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
ACTS-GC was a phase 3 randomized parallel trial evaluating TS-1 (S-1) in gastric cancer following surgery.
| Feature | ACTS-GC |
|---|---|
| Condition | Gastric Cancer |
| Design | Randomized parallel study |
| Masking | Quadruple |
| Primary purpose | Treatment |
| Lead sponsor | Taiho Pharmaceutical Co., Ltd. |
| ClinicalTrials.gov | NCT00152217 |
2. Clinical Question
The primary question was whether TS-1 (S-1) improved outcomes compared with surgery alone in patients with gastric cancer.
Population
Patients with gastric cancer.
Intervention
TS-1 (S-1) drug treatment.
Comparator
Surgery procedure.
Primary Question
Does TS-1 affect overall survival compared with surgery?
3. Trial Design
Randomized
Parallel assignment
Quadruple
1000 participants
| Arm | Intervention |
|---|---|
| TS-1 arm | TS-1 (S-1) |
| Comparator arm | Surgery |
4. Endpoints
| Endpoint | Registry definition / time frame |
|---|---|
| Overall survival | Overall survival; every course for first three courses, then every other course |
5. Planned Analysis
The registry identifies overall survival as the primary endpoint but does not report posted statistical analyses or outcome estimates.
For a time-to-event endpoint such as overall survival, a clinical trial analysis would typically compare survival distributions between randomized groups using methods such as Kaplan-Meier estimation, log-rank testing, and a Cox proportional-hazards model for estimating a hazard ratio.
6. Statistical Methodology
Overall survival analysis
Overall survival is a time-to-event endpoint measuring time until death. Patients who have not experienced the event at the time of analysis are generally handled as censored observations in survival analysis methods.
Kaplan-Meier estimation
The Kaplan-Meier method estimates survival probabilities over time while accounting for different follow-up durations among participants.
Log-rank comparison
A log-rank test compares survival experience between randomized groups across the observed follow-up period.
Cox proportional-hazards model
A Cox model estimates a hazard ratio comparing event rates between groups while allowing for censored observations.
7. Statistical Methods Explained
Why use overall survival?
Overall survival directly measures time until death and is commonly used as a definitive time-to-event outcome.
What does randomization accomplish?
Randomization helps balance known and unknown factors between treatment groups.
Why censor patients?
Censoring allows patients with incomplete follow-up information to contribute available survival information.
What does a hazard ratio represent?
A hazard ratio describes the relative event rate over time under the fitted model.
8. Limitations
- The registry does not report posted statistical analyses or numerical outcome estimates.
- Without reported results, treatment effects cannot be quantified from the registry information alone.
- Time-to-event analyses depend on follow-up completeness and assumptions of the statistical model used.
9. Why This Trial Matters Statistically
ACTS-GC is useful as a statistical teaching example because it illustrates the structure of a randomized phase 3 trial with a survival endpoint.
| Concept | Application |
|---|---|
| Randomization | Randomized treatment comparison |
| Parallel design | Concurrent comparison groups |
| Time-to-event analysis | Overall survival endpoint |
| Censoring | Handling incomplete event observation |
| Hazard ratio | Common survival treatment-effect measure |