This page separates information contained in the ClinicalTrials.gov record from statistical interpretation. The ClinicalTrials.gov record reports that results were posted, but it does not provide formal statistical analyses for the registered primary endpoint.
1. Trial at a Glance
TIVO-1 was a randomized, parallel, phase 3 oncology trial comparing tivozanib (AV-951) with sorafenib in subjects with advanced renal cell carcinoma. The registered primary endpoint was progression-free survival, a time-to-event outcome defined from randomization until documented progression or death.
| Feature | TIVO-1 |
|---|---|
| Trial name | TIVO-1 |
| NCT ID | NCT01030783 |
| Condition | Advanced Renal Cell Carcinoma |
| Phase | Phase 3 |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | None |
| Primary purpose | Treatment |
| Enrollment | 517 |
| Interventions | Tivozanib (AV-951) and sorafenib |
| Trial status | Completed |
| Lead sponsor | AVEO Pharmaceuticals, Inc. |
| Sponsor type | Industry |
2. Clinical Question
The trial's central comparison was between tivozanib (AV-951) and sorafenib in subjects with advanced renal cell carcinoma. The registered primary endpoint was progression-free survival, making the principal statistical question a comparison of time from randomization to progression or death.
Population
Subjects with advanced renal cell carcinoma.
Intervention
Tivozanib (AV-951).
Comparator
Sorafenib.
Primary question
How does time to progression or death compare between the randomized tivozanib and sorafenib groups?
3. Trial Design
Tivozanib
- Tivozanib (AV-951)
- Randomized treatment arm
Sorafenib
- Sorafenib
- Randomized comparator arm
The design is important statistically because randomization establishes the comparison before outcomes are observed. The parallel structure means participants are assigned to one treatment strategy rather than moving through a sequence of randomized treatment conditions. Because masking was listed as none, treatment assignment was not masked in the registry's design description.
4. Trial Timeline and Registry Status
Study begins
The registered trial start was December 2009.
Primary completion
The registered primary completion date was July 2012.
Trial completed
The ClinicalTrials.gov record classifies TIVO-1 as completed and indicate that results were posted.
5. Endpoints
| Endpoint | Registry definition / time frame | Endpoint type |
|---|---|---|
| Progression-free Survival (PFS) of Subjects With Advanced Renal Cell Cancer (RCC) Randomized to Treatment With Tivozanib or Sorafenib | From date of randomization until the date of first documented progression or date of death from any cause, whichever came first. Disease progression was assessed every 8 weeks. | Time-to-event |
Registered PFS definition
The registry definition states that Progression-Free Survival (PFS) is defined as the time from randomization to first documentation of objective tumor progression (progressive disease) or death due to any reasons whichever comes first.
6. Primary Endpoint: Progression-Free Survival
The only registered primary endpoint is PFS. Because PFS records the time until the first of two possible events—objective progression or death—it is fundamentally different from a simple binary response endpoint. Each participant contributes a follow-up time, and participants who have not experienced the event by the time their usable follow-up ends may be censored under the prespecified analysis rules.
The event is whichever qualifying outcome occurs first. The statistical analysis must therefore account for both the timing of events and incomplete follow-up.
What is actually reported in the ClinicalTrials.gov record?
the ClinicalTrials.gov record states Results Posted: Yes. However, no formal statistical analyses were posted. Consequently, the ClinicalTrials.gov record does not provide a formal PFS hazard ratio, confidence interval, p-value, median PFS, event count, or other comparative efficacy estimate.
7. Planned Analysis
Because the ClinicalTrials.gov record identifies a primary time-to-event endpoint but provides no formal statistical-analysis entries, the appropriate presentation is a planned-analysis framework rather than a reconstructed result.
| Statistical component | Typical role for this endpoint | Status in the ClinicalTrials.gov record |
|---|---|---|
| Kaplan-Meier estimator | Estimate the distribution of PFS over time while accommodating right censoring. | Typical method; not reported in registry-reported statistical analyses. |
| Median PFS | Summarize the time at which the estimated survival function reaches 0.50, when estimable. | Not reported in registry-reported statistical analyses. |
| Log-rank test | Compare the time-to-event distributions between randomized treatment groups. | Typical method; not reported in registry-reported statistical analyses. |
| Cox proportional-hazards model | Estimate a relative hazard measure comparing treatment groups. | Typical model; not reported in registry-reported statistical analyses. |
| Hazard ratio and confidence interval | Quantify relative treatment effect and statistical uncertainty. | Not reported in registry-reported statistical analyses. |
This distinction is important. It would be statistically inappropriate to take the existence of a posted result record and infer a numerical treatment effect from the trial name, phase, endpoint type, or general knowledge of the study. A valid numerical result must come from an identified analysis or source containing that result.
