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
STAR*D was a phase 4 treatment study examining the relationship between depression symptoms and brain physiologic measures in depressed people receiving antidepressant medication.
| Feature | STAR*D |
|---|---|
| NCT ID | NCT00375843 |
| Phase | Phase 4 |
| Status | Completed |
| Condition | Depression |
| Lead sponsor | National Institute of Mental Health (NIMH) |
| Sponsor type | NIH |
| Allocation | Non-randomized |
| Design model | Single group |
| Masking | None |
2. Clinical Question
The central question was whether depression symptoms were related to brain physiologic measures among depressed people receiving antidepressant medication.
Population
Depressed people receiving antidepressant medication.
Interventions
Escitalopram or sertraline.
Comparator
No separate comparator group was reported; the registry describes a single-group design.
Primary question
Relationship between depression symptoms and brain physiologic measures.
3. Trial Design
Escitalopram
Drug intervention evaluated within the study.
Sertraline
Drug intervention evaluated within the study.
4. Endpoints
| Endpoint | Registry definition | Time frame |
|---|---|---|
| Relationship between depression symptoms and brain physiologic measures | Relationship between depression symptoms and brain physiologic measures | Measured at exit from Level 1 treatment or from Level 2 treatment |
The registry specifies that each treatment level had a duration of 12 weeks. The primary endpoint was assessed at exit from Level 1 treatment or from Level 2 treatment.
5. Planned Analysis
The ClinicalTrials.gov record identifies the primary endpoint but does not report posted statistical analyses or results.
The primary endpoint is a relationship-based outcome involving depression symptoms and brain physiologic measurements. For endpoints of this type, statistical analysis commonly focuses on quantifying associations between measured variables, selecting methods based on the measurement scale, distribution, timing, and prespecified analysis plan.
6. Statistical Methodology
Association-based analysis
The primary endpoint evaluates a relationship rather than a direct comparison between randomized groups. Statistical approaches for relationship questions typically estimate the strength and direction of association between physiologic measures and clinical outcomes.
7. Statistical Methods Explained
Why is this not analyzed like a randomized comparison?
The registry describes a non-randomized, single-group design. Without a randomized comparator, treatment groups cannot be interpreted through the same causal framework as a randomized controlled trial.
What does a relationship between symptoms and brain measures mean?
An association describes whether two measured quantities vary together. It does not by itself establish that one variable causes changes in the other.
Why does measurement timing matter?
The endpoint was measured at exit from Level 1 treatment or Level 2 treatment, each with a 12-week duration. Timing defines the clinical context in which the relationship is evaluated.
Why are confidence intervals important in association analyses?
A confidence interval describes uncertainty around an estimated association. A precise estimate and an imprecise estimate can have different interpretations even if their point estimates are similar.
Why does a p-value not describe clinical importance?
A p-value addresses compatibility with a statistical hypothesis under assumptions of the analysis. It does not measure the magnitude, biological meaning, or practical importance of an observed relationship.
8. Limitations
- No randomized comparator: The registry describes a non-randomized, single-group design, limiting causal comparisons between treatments.
- No posted statistical analyses: The registry does not report formal statistical analysis results.
- Measurement complexity: Brain physiologic measures and symptom assessments may require careful handling of measurement variability and timing.
- Multiple measurements: Physiologic studies can involve multiple measured features, which may require prespecified control of statistical interpretation.
9. Why This Trial Matters Statistically
STAR*D is useful as a statistical teaching example because it illustrates analysis questions that differ from standard randomized efficacy trials.
| Concept | How it appears in STAR*D |
|---|---|
| Study design | Non-randomized, single-group treatment study. |
| Association analysis | Primary endpoint evaluates relationship between symptoms and physiologic measures. |
| Repeated treatment levels | Measurements occurred at exit from Level 1 or Level 2 treatment. |
| Clinical measurement | Links biological measurements with depression symptom assessment. |
| Interpretation | Associations require careful distinction from causal effects. |
10. Sources
- ClinicalTrials.gov: NCT00375843.
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11. Record Summary
STAR*D provides an example of a phase 4 treatment study focused on the relationship between clinical symptoms and physiologic measurements. The registry describes a completed non-randomized, single-group study of 118 participants receiving escitalopram or sertraline, with the primary endpoint measured at exit from Level 1 or Level 2 treatment.