This page separates reported trial results from statistical interpretation. Numerical trial results are taken only from the ClinicalTrials.gov data posted on ClinicalTrials.gov for ATLAS. The registry record is the official source for the registered design, endpoints, and posted statistical analyses.
1. Trial at a Glance
ATLAS was a randomized, double-blind, parallel phase 3 trial evaluating bevacizumab therapy with or without erlotinib for first-line treatment of non-small cell lung cancer. The registered primary endpoint was progression-free survival (PFS), a time-to-event outcome assessed over approximately 3 years.
| Feature | ATLAS |
|---|---|
| Phase | Phase 3 |
| Condition | Non-Small Cell Lung Cancer |
| Design | Randomized, double-blind, parallel |
| Allocation | Randomized |
| Primary purpose | Treatment |
| Enrollment | 1145 |
| Arms | 2 |
| Primary endpoint | Progression-free Survival (PFS) |
| Primary endpoint type | Time-to-event |
| Primary hypothesis | Superiority |
| Statistical method | Log-rank test |
| Effect measure | Hazard ratio |
| ClinicalTrials.gov | NCT00257608 |
2. Clinical Question
The trial's statistical question was whether treatment with bevacizumab plus erlotinib produced a different time-to-progression-or-death profile from bevacizumab plus placebo in the randomized trial population. The registered hypothesis type was superiority.
Population
Participants enrolled in the phase 3 ATLAS study for first-line treatment of non-small cell lung cancer.
Intervention
Bevacizumab + erlotinib.
Comparator
Bevacizumab + placebo.
Primary question
Does bevacizumab plus erlotinib improve progression-free survival compared with bevacizumab plus placebo?
3. Trial Design
Bevacizumab + Placebo
- Bevacizumab
- Placebo
Bevacizumab + Erlotinib
- Bevacizumab
- Erlotinib HCl
The registry describes ATLAS as a randomized, double-blind, parallel phase 3 treatment trial. The intervention list contains bevacizumab, placebo, and erlotinib HCl. The design therefore creates a direct randomized comparison between the two treatment combinations while maintaining blinding.
4. Trial Timeline
Trial start
The ATLAS trial began in January 2006 according to the registry data.
Randomized comparison
The study used randomized allocation, a parallel design, double masking, and a treatment-focused primary purpose.
Primary PFS assessment
The registered primary endpoint was progression-free survival over approximately 3 years.
Primary completion
The registry data identify November 2014 as the primary completion date.
5. Primary Endpoint
| Endpoint | Registered definition | Time frame | Type |
|---|---|---|---|
| Progression-free Survival (PFS) | PFS was defined as the length of time from randomization until documented disease progression or death from any cause, whichever occurred earlier. Progression is defined using Response Evaluation Criteria In Solid Tumors Criteria (RECIST v1.0), as a 20% increase in the sum of the longest diameter of target lesions, or a measurable increase in a non-target lesion, or the appearance of new lesions. Data presented until cut-off date 18 July 2008. | Approximately 3 years | Time-to-event |
This endpoint combines two possible events: documented disease progression and death from any cause. The first of these events to occur determines the PFS event time. This is important because a patient who dies before documented progression still experiences a PFS event under the registered definition.
6. Secondary Endpoint
The posted statistical analyses also include overall survival. The registry classifies this analysis as secondary rather than primary.
| Endpoint | Role | Time frame | Type | Analysis |
|---|---|---|---|---|
| Overall Survival | Secondary | Approximately 3.5 years | Time-to-event | Log-rank test; hazard ratio |
7. Statistical Analysis Population
The registry specifies an intent-to-treat (ITT) population for both the primary PFS analysis and the secondary overall-survival analysis. The ITT population included all participants who were randomized during the post-chemotherapy phase.
Why ITT is important
Analyzing participants according to their randomized assignment preserves the treatment comparison created by randomization, even when subsequent events affect the amount of observed follow-up.
What ITT does not guarantee
ITT does not eliminate missing follow-up, censoring, treatment discontinuation, or other practical complications. Those issues still have to be handled appropriately in the time-to-event analysis.
8. Primary Results: Progression-Free Survival
The posted primary analysis compares bevacizumab + placebo with bevacizumab + erlotinib in the ITT population. The reported method was a log-rank test, with the treatment effect expressed as a hazard ratio.
