after surgical resection or ablation.
Population
Patients with hepatocellular carcinoma at high risk of recurrence after surgical resection or ablation.
Intervention
Atezolizumab plus bevacizumab.
Comparator
Active surveillance.
Primary question
Does atezolizumab plus bevacizumab improve recurrence-free survival relative to active surveillance?
3. Trial Design
IMbrave050 used a randomized, parallel-group phase 3 design with no masking. The trial enrolled 668 patients and compared two study groups: active surveillance and atezolizumab plus bevacizumab.
Active Surveillance
- Active surveillance was the comparator arm.
- Serious adverse events were reported for 34/330 affected/at risk.
Atezolizumab Plus Bevacizumab
- Atezolizumab and bevacizumab were the registered study interventions.
- Serious adverse events were reported for 80/332 affected/at risk.
- A separate crossover group is reported with 10/81 affected/at risk for serious adverse events.
4. Trial Timeline
Trial start
The registry lists December 31, 2019 as the trial start date.
Primary completion
The registry lists October 21, 2022 as the primary completion date.
Primary endpoint time frame
The registered recurrence-free survival endpoint is measured from baseline up to approximately 33 months.
5. Primary Endpoint
| Endpoint | Registry definition | Time frame | Endpoint type |
|---|---|---|---|
| Recurrence-Free Survival (RFS), as Determined by IRF | RFS is defined as the time from randomization to the first documented occurrence of intrahepatic or extrahepatic HCC as determined by an IRF, or death from any cause (whichever occurs first). | Baseline up to approximately 33 months | Time-to-event |
This definition is important because recurrence-free survival is not simply a count of recurrent tumors. It is a time-to-event endpoint with a composite event definition: the first documented intrahepatic or extrahepatic HCC occurrence determined by an independent review function, or death from any cause, whichever occurs first.
Patients who have not experienced the defined event by their last evaluable follow-up contribute information up to that point and are handled through time-to-event methods rather than being treated as simple binary responders or nonresponders.
6. Analysis Population and Stratification
The posted primary analysis used the intention-to-treat (ITT) population. The registry defines the ITT population as all randomized patients, whether or not the patient has received the assigned study treatment.
| Analysis feature | Registry-supported description |
|---|---|
| Analysis population | ITT population: all randomized patients, whether or not the patient has received the assigned study treatment. |
| Groups compared | Arm B (Active Surveillance) vs Arm A (Atezolizumab Plus Bevacizumab) |
| Primary method | Log Rank |
| Effect measure | Hazard ratio |
| Hypothesis | Superiority |
The analysis also identifies stratified analysis as an analysis concept. The registry analysis notes specify the stratification factors as geographic region and high-risk features/curative procedure.
| Stratification factor | Categories |
|---|---|
| Geographic region | Asia Pacific excluding Japan vs. rest of world |
| High risk features / curative procedure | Ablation vs. resection with 1 high risk feature vs. resection with 2 or more high risk features |
7. Statistical Methodology
Log-rank test
The primary comparison used a log-rank test. This is a standard method for comparing two time-to-event distributions while accounting for the timing of events and the fact that some patients may be censored before experiencing the event.
Conceptually, the log-rank test compares the observed number of events in each randomized group with the number expected under a null hypothesis of no difference between the groups. The test is therefore based on the ordering and timing of events rather than simply comparing the percentage of patients who eventually experienced recurrence.
Hazard ratio
The effect measure reported for the primary endpoint was a hazard ratio. The estimate was 0.72 for Arm B, active surveillance, versus Arm A, atezolizumab plus bevacizumab.
For this trial, the reported comparison is explicitly labeled Arm B (Active Surveillance) vs Arm A (Atezolizumab Plus Bevacizumab). Thus, careful attention to the group ordering is essential when interpreting the direction of the reported HR.
Stratified survival analysis
The registry analysis text identifies stratified analysis and provides the two sets of stratification factors. Stratification allows the treatment comparison to account for these prespecified factors rather than treating the trial population as completely homogeneous with respect to them.
Intention-to-treat analysis
The ITT principle means that randomized patients remain associated with their assigned study group for the primary efficacy analysis, whether or not they actually received the assigned treatment. This preserves the treatment comparison created by randomization.
Time-to-event analysis
RFS is inherently a time-to-event outcome. The statistical analysis therefore needs to distinguish between patients who experience recurrence or death, patients who remain event-free at their last assessment, and the timing at which those observations occur. The posted analysis uses a log-rank test and hazard ratio, both designed for this type of endpoint.
