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Stage IV NSCLC Phase 3 Completed NCT01257139

ESOGIA: Complete Statistical Analysis of Treatment Strategies in Elderly Stage IV Non-Small-Cell Lung Cancer

An independent statistical analysis of the randomized phase 3 ESOGIA trial comparing a classical strategy of treatment allocation with an optimized strategy allocating the same treatments in subjects over 70 years of age with stage IV non-small-cell lung cancer.

Rennes University Hospital · Start date 2010-01 · Primary completion date 2014-07
Scope of this 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

ESOGIA was a randomized phase 3 parallel-group trial evaluating treatment allocation strategies for subjects over 70 years of age with stage IV non-small-cell lung cancer.

490
Enrollment
2
Arms
3
Phase
2010–2014
Trial period
FeatureESOGIA
ConditionNon Small-cell Lung Cancer
PopulationSubjects over 70 years of age with stage IV non-small-cell lung cancer
DesignRandomized, parallel, open-label
Enrollment490
Lead sponsorRennes University Hospital
InterventionsDual-agent therapy or docetaxel alone or best supportive care (procedure)

2. Clinical Question

Population

Subjects over 70 years of age with stage IV non-small-cell lung cancer.

Intervention

An optimized strategy allocating the same treatments.

Comparator

A classical strategy of treatment allocation.

Primary question

Whether the treatment allocation strategy affected time to failure.

3. Trial Design

01
Randomize
490 subjects
02
Allocation
Two strategies
03
Treatment
Same treatments
04
Follow-up
Failure assessment
05
Analysis
Primary endpoint

4. Endpoints

EndpointDefinitionTime frame
Time to failureDefined from the date of inclusion to the date of documented progression, death of any cause, trial exit for toxicity considered unacceptable by the patient or investigator, or withdrawal of consentDate of documented progression up to 6 months

5. Planned Analysis

The ClinicalTrials.gov record identifies time to failure as the primary endpoint. For a time-to-event endpoint, statistical analysis would typically evaluate the distribution of time until the defined failure event using methods that account for censoring and differing follow-up times between randomized groups.

Registry reporting status. Results have not been posted on ClinicalTrials.gov.

6. Statistical Methodology

Time-to-event analysis

Time to failure is a survival-type endpoint because the outcome is measured as the time from inclusion until the occurrence of a defined event. These analyses commonly account for participants who have not yet experienced failure at the end of observation through censoring.

Conceptual survival function
S(t) = Probability of remaining free of the event beyond time t

Survival methods describe how event risk accumulates over time rather than only comparing event proportions at a single time point.

Randomized comparison

Because ESOGIA used randomized allocation, the treatment strategies can be compared while preserving the balance created by randomization. The registry describes allocation as randomized and the design model as parallel.

7. Statistical Methods Explained

Why is time to failure analyzed as a time-to-event endpoint?

A time-to-event approach uses both whether an event occurred and when it occurred. This is important when participants have different follow-up durations.

What does censoring mean?

Censoring occurs when the exact event time is not observed during follow-up. Proper survival methods allow these observations to contribute information up to the available follow-up time.

Why does randomization matter?

Randomization helps create comparable groups at baseline, allowing differences observed after treatment allocation to be interpreted within the randomized comparison framework.

Why is the endpoint definition important?

The ESOGIA endpoint combines documented progression, death, unacceptable toxicity-related trial exit, and withdrawal of consent. The statistical interpretation depends on exactly which events are counted as failures.

Why are published estimates needed?

Effect estimates, confidence intervals, and statistical tests require reported trial results. The registry does not provide posted statistical analyses for this trial.

8. Limitations

9. Why This Trial Matters Statistically

ConceptHow it appears in ESOGIA
RandomizationRandomized allocation of treatment strategies
Parallel designTwo concurrent trial arms
Time-to-event analysisPrimary endpoint measured from inclusion to failure
Composite endpoint interpretationFailure includes progression, death, toxicity-related exit, or withdrawal of consent
Open-label designNo masking reported

10. Sources