Hazard ratio for progression or death
95% CI: 0.580–0.864 · P = 0.0006
Two-sided confidence interval · Superiority hypothesis
| Primary endpoint | Comparison | Method | Hazard ratio | 95% CI | P-value |
|---|---|---|---|---|---|
| Progression-free Survival | Bevacizumab + Placebo vs Bevacizumab + Erlotinib | Log-rank test | 0.708 | 0.580–0.864 | 0.0006 |
The reported hazard ratio of 0.708 means that the estimated instantaneous rate of a PFS event was about 70.8% for the comparison represented by the reported hazard ratio, or equivalently that the estimated hazard was approximately 29.2% lower for bevacizumab plus erlotinib relative to bevacizumab plus placebo under the fitted time-to-event comparison.
This does not mean that 29.2% of patients avoided progression, that every patient experienced a 29.2% reduction in risk, or that the probability of progression or death at a particular time point was reduced by exactly 29.2%.
The 95% confidence interval of 0.580–0.864 describes statistical uncertainty around the estimated hazard ratio under the analysis framework. It is an interval for the treatment-effect estimate, not a range containing the individual treatment effects experienced by patients.
The P-value of 0.0006 addresses evidence against the null hypothesis within the reported statistical framework. It does not measure the size, clinical importance, or certainty of the treatment effect. The hazard ratio and its confidence interval are needed to describe the magnitude and precision of the estimated effect.
Because PFS is a time-to-event endpoint, interpretation also depends on censoring and the assumptions underlying the survival-analysis framework. A hazard ratio is a relative rate measure over follow-up; it is not interchangeable with a risk ratio or an absolute difference in PFS probability.
9. Secondary Results: Overall Survival
The posted secondary analysis evaluated overall survival in the same ITT population. The registry reports a log-rank comparison and a hazard ratio with a two-sided 95% confidence interval.
Hazard ratio for overall survival
95% CI: 0.698–1.205 · P = 0.5341
Approximately 3.5-year time frame · Superiority hypothesis
| Secondary endpoint | Comparison | Method | Hazard ratio | 95% CI | P-value |
|---|---|---|---|---|---|
| Overall Survival | Bevacizumab + Placebo vs Bevacizumab + Erlotinib | Log-rank test | 0.917 | 0.698–1.205 | 0.5341 |
The reported hazard ratio of 0.917 is below 1, corresponding to an estimated instantaneous death hazard approximately 8.3% lower for the comparison represented by the reported treatment effect. This is a relative model-based estimate, not an 8.3% reduction in the proportion of patients who died.
The 95% confidence interval of 0.698–1.205 is substantially wider than the PFS interval and crosses 1. This indicates considerable uncertainty around the estimated relative effect and includes values corresponding to lower, similar, and higher hazards under the model.
The P-value of 0.5341 does not measure the magnitude of the observed hazard ratio. It describes the compatibility of the observed data with the statistical null hypothesis under the specified testing framework. A nonsmall P-value should not be translated into proof that the treatments are identical.
Overall survival can also be affected by events and treatments occurring after the initial randomized treatment. The ClinicalTrials.gov record does not provide additional information about subsequent treatment, crossover, or other post-progression factors, so those mechanisms should not be inferred here.
10. Comparing PFS and Overall Survival Statistically
ATLAS provides a useful example of why different time-to-event endpoints should not be treated as interchangeable.
| Feature | Progression-free Survival | Overall Survival |
|---|---|---|
| Role | Primary endpoint | Secondary endpoint |
| Time frame | Approximately 3 years | Approximately 3.5 years |
| Event definition | Documented progression or death, whichever occurs earlier | Death from any cause |
| Analysis population | ITT | ITT |
| Method | Log-rank test | Log-rank test |
| Hazard ratio | 0.708 | 0.917 |
| 95% CI | 0.580–0.864 | 0.698–1.205 |
| P-value | 0.0006 | 0.5341 |
The two endpoints measure different clinical events. PFS incorporates disease progression as well as death, whereas overall survival uses death from any cause. Consequently, a treatment effect on PFS need not have the same numerical magnitude as its effect on OS.
11. Statistical Methodology
Time-to-event analysis
Both posted statistical analyses concern outcomes for which the timing of an event matters. In a time-to-event analysis, a participant contributes information not only through whether an event occurs, but also through the observed time until the event or the point at which follow-up ends.