8. Primary Result: Recurrence-Free Survival
The registry reports a formal statistical analysis for the primary endpoint, Recurrence-Free Survival (RFS), as Determined by IRF, over the period from baseline up to approximately 33 months.
Hazard ratio for recurrence or death
95% CI: 0.56–0.93 · P = 0.0120
Comparison: Arm B (Active Surveillance) vs Arm A (Atezolizumab Plus Bevacizumab)
| Primary endpoint | Comparison | Method | Effect estimate | 95% CI | P-value |
|---|---|---|---|---|---|
| Recurrence-Free Survival (RFS), as Determined by IRF | Active Surveillance vs Atezolizumab Plus Bevacizumab | Log-rank test | HR 0.72 | 0.56–0.93 | 0.0120 |
The reported hazard ratio of 0.72 means that, for the reported comparison of active surveillance versus atezolizumab plus bevacizumab, the estimated instantaneous rate of the defined RFS event in the numerator group was approximately 72% of that in the comparator group under the fitted time-to-event analysis. Equivalently, reversing the descriptive direction, the estimate corresponds to a hazard ratio of 1/0.72 only if one explicitly changes the group ordering; the registry's reported estimate should therefore be preserved as 0.72 rather than silently changing its direction.
The hazard ratio does not mean that 28% of patients avoided recurrence, that 28% of patients were cured, or that every patient experienced exactly a 28% reduction in recurrence risk. A hazard ratio is a relative time-to-event measure, not an absolute probability.
The 95% confidence interval of 0.56–0.93 describes uncertainty around the estimated hazard ratio under the statistical model and sampling framework. It does not describe the range of outcomes that individual patients will experience.
The P-value of 0.0120 addresses evidence against the null hypothesis under the specified testing framework. It is not a measure of the magnitude or clinical importance of the treatment effect. Effect size and uncertainty are better conveyed by the hazard ratio and its confidence interval.
Because this is a time-to-event analysis, interpretation also depends on censoring and the assumptions underlying the hazard-ratio model. The ClinicalTrials.gov record does not provide a separate assessment of proportional hazards, so the reported HR should not be interpreted as proof that the hazard ratio was constant at every time point.
9. Understanding the Direction of the Hazard Ratio
The ordering of the groups is especially important in this registry analysis. The posted analysis explicitly lists Arm B (Active Surveillance) vs Arm A (Atezolizumab Plus Bevacizumab) and reports an HR of 0.72.
Reported direction
The registry reports the hazard ratio as Active Surveillance relative to Atezolizumab Plus Bevacizumab: HR 0.72.
What HR 0.72 is not
It is not an absolute recurrence probability, a difference in recurrence percentages, or a statement that 72% of patients experienced an event.
Why ordering matters
Changing the reference group changes the numerical reciprocal of a hazard ratio. Statistical interpretation must therefore retain the reported group order.
What the CI adds
The interval 0.56–0.93 communicates the uncertainty around the reported HR and is more informative than the point estimate alone.
This is a useful general lesson in clinical-trial reporting: a hazard ratio without its group ordering is incomplete. The same numerical effect can be expressed in the opposite direction when the reference group changes.
10. Why a Log-Rank Test Was Used
RFS is a time-to-event endpoint, so a simple comparison of the proportion of patients with recurrence would discard information about when recurrence or death occurred. The log-rank test instead uses the observed event times across follow-up.
At each event time, the analysis considers how many patients remain at risk in each group and compares the observed pattern of events with the pattern expected under the null hypothesis of no treatment-group difference.
This approach is particularly appropriate when patients can have different follow-up durations. A patient who has not experienced recurrence by the end of observation is not treated as if the patient had been followed indefinitely without an event. Instead, the observation is censored at the appropriate time.
The log-rank test and the hazard ratio answer related but different statistical questions. The log-rank test provides a hypothesis test for differences between the time-to-event distributions, whereas the hazard ratio provides an estimate of the relative event rate under the fitted model.
11. Why the ITT Population Matters
The primary analysis population is explicitly defined as the ITT population: all randomized patients, whether or not they received the assigned study treatment.
Randomization is the mechanism that establishes the treatment comparison. An ITT analysis maintains that randomized comparison rather than redefining groups according to treatment actually received. This reduces the risk that post-randomization treatment decisions systematically alter the original comparison.
ITT does not mean that every patient contributes an event. Patients can remain event-free at their last follow-up and therefore contribute censored observations. The analysis still uses the available follow-up time for each randomized patient.
For RFS, the combination of ITT analysis and time-to-event methodology allows the primary comparison to retain the randomized structure while appropriately incorporating different event and censoring times.