8. How a PFS Analysis Works
Kaplan-Meier estimation
The Kaplan-Meier method is designed for situations in which not every participant experiences the event during observed follow-up. Rather than assigning a binary outcome to each participant, it estimates the probability of remaining event-free over time.
Here, di represents events at time ti, while ni represents participants at risk immediately before that time.
For TIVO-1, this framework matches the structure of the registered PFS endpoint because the endpoint is explicitly defined from randomization until progression or death. A participant who has neither event by the end of observed follow-up does not become an artificial "no-event forever" observation; instead, their information is handled through censoring according to the analysis rules.
Hazard ratios
A Cox proportional-hazards analysis can summarize the relative instantaneous event rate between two treatment groups. Conceptually, a hazard ratio below 1 would indicate a lower estimated instantaneous rate of the PFS event in the numerator treatment group relative to the reference group, while a hazard ratio above 1 would indicate a higher estimated rate.
The hazard ratio is not a probability, not a percentage of patients cured, and not a direct measure of how much longer every individual participant remains progression-free.
Confidence intervals
A confidence interval around a hazard ratio describes uncertainty in the estimated treatment effect under the model and sampling framework. A narrow interval generally indicates greater statistical precision than a wide interval, although precision and clinical importance are separate questions.
Log-rank comparison
A log-rank test compares the observed timing of events between treatment groups while accounting for the risk set at each event time. It is therefore naturally aligned with randomized trials whose primary endpoint is a time-to-event outcome.
Proportional-hazards assumption
The usual Cox hazard-ratio interpretation relies on a proportional-hazards framework: the relative hazard is treated as sufficiently stable over time for the model to provide a useful summary. If hazards vary substantially over time, a single hazard ratio can compress a more complicated pattern into one number. The registry-reported TIVO-1 data do not report whether proportional-hazards diagnostics were performed.
9. Statistical Methods Explained
Why is PFS a time-to-event endpoint?
Because the endpoint records when progression or death occurs, not simply whether it ever occurs during a fixed observation window. Two participants can both experience progression while having very different PFS times, and a third participant may remain event-free when the available follow-up ends.
Why can death be part of PFS?
The registered definition specifies progression or death, whichever comes first. This makes death an event rather than treating a participant who dies without a documented progression as if the participant remained progression-free indefinitely.
Why is randomization important?
Randomization creates the basis for comparing treatment groups without choosing treatment according to observed patient characteristics. It does not guarantee identical groups in every variable, but it establishes the intended treatment comparison at the design stage.
Why would Kaplan-Meier estimation be useful?
Kaplan-Meier estimation allows the analysis to use different follow-up durations and appropriately represent participants whose event status is not observed through the end of the study. This is one of the central reasons survival-analysis methods are used for PFS.
What would a hazard ratio mean?
A hazard ratio would describe the estimated relative instantaneous event rate between treatment groups. It would not mean that the same relative reduction applies to every participant, nor would it directly provide the absolute probability of remaining progression-free at a particular time.
Why does the p-value not measure effect size?
A p-value addresses compatibility of the observed data with a specified null hypothesis under the statistical testing framework. It does not quantify the magnitude of the treatment effect. Effect magnitude is described with measures such as a hazard ratio, median PFS difference, or time-specific PFS probabilities, together with their uncertainty.
Why is censoring important?
Not every participant necessarily experiences progression or death during observable follow-up. Censoring allows those participants to contribute information up to the point at which their event-free status can be established, provided the assumptions underlying the censoring mechanism and analysis are appropriate.
10. Safety Results
The ClinicalTrials.gov record reports serious adverse events by randomized treatment arm. These counts are presented exactly as reported in the registry rather than converted into percentages or otherwise recomputed.
| Treatment arm | Serious adverse events affected | At risk |
|---|---|---|
| Tivozanib (AV-951) | 74 | 259 |
| Sorafenib | 56 | 257 |
These figures describe serious adverse events as reported in the ClinicalTrials.gov record. They should not be interpreted as an overall benefit-risk conclusion by themselves. Safety interpretation normally requires the event definition, severity grading, exposure duration, treatment-emergent rules, event-specific classifications, and appropriate analysis populations.
