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
IFCT-0501 was a randomized phase 3 treatment trial in NSCLC with 451 enrolled participants and two treatment arms. The registry identifies paclitaxel plus carboplatin and monotherapy with gemcitabine or vinorelbine as the interventions, with overall survival at 1-year as the registered primary endpoint.
| Feature | IFCT-0501 |
|---|---|
| Study acronym | IFCT-0501 |
| NCT identifier | NCT00298415 |
| Phase | Phase 3 |
| Status | COMPLETED |
| Condition | NSCLC |
| Enrollment | 451 |
| Allocation | RANDOMIZED |
| Design model | SINGLE_GROUP |
| Masking | NONE |
| Primary purpose | TREATMENT |
| Number of arms | 2 |
| Lead sponsor | Intergroupe Francophone de Cancerologie Thoracique |
| Sponsor type | OTHER |
2. Clinical Question
The trial addresses a comparative treatment question in NSCLC: how does paclitaxel plus carboplatin compare with monotherapy using gemcitabine or vinorelbine when the primary endpoint is overall survival at 1-year?
Population
Patients with NSCLC, as specified by the registry condition.
Intervention
Paclitaxel plus carboplatin.
Comparator
Monotherapy with gemcitabine or vinorelbine.
Primary question
The registered primary endpoint is overall survival at 1-year.
3. Trial Design
The registry classifies IFCT-0501 as a phase 3, randomized treatment trial with two arms, no masking, and an enrollment of 451 participants. The registry also lists the design model as SINGLE_GROUP. Because the allocation field separately identifies the study as RANDOMIZED and the record specifies two arms, the allocation field and arm structure are the more direct descriptions of the comparative treatment design.
Paclitaxel + Carboplatin
- Paclitaxel
- Carboplatin
Monotherapy
- Gemcitabine or vinorelbine
4. Trial Timeline
Trial start
The registry records the study start in March 2006.
Primary completion
The registry records September 2010 as the primary completion date.
Registry status
The current registry record identifies the study status as COMPLETED.
5. Endpoints
The registry lists one registered primary endpoint: overall survival with a 1-year time frame. No additional registered primary endpoints are specified in the record.
| Endpoint | Registry time frame | Statistical role |
|---|---|---|
| Overall survival | 1-year | Primary endpoint |
Overall survival
Overall survival is a time-to-event endpoint. Conceptually, it measures the time from a defined trial starting point to death from any cause. For a 1-year endpoint, the analysis can be expressed as the probability of remaining alive through the specified 1-year time point.
Here, S(t) represents the probability that the event time T exceeds time t. At the registered 1-year time point, the corresponding quantity is the estimated probability of survival beyond 1 year.
6. Statistical Methodology
The registry identifies overall survival at 1-year as the primary endpoint but does not post a statistical analysis for that endpoint. For a randomized two-arm trial with an overall-survival endpoint, the standard statistical framework is a time-to-event analysis rather than a simple comparison of proportions that ignores follow-up time.
Kaplan-Meier estimation
A Kaplan-Meier estimator is typically used to estimate the survival function over time. It incorporates the information contributed by participants who have not experienced the event by the end of their observed follow-up through right censoring.
At each observed event time, di is the number of events and ni is the number of participants at risk immediately before that time.
Log-rank comparison
For two randomized groups, a log-rank test is commonly used to compare the survival experience over the follow-up period. It evaluates whether the observed pattern of events differs between treatment groups under the test's assumptions.
Cox proportional-hazards model
A Cox proportional-hazards model is commonly used to estimate a hazard ratio for the treatment comparison. The hazard ratio is a relative measure of the instantaneous event rate and is distinct from a 1-year survival probability.
A hazard ratio below 1 would describe a lower modeled event rate in the numerator treatment group relative to its comparator. It would not directly state the absolute difference in 1-year survival.
Time-specific survival estimation
Because the registry specifies a 1-year time frame, an analysis can focus on the estimated survival probability at 1 year. This is an absolute measure and can be presented alongside a hazard ratio when a time-to-event model is used.
Randomization and causal comparison
Randomized allocation is important because treatment assignment is determined before outcome information is observed. When the randomized comparison is analysed according to assigned treatment, the resulting treatment-group comparison can preserve the principal causal advantage of randomization, subject to the quality of trial conduct and the prespecified analysis.
7. Planned Analysis
The registered primary endpoint is overall survival at 1-year. For this type of endpoint, the usual analysis would estimate survival over time using the Kaplan-Meier method and compare randomized treatment groups with a time-to-event method such as the log-rank test. A Cox proportional-hazards model can provide a hazard ratio with a confidence interval as a relative measure of treatment effect.
| Analysis component | Typical role for this endpoint |
|---|---|
| Kaplan-Meier estimator | Estimate the overall-survival function over time |
| 1-year survival estimate | Quantify the absolute probability of remaining alive through 1 year |
| Log-rank test | Compare the survival distributions between randomized groups |
| Cox proportional-hazards model | Estimate a relative hazard ratio and confidence interval |
| Censoring | Account for participants whose event status is not observed through the relevant follow-up time |
8. Statistical Methods Explained
Why is overall survival a time-to-event endpoint?