12. Stratified Analysis
The posted analysis identifies two stratification structures:
| Stratification domain | Levels specified in the registry analysis notes |
|---|---|
| Geographic region | Asia Pacific excluding Japan vs. rest of world |
| High risk features / curative procedure | Ablation vs. resection with 1 high risk feature vs. resection with 2 or more high risk features |
Stratification is useful when important prognostic factors have been identified before the treatment comparison is made. Instead of assuming that all patients have identical underlying recurrence risk, the analysis can compare treatment groups while accounting for the prespecified strata.
13. Statistical Methods Explained
Why was a log-rank test used?
Because the primary endpoint is recurrence-free survival, an outcome defined by the time from randomization until recurrence or death. The log-rank test is designed to compare time-to-event distributions while incorporating the timing of events and censored observations.
What does a hazard ratio of 0.72 mean?
It means that, for the reported comparison of active surveillance versus atezolizumab plus bevacizumab, the estimated instantaneous event rate was 0.72 times the corresponding rate in the comparison group under the fitted analysis. It does not mean that 72% of patients had an event or that every patient experienced a 28% reduction in risk.
Why is the confidence interval important?
The 95% confidence interval of 0.56–0.93 shows the statistical uncertainty around the estimated HR. A point estimate alone cannot communicate how precisely the treatment effect was estimated.
Why doesn't the P-value measure effect size?
The P-value of 0.0120 quantifies evidence against the null hypothesis under the specified statistical testing framework. It does not tell us how large the treatment effect is. The HR describes the estimated relative effect, while the confidence interval describes its uncertainty.
Why does the analysis use ITT?
The ITT population includes all randomized patients regardless of whether they received the assigned treatment. This preserves the comparison established by randomization and avoids redefining the efficacy population after randomization.
Why does the analysis use stratification?
The registry analysis identifies geographic region and high-risk features/curative procedure as stratification factors. Stratified analysis allows the treatment comparison to account for these prespecified categories when evaluating the time-to-event endpoint.
Why is RFS analyzed as a time-to-event endpoint rather than a simple percentage?
Because the registry definition is based on the time from randomization to the first documented recurrence or death. Patients can have different follow-up times, so a time-to-event analysis preserves information about when events occur and appropriately handles patients whose event status is not observed through the full follow-up period.
14. What the Confidence Interval Says
Primary RFS estimate
95% CI: 0.56–0.93
Two-sided P = 0.0120
The confidence interval provides information that the point estimate alone cannot. The observed estimate is 0.72, but the analysis is subject to sampling uncertainty. The interval from 0.56 to 0.93 expresses that uncertainty under the specified statistical framework.
A confidence interval should not be interpreted as saying that there is a 95% probability that the true hazard ratio lies between 0.56 and 0.93. Rather, it is an interval produced by a procedure designed to have 95% coverage under repeated sampling when its assumptions hold.
The width of the interval also matters. A relatively narrow interval indicates greater precision than a very wide interval would, although precision and clinical importance remain distinct concepts.
The most complete statistical statement is not simply "HR 0.72, P = 0.0120." It is that the trial reported a hazard ratio of 0.72, with a two-sided 95% CI of 0.56–0.93, using a log-rank analysis for the primary RFS endpoint in the ITT population, with the specified stratification factors incorporated into the analysis.
15. Primary Endpoint Interpretation
The primary endpoint combines two clinically important event types into one time-to-event outcome: documented intrahepatic or extrahepatic HCC recurrence and death from any cause. The event occurring first determines the RFS event.
Recurrence component
The first documented occurrence of intrahepatic or extrahepatic HCC determined by an IRF qualifies as an RFS event.
Death component
Death from any cause is also an RFS event, whichever occurs first.
Time origin
The registry defines RFS from randomization.
Assessment horizon
The registered time frame is baseline up to approximately 33 months.
This endpoint structure means that RFS should not be interpreted as recurrence alone. A treatment-group difference in RFS can arise through differences in the occurrence of documented recurrence, death before documented recurrence, or both.
16. Safety Results
The ClinicalTrials.gov record provides serious adverse events by arm as affected patients divided by the number at risk. These figures should be reported as reported in the registry rather than converted into a different metric.
| Group | Serious adverse events | Reported affected / at risk |
|---|---|---|
| Active Surveillance | Serious adverse events | 34/330 |
| Atezolizumab + Bevacizumab | Serious adverse events | 80/332 |
| Crossover: Atezolizumab + Bevacizumab | Serious adverse events | 10/81 |
The safety and efficacy analyses also have different statistical purposes. The primary RFS analysis is explicitly based on the randomized ITT population, whereas the registry-reported serious-adverse-event data are presented as affected/at-risk counts by group. These should not be conflated into a single overall treatment-effect statistic.