11. Statistical Interpretation of the Evidence Available
TIVO-1 was a randomized phase 3 parallel-group trial with 517 enrolled subjects, comparing tivozanib with sorafenib in advanced renal cell carcinoma. Its registered primary endpoint was a time-to-event measure of progression-free survival.
The ClinicalTrials.gov record does not provide a formal numerical PFS comparison. There is therefore no reported hazard ratio, confidence interval, p-value, median PFS, or formal test result that can responsibly be attributed to the primary endpoint from the posted statistical analyses.
A statistically rigorous trial page should not fill an evidence gap with an estimate obtained from memory, an unrelated publication, or an inference from the trial's design. The absence of a registry-reported numerical analysis is itself relevant information about what can be concluded from the specified source data.
12. ClinicalTrials.gov Results vs Formal Statistical Analysis
The registry-reported profile contains a potentially important distinction: Results Posted: Yes, while the formal no formal statistical analyses were posted. These fields answer different questions.
| Registry information | What it tells us |
|---|---|
| Results Posted: Yes | The trial record indicates that results have been posted. |
| Outcome Measures Posted: 7 | Seven outcome measures are identified as posted in the ClinicalTrials.gov record. |
| Primary Endpoints Registered: 1 | One registered primary endpoint is identified in the ClinicalTrials.gov record. |
| Statistical analyses | No formal statistical-analysis entries are reported. |
For statistical interpretation, the last distinction is crucial. An outcome being posted does not automatically mean that a formal between-group statistical comparison is available in the registry-reported analysis field.
13. Randomization as the Core Statistical Design Feature
Randomization is the explicit learning-pathway concept in the ClinicalTrials.gov record. It is also the design feature that gives the treatment comparison its principal causal structure.
Before outcomes
Treatment assignment is determined by the randomized design rather than by a participant's eventual progression status.
Between-group comparison
The primary PFS question compares outcomes accumulated after assignment to the two randomized treatment strategies.
Time-to-event extension
Randomization establishes the treatment comparison; survival methods then analyze when progression or death occurs.
Interpretive discipline
The statistical analysis should preserve the randomized comparison rather than selectively comparing participants after observing outcomes.
14. Missing Data, Censoring, and Analysis Populations
The ClinicalTrials.gov record does not describe a specific missing-data or imputation strategy, nor do they identify detailed efficacy analysis populations. Accordingly, no trial-specific imputation method is attributed to TIVO-1 here.
For a PFS analysis, however, the distinction between missing data and right censoring is important. A participant without a recorded progression by the last usable assessment is not necessarily a missing observation. In a conventional time-to-event framework, that participant can contribute event-free follow-up through the censoring time.
| Issue | Statistical meaning |
|---|---|
| Observed progression | A PFS event under the registered endpoint definition. |
| Death | A PFS event under the registered endpoint definition. |
| No event during observed follow-up | Potentially right-censored rather than treated as an event-free observation indefinitely. |
| Missing assessment information | Requires prespecified rules to determine how the available information affects the analysis. |
Because the ClinicalTrials.gov record does not specify the protocol's censoring rules or missing-assessment conventions, this page does not assign any particular censoring convention to the TIVO-1 analysis beyond explaining the statistical principles relevant to the registered endpoint.
15. Multiplicity and Interim Analysis
The ClinicalTrials.gov record does not report a multiplicity strategy, alpha-spending procedure, interim-analysis plan, stopping boundary, or endpoint hierarchy beyond identifying one registered primary endpoint.
| Design topic | Evidence in the ClinicalTrials.gov record |
|---|---|
| Multiple primary endpoints | One primary endpoint is identified. |
| Multiplicity adjustment | Not reported in the ClinicalTrials.gov record. |
| Interim analysis | Not reported in the ClinicalTrials.gov record. |
| Alpha spending | Not reported in the ClinicalTrials.gov record. |
| Stopping boundary | Not reported in the ClinicalTrials.gov record. |
This is an important limitation on statistical reconstruction. A phase 3 trial may have a complex prespecified monitoring structure, but that structure should not be inferred merely from the trial phase. If an interim analysis or multiplicity adjustment materially affected the interpretation of a reported p-value, the relevant design documentation would be needed to reproduce that interpretation accurately.
16. Non-Inferiority, Factorial, and Bayesian Methods
The ClinicalTrials.gov record does not identify a non-inferiority margin, factorial design, crossover design, or Bayesian analysis.
Non-inferiority margin
No non-inferiority margin is reported in the ClinicalTrials.gov record.