Overall survival is not simply a binary outcome because the timing of death contains information. Two participants can both experience the event while having very different follow-up times. Time-to-event methods preserve that timing information and also accommodate participants whose event has not occurred during observed follow-up.
Why use Kaplan-Meier estimation?
Kaplan-Meier estimation provides a way to estimate survival probabilities across follow-up without requiring every participant to have experienced the event. Participants who remain alive when their observation ends can be censored and still contribute information up to that point.
What would a 1-year survival estimate mean?
A 1-year survival estimate would represent the estimated probability of being alive at the 1-year time point. It is an absolute measure. It does not by itself quantify the relative instantaneous event rate between the two treatment groups.
What would a hazard ratio add?
A hazard ratio would summarize the relative event rate between treatment groups under a Cox model. It provides a different perspective from a 1-year survival percentage. For example, a hazard ratio below 1 would indicate a lower estimated hazard in the treatment group, while the magnitude of the 1-year survival difference would still need to be examined separately.
Why does censoring matter?
Some participants may reach the end of their observable follow-up without experiencing death. Treating those participants as if they had died would bias the survival analysis. Kaplan-Meier and related survival methods instead treat such observations as censored, provided the assumptions supporting the censoring mechanism are reasonable.
What assumption accompanies a Cox hazard ratio?
The conventional Cox proportional-hazards interpretation assumes that the relative hazards are reasonably represented by a proportional relationship over time. If that assumption is inappropriate, a single hazard ratio can obscure changes in the relative treatment effect during follow-up. Time-specific survival estimates can provide an important complementary perspective.
9. Interpreting a Potential Treatment Effect
Because the registry does not post a statistical estimate for the primary endpoint, the appropriate interpretation is methodological rather than outcome-based. The central estimand is the difference in survival experience between the randomized treatment groups, with the registered time frame providing a specific 1-year perspective.
Absolute perspective
A 1-year survival estimate describes the probability of remaining alive through the specified time point. The absolute difference between treatment groups would describe the separation at that time.
Relative perspective
A hazard ratio describes relative instantaneous event rates under a time-to-event model. It is not equivalent to the difference in 1-year survival probabilities.
Uncertainty
A confidence interval around a treatment-effect estimate would quantify statistical uncertainty associated with the estimated effect under the specified analysis.
Evidence threshold
A p-value, if reported, would address evidence against a specified null hypothesis. It would not measure the magnitude or clinical importance of an effect.
10. Analysis Population and Randomization
The registry identifies the allocation as RANDOMIZED and the study as having two arms, with 451 participants enrolled. The record does not specify an analysis population such as intention-to-treat, per-protocol, or as-treated in the information available here.
| Design feature | Registry description | Statistical significance |
|---|---|---|
| Allocation | RANDOMIZED | Provides the basis for a comparative treatment analysis |
| Number of arms | 2 | Defines a two-group treatment comparison |
| Enrollment | 451 | Defines the registered study size |
| Masking | NONE | Identifies the study as unmasked |
| Analysis population | Not specified in the registry information available here | Would need to be established before interpreting a formal estimate |
Randomization supports a comparison of the assigned treatment strategies, while the absence of masking can be relevant to outcomes that are influenced by knowledge of treatment assignment. Overall survival is generally less susceptible to subjective assessment than outcomes requiring investigator judgment, but the analysis population and handling of post-randomization events remain important to interpretation.
11. Design Issues and Statistical Considerations
Randomization
Randomized allocation is a central design feature because it creates treatment groups whose differences can be interpreted within a causal framework when the trial is appropriately conducted and analysed. The registry does not specify the randomization ratio or any stratification factors.
Masking
The trial is listed as having no masking. Consequently, treatment assignment was not described as blinded in the registry. This is a design characteristic rather than evidence of a particular treatment effect.
Multiplicity
The registry lists overall survival at 1-year as the registered primary endpoint. It does not provide a multiplicity strategy, a hierarchy of multiple primary endpoints, or an alpha-allocation procedure in the information available here.
Interim analysis
The registry information available here does not specify an interim efficacy analysis, an interim monitoring boundary, or an alpha-spending method.
Missing data and imputation
The registry information available here does not specify a missing-data or imputation strategy for the primary endpoint. For overall survival, time-to-event methods generally distinguish between observed deaths and censored follow-up rather than treating censored participants as having missing binary outcomes.
Stratification
The registry information available here does not specify stratification factors for randomization or the primary survival analysis.
Bayesian methods
The registry information available here does not specify Bayesian methods or Bayesian decision criteria.
12. Limitations
- No posted primary statistical analysis: the ClinicalTrials.gov record identifies overall survival at 1-year as the primary endpoint but does not post a formal statistical analysis or numerical treatment-effect estimate.
- Limited endpoint information: the registry specifies the primary endpoint and time frame but does not provide additional efficacy endpoints in the information available here.