17. Crossover and Its Statistical Implications
The ClinicalTrials.gov record identifies a crossover group for which serious adverse events were reported as 10/81. The ClinicalTrials.gov record does not provide the detailed crossover mechanism, timing, or an adjusted survival analysis specifically designed to estimate the effect of crossover.
From a statistical perspective, crossover is important because treatment received after randomization can complicate interpretation of an intention-to-treat comparison. The ITT comparison answers a question about the effect of being assigned to a strategy at randomization, whereas an analysis based on treatment actually received would answer a different question and can be affected by the reasons patients change treatment.
18. Superiority Hypothesis
The registry classifies the primary hypothesis as superiority. This is distinct from a non-inferiority design.
| Feature | IMbrave050 |
|---|---|
| Hypothesis type | Superiority |
| Primary endpoint | Recurrence-Free Survival (RFS), as Determined by IRF |
| Primary endpoint type | Time-to-event |
| Primary test | Log-rank test |
| Effect measure | Hazard ratio |
| Confidence interval | 95%, two-sided |
Because the ClinicalTrials.gov record identifies a superiority hypothesis, there is no non-inferiority margin to interpret here. The reported confidence interval and P-value should therefore be understood within a superiority-testing framework rather than through the logic of a prespecified non-inferiority boundary.
19. Multiplicity and Interim Analysis
The ClinicalTrials.gov record identifies one registered primary endpoint and one posted statistical analysis for that endpoint. They do not provide a multiplicity-adjustment procedure or an interim-analysis plan in the ClinicalTrials.gov record.
What is documented
One registered primary endpoint, one posted primary analysis, a log-rank method, a hazard ratio, a 95% two-sided confidence interval, and a superiority hypothesis.
What is not established here
The ClinicalTrials.gov record does not provide an alpha-spending scheme, multiplicity hierarchy, or interim-analysis boundary.
Accordingly, the reported P = 0.0120 should be described as the posted primary-analysis P-value. It should not be reinterpreted using an unreported alpha-spending or multiplicity procedure.
20. Missing Data, Censoring, and Time-to-Event Interpretation
Time-to-event analyses are designed to incorporate patients who have not experienced the event by their last available follow-up. Such observations contribute information until censoring rather than being classified simply as events or non-events.
The ClinicalTrials.gov record does not specify a detailed missing-data or imputation strategy for the RFS analysis. No particular imputation method should therefore be attributed to this trial on the basis of the ClinicalTrials.gov record.
The statistical analysis uses the timing of the event or censoring information rather than requiring every randomized patient to have a fully observed recurrence status at the end of the study.
A key assumption in conventional survival analysis is that the censoring mechanism is appropriately handled by the analysis framework. The ClinicalTrials.gov record does not provide enough information to assess that assumption empirically, so this page does not make a separate claim about the adequacy of the censoring process.
21. Proportional-Hazards Considerations
The primary effect measure is a hazard ratio. Hazard ratios are particularly useful for time-to-event comparisons, but their interpretation requires care when the relative event rates change substantially over time.
An HR of 0.72 is a summary relative measure of the event rate under the fitted time-to-event analysis. It should not automatically be interpreted as saying that the treatment reduces the event probability by exactly 28% at every follow-up time.
If hazards are not approximately proportional, a single HR can summarize a more complex time-varying pattern imperfectly. The ClinicalTrials.gov record does not report a formal proportional-hazards diagnostic or a time-varying treatment-effect analysis.
This distinction is especially important when explaining hazard ratios to readers who may otherwise interpret them as if they were ordinary risk ratios. A hazard ratio concerns the relative instantaneous event rate within the survival-analysis framework; it is not a direct statement about cumulative incidence at a particular time.
22. What This Result Does — and Does Not — Establish
It establishes a reported statistical comparison
The registry reports a formal log-rank analysis of the primary RFS endpoint, with HR 0.72, 95% CI 0.56–0.93, and P = 0.0120.
It does not establish an individual outcome
A population-level hazard ratio cannot determine whether a particular patient will experience recurrence or remain recurrence-free.
It does not equal an absolute risk reduction
The HR is a relative time-to-event measure and is not an absolute percentage-point difference in recurrence-free survival.
It does not prove a constant effect over time
The ClinicalTrials.gov record does not provide a separate proportional-hazards assessment or demonstrate that the HR is constant at every follow-up time.