The survival function represents the probability that the event time T exceeds time t. For PFS, the event is progression or death according to the registered definition. For OS, the event is death from any cause.
Log-rank test
The registry reports the log-rank test for both PFS and overall survival. The log-rank test compares the observed pattern of event occurrence between randomized groups across follow-up, accounting for the time at which participants experience events or are censored.
The test is therefore fundamentally different from a simple comparison of proportions. A participant who remains event-free for a longer period contributes information about the treatment comparison even if that participant has not experienced the event by the end of available follow-up.
Hazard ratio
The treatment effect was expressed as a hazard ratio. Conceptually, a hazard ratio compares the instantaneous event rates between groups within a time-to-event framework.
The exact direction of interpretation depends on which treatment group is represented in the numerator of the reported comparison. A hazard ratio should not be interpreted as an absolute probability difference.
Confidence intervals
A confidence interval provides information about the precision of the estimated treatment effect. Narrower intervals generally indicate greater statistical precision, while wider intervals indicate more uncertainty. For a hazard ratio, the value 1 represents equal hazards between the compared groups.
Intention-to-treat analysis
The ATLAS registry analysis specifies an ITT population consisting of all participants randomized during the post-chemotherapy phase. This preserves the randomized treatment assignment as the basis of the efficacy comparison and avoids redefining treatment groups according to later treatment behavior.
Superiority hypothesis
The registry identifies the hypothesis type for both posted analyses as superiority. This means the statistical question is whether the randomized treatment groups differ in the favorable direction specified by the trial hypothesis, rather than whether one treatment is merely not unacceptably worse than another under a non-inferiority margin.
12. Statistical Methods Explained
Why was a log-rank test used?
PFS and OS are time-to-event endpoints, so the timing of events and censoring matters. The log-rank test is designed to compare survival experience between randomized groups while using information across the follow-up period rather than reducing each patient to a simple event/no-event indicator.
What does a PFS hazard ratio of 0.708 mean?
A hazard ratio of 0.708 indicates an estimated event rate ratio below 1 for the reported comparison. Expressed descriptively, 0.708 corresponds to an estimated hazard about 29.2% lower for the treatment represented as the numerator relative to the comparator. It does not mean that exactly 29.2% fewer patients progressed or died.
Why is the confidence interval important?
The point estimate is only one estimate of the treatment effect. The 95% CI of 0.580–0.864 shows the statistical uncertainty around the PFS hazard ratio. Looking only at 0.708 would conceal information about how precisely the effect was estimated.
Why does the P-value not measure effect size?
A P-value is a measure of evidence against a specified null hypothesis under the statistical model and testing procedure. It is affected by both the observed effect and the amount of information in the study. The hazard ratio describes relative effect size, while its confidence interval describes precision.
Why is PFS different from overall survival?
PFS records progression or death, whichever occurs first, whereas OS records death from any cause. These endpoints therefore capture different clinical processes. A treatment can have different estimated effects on the two endpoints without the statistical analysis being contradictory.
Why does randomization matter for the statistical comparison?
Randomization establishes the treatment assignment before subsequent outcomes occur. When an ITT analysis retains participants according to that assignment, the treatment comparison remains anchored to the randomized design rather than being reconstructed from post-randomization treatment choices.
13. Understanding Censoring in ATLAS
Time-to-event trials commonly include participants whose event has not been observed by the end of their available follow-up. Such observations are typically treated as censored at the appropriate follow-up time rather than being treated as if an event never occurred.
Event observed
For PFS, a documented progression or death establishes the event time under the registered definition. For OS, death establishes the event.
Event not observed
A participant without an observed event by the relevant end of follow-up contributes information up to the point at which the observation is censored.
This is one reason a simple proportion of participants with events is not equivalent to a survival-analysis result. Time-to-event methods use the available timing information and account for different lengths of observed follow-up.