- No reported event counts: the registry does not report the number of overall-survival events by treatment group in the available record.
- No reported confidence interval or p-value: there is no posted inferential estimate from which statistical precision or evidence against a null hypothesis can be assessed.
- Analysis population not specified: the available registry information does not identify whether the primary analysis used an intention-to-treat, per-protocol, or another defined population.
- No stated stratification scheme: the available registry information does not identify stratification factors for randomization or survival analysis.
- No stated interim strategy: the available registry information does not identify interim analyses, stopping boundaries, or alpha spending.
- Design-model discrepancy: the registry lists RANDOMIZED allocation and two arms while also listing the design model as SINGLE_GROUP. These fields should be interpreted separately rather than assuming that the single-group label overrides the explicit randomized two-arm structure.
13. Why This Trial Matters Statistically
IFCT-0501 is a useful teaching example because its registry record illustrates how a randomized phase 3 trial can be described through its treatment comparison and a single time-to-event primary endpoint. The statistical challenge is to distinguish what the design establishes from what an eventual analysis must estimate.
| Concept | How it appears in IFCT-0501 |
|---|---|
| Randomization | The registry identifies RANDOMIZED allocation. |
| Two-arm comparison | The record specifies 2 arms with two distinct interventions. |
| Time-to-event analysis | The primary endpoint is overall survival. |
| Time-specific analysis | The primary endpoint has a 1-year time frame. |
| Kaplan-Meier estimation | A standard method for estimating survival probabilities over time. |
| Log-rank testing | A standard method for comparing survival distributions between randomized groups. |
| Cox modeling | A standard framework for estimating a relative hazard ratio. |
| Censoring | A fundamental consideration when participants are followed for differing amounts of time. |
| Unmasked design | The registry specifies NONE for masking. |
| Endpoint interpretation | A 1-year survival estimate and a hazard ratio describe different aspects of treatment effect. |
14. Clinical Interpretation vs Statistical Interpretation
Statistical interpretation
The registered primary question is a randomized comparison of overall survival at 1-year. A formal analysis would normally quantify the survival experience in each group and estimate the uncertainty around the between-group comparison.
Clinical interpretation
The treatment strategies under comparison are paclitaxel plus carboplatin and monotherapy with gemcitabine or vinorelbine. The registry identifies the comparison and endpoint but does not provide a numerical outcome from which a clinical treatment conclusion can be drawn.
15. What a Complete Survival Analysis Would Contain
A statistically complete presentation of the registered primary endpoint would normally include both an absolute and a relative description of overall survival. This distinction is important because no single statistic captures the entire survival experience.
| Component | Question answered |
|---|---|
| Kaplan-Meier curve | How does estimated survival evolve over follow-up? |
| 1-year survival estimate | What is the estimated probability of being alive at 1 year? |
| Absolute difference | How far apart are the treatment-group survival probabilities at 1 year? |
| Hazard ratio | How do modeled instantaneous event rates compare between groups? |
| 95% confidence interval | How precisely is the treatment-effect estimate estimated? |
| P-value | How compatible are the data with the specified null hypothesis under the statistical test? |
| Event counts | How much observed event information contributes to the analysis? |
A 1-year survival percentage is an absolute time-specific quantity. A hazard ratio is a relative model-based quantity over follow-up. A p-value addresses statistical evidence under a null hypothesis, while a confidence interval describes uncertainty around an estimate. Treating these as interchangeable would obscure the statistical meaning of the trial endpoint.
16. Reading the Registry Record Correctly
The registry establishes several important design facts: IFCT-0501 is a phase 3 study, it is listed as completed, enrollment is 451, allocation is randomized, there are two arms, masking is none, and the primary purpose is treatment. The interventions are paclitaxel plus carboplatin and monotherapy with gemcitabine or vinorelbine.
The primary endpoint is specifically overall survival with a 1-year time frame. This means that the principal statistical question can be framed around survival through the specified time point, while a broader time-to-event analysis would use the complete available follow-up and censoring information.
The distinction between registration and results is important. A registered endpoint describes what the study was intended to measure. A statistical result requires observed event and follow-up information together with a defined analysis population and inferential procedure.
17. Trial Status and Sponsorship
| Administrative feature | Registry record |
|---|---|
| Lead sponsor | Intergroupe Francophone de Cancerologie Thoracique |
| Sponsor type | OTHER |
| Start date | 2006-03 |
| Primary completion date | 2010-09 |
| Status | COMPLETED |
18. Sources
- ClinicalTrials.gov: IFCT-0501 (NCT00298415).
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19. Record Summary
IFCT-0501 is a completed randomized phase 3 treatment trial with 451 enrolled participants and two intervention arms: paclitaxel plus carboplatin versus monotherapy with gemcitabine or vinorelbine. The registry identifies overall survival at 1-year as the primary endpoint. Statistically, that endpoint calls for a time-to-event framework that can incorporate censoring and estimate survival at the specified time point, with methods such as Kaplan-Meier estimation, log-rank comparison, and Cox modeling providing complementary perspectives.