Factorial design
The registered design model is parallel, with two interventions identified.
Crossover
No crossover feature is reported in the ClinicalTrials.gov record.
Bayesian methods
No Bayesian analysis is reported in the ClinicalTrials.gov record.
17. Limitations
- No formal primary analysis reported: no formal statistical analyses were posted, so a numerical PFS treatment effect cannot be responsibly reconstructed from the ClinicalTrials.gov record.
- Endpoint-specific information: the ClinicalTrials.gov record identifies seven posted outcome measures but provide only one registered primary endpoint in the detailed endpoint section.
- No detailed analysis population: the ClinicalTrials.gov record does not specify the exact efficacy or safety analysis-population rules beyond the serious-adverse-event denominators.
- No censoring algorithm: the ClinicalTrials.gov record does not specify detailed rules for censoring, missed assessments, or progression assessments.
- No multiplicity details: the ClinicalTrials.gov record does not describe alpha allocation, multiplicity adjustment, or interim monitoring.
- No effect estimate: without a registry-reported hazard ratio, confidence interval, p-value, or median PFS, the page cannot characterize the magnitude or statistical significance of the treatment comparison.
- Safety scope: the ClinicalTrials.gov record is limited to serious adverse events by arm and does not provide a complete adverse-event profile.
18. Why This Trial Matters Statistically
TIVO-1 is a useful teaching case because it connects the design of a randomized phase 3 oncology trial directly to the statistical structure of a time-to-event endpoint. Even without inserting an unreported efficacy estimate, the trial illustrates how randomization, censoring, Kaplan-Meier estimation, hazard ratios, confidence intervals, and hypothesis testing fit together.
| Concept | How it appears in TIVO-1 |
|---|---|
| Randomization | The allocation is explicitly randomized. |
| Parallel design | The registered design model is parallel. |
| Time-to-event analysis | PFS is the registered primary endpoint type. |
| Progression-free survival | Time from randomization to progression or death. |
| RECIST | The registered PFS definition references RECIST 1.0 for disease progression. |
| Kaplan-Meier | A standard framework for estimating time-to-event distributions. |
| Hazard ratio | A standard relative measure for comparing event rates over time. |
| Confidence interval | Describes uncertainty around an estimated treatment effect. |
| Randomized comparison | Provides the foundation for comparing treatment strategies. |
| Safety analysis | Serious adverse events are reported by treatment arm. |
19. What a Complete Statistical Result Would Need to Show
For a randomized trial with PFS as the primary endpoint, a complete statistical result would normally allow the reader to see several complementary pieces of evidence rather than relying on one number.
Time-to-event curve
A Kaplan-Meier estimate would show how the probability of remaining progression-free changes over follow-up.
Effect estimate
A hazard ratio would summarize the relative event rate under a Cox-model framework.
Precision
A confidence interval would communicate uncertainty around the estimated treatment effect.
Hypothesis test
A p-value would address the prespecified null hypothesis under the applicable testing framework.
These measures answer different questions. A hazard ratio describes relative effect; a confidence interval describes uncertainty; a p-value addresses the statistical test; and a Kaplan-Meier curve describes the event-free experience over time. None of these measures should be treated as interchangeable.
20. Statistical Concepts in This Trial
Learn more about the methods used to understand randomized time-to-event trials:
21. Related Statistical Calculators
22. Sources
- ClinicalTrials.gov: TIVO-1, NCT01030783.
- Linked publication: PubMed record for PMID 37146227: PMID 37146227.
Continue with Clinical Biostats statistical methods
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23. Record Summary
TIVO-1 was a completed, randomized, parallel phase 3 trial comparing tivozanib (AV-951) with sorafenib in subjects with advanced renal cell carcinoma. The ClinicalTrials.gov record identifies progression-free survival as the single registered primary endpoint and classify it as a time-to-event outcome defined from randomization to first documented objective tumor progression or death, whichever comes first. The ClinicalTrials.gov record also report serious adverse-event counts of 74/259 for tivozanib and 56/257 for sorafenib.
The central statistical lesson is that a randomized PFS endpoint requires methods that preserve both dimensions of the data: which treatment a participant was randomized to receive and when the progression-or-death event occurred. Kaplan-Meier estimation, time-to-event hypothesis testing, and Cox-model effect estimation are natural analytical tools for this structure. However, because the registry-reported statistical-analysis field contains no formal analyses, this page deliberately stops short of assigning an unreported hazard ratio, confidence interval, p-value, or median PFS to the trial.