14. Primary Endpoint Interpretation in Context
The PFS result combines three pieces of statistical information that should be read together: the hazard ratio, the confidence interval, and the P-value.
| Component | ATLAS PFS result | What it tells the reader |
|---|---|---|
| Hazard ratio | 0.708 | Magnitude and direction of the estimated relative time-to-event effect |
| 95% CI | 0.580–0.864 | Statistical uncertainty around the hazard-ratio estimate |
| P-value | 0.0006 | Evidence against the relevant null hypothesis under the reported test |
| Hypothesis | Superiority | The trial tested for a treatment difference rather than non-inferiority |
The three quantities answer different questions. The hazard ratio asks how large is the estimated relative effect? The confidence interval asks how precisely is that effect estimated? The P-value asks how compatible are the data with the null hypothesis under the specified testing framework?
15. Safety Results
The ClinicalTrials.gov record reports serious adverse events by treatment arm. These figures should be interpreted separately from the efficacy analyses because safety and efficacy address different outcomes and use different conceptual denominators.
| Treatment group | Participants with serious adverse events | Participants at risk |
|---|---|---|
| Bevacizumab + Placebo | 63 | 367 |
| Bevacizumab + Erlotinib | 86 | 368 |
The ClinicalTrials.gov record reports affected and at-risk counts but do not provide a formal statistical comparison for serious adverse events. Therefore, the counts should not be converted into an inferential treatment-effect claim. Safety interpretation would ordinarily consider the denominator, event definitions, exposure time, severity, timing, and clinical attribution.
16. What the Hazard Ratio Does — and Does Not — Mean
The ATLAS PFS hazard ratio of 0.708 indicates a lower estimated instantaneous rate of PFS events for the treatment represented by the numerator of the reported comparison. The complementary calculation, 1 − 0.708, gives 0.292, or approximately a 29.2% lower estimated hazard.
It does not mean that 29.2% of participants benefited, that every participant experienced a 29.2% reduction, or that the absolute probability of progression or death was reduced by 29.2 percentage points.
The 95% CI of 0.580–0.864 gives a range for the hazard-ratio estimate under the statistical framework used for the analysis. Because the entire interval lies below 1, the interval is consistent with a lower estimated hazard for the treatment represented by the numerator of the comparison.
The OS hazard ratio of 0.917 is closer to 1 than the PFS estimate, and its 95% CI of 0.698–1.205 crosses 1. This means the posted OS estimate is less precise and does not establish a statistically distinguishable difference under the reported superiority test.
17. Limitations and Interpretation Issues
- Registry-level reporting: the ClinicalTrials.gov record provides the principal statistical analyses but not the full statistical analysis plan, detailed censoring rules, or complete programming specifications.
- No median event times reported: the ClinicalTrials.gov record does not include median PFS or median overall survival, so those measures are not reported here.
- No Kaplan-Meier estimates reported: the posted information gives hazard ratios, confidence intervals, and P-values but not time-specific survival probabilities.
- Hazard-ratio interpretation: a hazard ratio is a relative time-to-event measure and should not be interpreted as a relative risk or absolute probability difference.
- Proportional-hazards consideration: hazard-ratio interpretation is most straightforward when the relative hazard is reasonably represented by a common ratio over follow-up. The ClinicalTrials.gov record does not provide a diagnostic assessment of this assumption.
- Endpoint distinction: PFS and OS are different endpoints and should not be expected to have identical treatment-effect estimates.
- Safety inference: the serious-adverse-event counts are descriptive registry data here; the ClinicalTrials.gov record does not include a formal inferential comparison.
- Generalizability: the ClinicalTrials.gov record does not provide a detailed baseline-characteristic table, so the represented study population cannot be characterized beyond the reported trial condition and design information.
- Multiplicity information: the ClinicalTrials.gov record identifies one primary endpoint and one secondary statistical analysis but do not provide an alpha-allocation or multiplicity-adjustment procedure. No such procedure is inferred here.
18. Why This Trial Matters Statistically
ATLAS is a useful teaching example because it illustrates the complete statistical chain for a randomized time-to-event endpoint: randomization establishes the comparison, an ITT population preserves that randomized assignment for efficacy analysis, the endpoint is defined as a time until progression or death, the groups are compared with a log-rank test, and the treatment effect is summarized with a hazard ratio and confidence interval.
| Concept | How it appears in ATLAS |
|---|---|
| Randomization | Randomized allocation in a parallel phase 3 design |
| Blinding | Double masking |
| ITT analysis | Primary and secondary efficacy analyses use the ITT population |
| Time-to-event endpoint | PFS is the registered primary endpoint |
| RECIST-based progression | Progression is defined using RECIST v1.0 criteria in the registry definition |
| Log-rank test | Reported for PFS and overall survival |
| Hazard ratio | Reported as the treatment-effect measure |
| Confidence interval | Two-sided 95% CIs reported for both hazard ratios |
| Superiority testing | Both posted analyses are identified as superiority hypotheses |
19. Statistical Methods Explained: A Deeper View
Why not compare only the number of patients who progressed?