23. Important Limitations and Interpretation Issues
- Endpoint complexity: RFS combines first documented intrahepatic or extrahepatic HCC recurrence and death from any cause, whichever occurs first. It should therefore not be described as recurrence alone.
- Hazard-ratio interpretation: the HR is a relative time-to-event measure and should not be translated directly into an absolute probability or individual treatment effect.
- Group ordering: the posted analysis explicitly compares Arm B (Active Surveillance) with Arm A (Atezolizumab Plus Bevacizumab). Reversing the reference group changes the numerical direction of the HR.
- Confidence interval: the 95% CI describes uncertainty around the estimated HR and does not describe the range of outcomes experienced by individual patients.
- Proportional hazards: the ClinicalTrials.gov record does not provide a formal assessment of the proportional-hazards assumption.
- Censoring: the ClinicalTrials.gov record does not provide detailed information about the censoring mechanism or a formal assessment of censoring assumptions.
- Missing-data methods: the ClinicalTrials.gov record does not specify a detailed missing-data or imputation strategy for the primary RFS analysis.
- Multiplicity: the ClinicalTrials.gov record does not provide an alpha-adjustment or multiplicity procedure beyond identifying the primary endpoint and its posted analysis.
- Interim analysis: the ClinicalTrials.gov record does not provide an interim-analysis boundary or alpha-spending scheme.
- Safety comparisons: serious adverse events are reported as affected/at-risk counts, without a formal statistical comparison in the ClinicalTrials.gov record.
- Crossover: the ClinicalTrials.gov record identifies a crossover group but do not provide enough detail to determine the effect of crossover on the primary RFS estimate.
24. Why This Trial Matters Statistically
IMbrave050 is a useful teaching case because its primary analysis brings together several core principles of modern clinical-trial biostatistics: randomization, an intention-to-treat population, a time-to-event endpoint, stratified analysis, a log-rank test, a hazard ratio, a confidence interval, and a superiority hypothesis.
| Concept | How it appears in IMbrave050 |
|---|---|
| Randomization | The trial is randomized with 668 enrolled patients. |
| Parallel design | The design model is parallel with two arms. |
| Intention-to-treat analysis | The primary analysis population includes all randomized patients, whether or not they received assigned study treatment. |
| Time-to-event endpoint | RFS is measured from randomization to recurrence or death. |
| IRF determination | HCC recurrence is determined by an IRF under the registered endpoint definition. |
| Log-rank test | The posted primary analysis uses a log-rank method. |
| Hazard ratio | The primary effect measure is HR 0.72. |
| Confidence interval | The reported 95% two-sided CI is 0.56–0.93. |
| P-value | The posted primary-analysis P-value is 0.0120. |
| Stratified analysis | Geographic region and high-risk features/curative procedure are identified as stratification factors. |
| Superiority hypothesis | The registry classifies the primary hypothesis as superiority. |
| Safety analysis | Serious adverse events are reported as affected/at-risk counts by group. |
25. Related Tutorials
Learn more about the methods used in this trial:
26. Related Calculators
27. Sources
- ClinicalTrials.gov: NCT04102098 — IMbrave050.
- PubMed: PMID 41580093.
- PubMed: PMID 37871608.
- PubMed: PMID 32352320.
Continue with Clinical Biostats statistical methods
Explore the underlying biostatistical methods through tutorials, calculators, and additional clinical-trial analyses.
28. Record Summary
IMbrave050 provides a focused example of a randomized phase 3 time-to-event analysis. The trial enrolled 668 patients and evaluated atezolizumab plus bevacizumab versus active surveillance using a primary endpoint of Recurrence-Free Survival (RFS), as Determined by IRF. The registered RFS definition begins at randomization and ends at the first documented intrahepatic or extrahepatic HCC recurrence determined by an IRF, or death from any cause, whichever occurs first.
The posted primary analysis used the ITT population, a log-rank test, and a hazard ratio, with stratification by geographic region and high-risk features/curative procedure. The reported comparison of active surveillance versus atezolizumab plus bevacizumab produced an HR of 0.72, with a 95% two-sided CI of 0.56–0.93 and a P-value of 0.0120.
The central statistical lesson is that a time-to-event result should be interpreted as a complete package: the endpoint definition, randomized analysis population, group ordering, analysis method, effect estimate, confidence interval, and P-value all matter. The hazard ratio describes a relative event-rate measure, the confidence interval describes uncertainty around that estimate, and the P-value addresses evidence against the null hypothesis under the specified testing framework. None of these quantities alone describes the outcome of an individual patient.