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Pancreatic Cancer Phase 3 Randomized Trial NCT00058201

ESPAC-3: Complete Statistical Analysis of Chemotherapy in Resected Pancreatic Cancer

An educational statistical review of the ESPAC-3 phase 3 randomized trial comparing chemotherapy regimens with observation in patients with completely resected pancreatic cancer.

ESPAC-3 · ClinicalTrials.gov NCT00058201
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

ESPAC-3 was a phase 3 randomized treatment trial evaluating chemotherapy regimens and clinical observation in patients with completely resected pancreatic cancer.

1030
Enrollment
3
Number of arms
Phase 3
Trial phase
2001-07
Start date
FeatureESPAC-3
ConditionPancreatic Cancer
DesignRandomized phase 3 trial
Primary purposeTreatment
AllocationRandomized
Lead sponsorRoyal Liverpool University Hospital
Sponsor typeOTHER_GOV

2. Clinical Question

Population

Patients with completely resected pancreatic cancer.

Interventions

Fluorouracil, gemcitabine hydrochloride, leucovorin calcium, and clinical observation.

Comparator

The registry identifies clinical observation as one of the trial arms.

Primary question

Does the assigned treatment strategy affect overall survival?

3. Trial Design

Randomization

Patients were assigned in a randomized phase 3 design.

Arms

The study included 3 arms.

Enrollment

The registry reports 1030 participants.

Timeline

Primary completion date: 2008-04.

4. Endpoints

EndpointRegistry definition
Overall survivalPrimary endpoint

5. Statistical Methodology

The registry identifies overall survival as the primary endpoint. For randomized oncology trials with an overall survival endpoint, the statistical framework generally focuses on comparing time-to-event distributions between randomized groups.

Time-to-event analysis

Overall survival is typically analysed using methods that account for patients who are alive at the end of follow-up or lost to follow-up. Kaplan-Meier estimation describes survival over time, while comparative models such as Cox proportional-hazards models may summarize relative treatment effects.

Conceptual survival function
S(t) = P(T > t)

The survival function represents the probability that the event time exceeds a specified time point.

6. Planned Analysis

The registry identifies overall survival as the primary endpoint but does not report posted statistical analyses or endpoint results on ClinicalTrials.gov.

For an endpoint of this type, a typical analysis would compare overall survival between randomized groups using time-to-event methods, accounting for censoring and estimating uncertainty around treatment comparisons. Results have not been posted on ClinicalTrials.gov.

7. Statistical Methods Explained

Why is overall survival analysed as a time-to-event endpoint?

Patients may experience death at different times, and some observations may be censored. Time-to-event methods incorporate the timing of events rather than only whether an event occurred.

What does randomization contribute statistically?

Randomization creates treatment groups whose outcomes can be compared while reducing systematic differences between groups at baseline.

Why is censoring important?

Censoring allows patients with incomplete follow-up information to contribute available survival information without assuming their future outcomes.

What does a hazard ratio represent?

A hazard ratio is a relative comparison of event rates over time under a statistical model. It is not the same as the percentage of patients who experience an event.

Why are confidence intervals important?

Confidence intervals describe uncertainty around an estimated treatment effect and help distinguish precise estimates from estimates with substantial uncertainty.

Why does a p-value not describe treatment magnitude?

A p-value addresses evidence against a statistical null hypothesis. It does not directly measure clinical importance or the size of an effect.

8. Limitations

9. Why This Trial Matters Statistically

ESPAC-3 illustrates several important principles in clinical trial statistics:

ConceptApplication
RandomizationComparison of treatment strategies in a phase 3 design
Overall survivalTime-to-event primary endpoint
CensoringRequired for incomplete follow-up observations
Survival modelsFramework for analysing event timing

10. Sources