Because the timing of progression matters. Two trials could have the same proportion of participants experiencing an event while having very different distributions of when those events occurred. A time-to-event method uses the follow-up time rather than discarding it.
Why does randomization support causal interpretation?
Randomization creates the treatment groups before post-randomization outcomes occur. In expectation, this balances measured and unmeasured prognostic factors across treatment assignments. The resulting comparison is therefore fundamentally different from an observational comparison in which treatment choice may be associated with baseline risk.
Why use the ITT population?
The ITT approach maintains the treatment groups created by randomization. If participants are removed from their randomized groups because of what happens after assignment, the original randomized comparison can be weakened or distorted.
What does a confidence interval crossing 1 mean for a hazard ratio?
For a hazard ratio, 1 represents equal hazards. A confidence interval that crosses 1 therefore includes values compatible with equal hazards as well as values on both sides of the null value. In ATLAS, the OS interval of 0.698–1.205 has this property.
Can the PFS and OS hazard ratios be directly compared as if they were the same outcome?
No. The PFS event includes progression or death, while the OS event is death from any cause. Different event definitions produce different estimands, so the numerical hazard ratios describe different treatment effects.
20. PFS Versus OS: An Important Statistical Distinction
PFS
The primary endpoint asks how long participants remain alive without documented disease progression. Its event definition combines progression and death.
Overall survival
The secondary endpoint asks about time to death from any cause. It does not count documented disease progression as an event by itself.
This distinction is especially important when reading a trial report. A favorable PFS result and a different OS estimate are not inherently inconsistent. They are estimates for different endpoints, with different event definitions and potentially different sources of information over follow-up.
21. Results Summary
| Endpoint | Role | Time frame | HR | 95% CI | P-value |
|---|---|---|---|---|---|
| Progression-free Survival | Primary | Approximately 3 years | 0.708 | 0.580–0.864 | 0.0006 |
| Overall Survival | Secondary | Approximately 3.5 years | 0.917 | 0.698–1.205 | 0.5341 |
The two results illustrate why a complete statistical interpretation should report the point estimate, uncertainty interval, endpoint definition, analysis population, and testing framework together. The PFS analysis reports a hazard ratio below 1 with a 95% confidence interval entirely below 1 and a P-value of 0.0006. The OS analysis reports a hazard ratio below 1, but its 95% confidence interval crosses 1 and its P-value is 0.5341.
22. Related Tutorials
Learn more about the methods used in this trial:
23. Related Calculators
24. Sources
- ClinicalTrials.gov: ATLAS — NCT00257608. Registry source for the trial design, endpoint definitions, analysis populations, statistical methods, posted estimates, confidence intervals, P-values, and serious adverse-event counts used on this page.
- Linked publication: PubMed record for PMID 24101054. Linked publication identified in the ClinicalTrials.gov record.
Continue with the statistical methods
Explore the broader Clinical Biostats collection of biostatistics tutorials, statistical calculators, and clinical-trial analyses.
25. Record Summary
ATLAS is a phase 3 randomized, double-blind, parallel clinical trial with a registered primary endpoint of progression-free survival. The primary PFS analysis used an ITT population, a log-rank test, and a hazard ratio as the effect measure. The reported PFS hazard ratio was 0.708, with a two-sided 95% CI of 0.580–0.864 and a P-value of 0.0006.
The posted secondary overall-survival analysis used the same general time-to-event framework and reported an HR of 0.917, with a two-sided 95% CI of 0.698–1.205 and a P-value of 0.5341. The contrast between these estimates demonstrates why endpoint definition, effect measure, confidence interval, and hypothesis test must all be considered together rather than relying on a single statistic.
The ClinicalTrials.gov record also report serious adverse events affecting 63/367 participants in the bevacizumab + placebo group and 86/368 participants in the bevacizumab + erlotinib group. These safety counts are descriptive in the ClinicalTrials.gov record and do not by themselves establish a statistical difference between groups.