1. Trial at a Glance
Look AHEAD was a completed clinical trial evaluating behavioral interventions in participants with obesity and type 2 diabetes. The registry lists intensive lifestyle intervention and diabetes support and education as the behavioral interventions.
Enrollment
Registered arm
Start date
Primary completion
| Feature | Look AHEAD |
|---|---|
| NCT ID | NCT01270763 |
| Acronym | Look AHEAD |
| Status | Completed |
| Lead sponsor | The Miriam Hospital |
| Conditions | Obesity; Type 2 Diabetes |
| Interventions | Intensive lifestyle intervention (behavioral); Diabetes support and education (behavioral) |
2. Clinical Question
Population
Adults studied in the setting of obesity and type 2 diabetes.
Intervention
Intensive lifestyle intervention (behavioral).
Comparator
Diabetes support and education (behavioral).
Primary question
How does intensive lifestyle intervention affect prespecified metabolic outcomes compared with diabetes support and education?
3. Trial Design
| Design feature | Description |
|---|---|
| Enrollment | 4,108 participants |
| Number of arms | 1 registered arm |
| Study type | Clinical trial |
| Interventions | Behavioral interventions |
4. Endpoints
| Endpoint | Time frame |
|---|---|
| Body weight | 4 years |
| High density lipoprotein cholesterol | 4 years |
5. Planned Analysis
The registry identifies body weight and high density lipoprotein cholesterol as primary endpoints measured at 4 years. Results have not been posted on ClinicalTrials.gov.
For continuous metabolic outcomes such as body weight and lipid measurements, analyses commonly compare changes over time between intervention groups using methods such as analysis of covariance, repeated-measures models, or other prespecified longitudinal approaches. The appropriate method depends on the final statistical analysis plan, measurement schedule, and assumptions about missing observations.
6. Statistical Methodology
The statistical framework for behavioral intervention trials generally focuses on comparing changes in continuous clinical measures while accounting for baseline values and repeated measurements over time.
A treatment effect for body weight or high density lipoprotein cholesterol describes the difference in average outcome between randomized groups under the chosen statistical model. It does not describe the response of every individual participant.
7. Statistical Methods Explained
Why are continuous outcomes analyzed differently from survival outcomes?
Body weight and high density lipoprotein cholesterol are measured quantities rather than time-to-event outcomes. Their analyses focus on differences in means, changes from baseline, or longitudinal trajectories rather than hazard ratios.
Why can baseline adjustment improve precision?
When baseline measurements are available, statistical models can account for initial differences and reduce unexplained variability, potentially improving estimation of the intervention effect.
Why does missing data matter?
Longitudinal behavioral studies may have incomplete follow-up measurements. The statistical approach used to address missing observations can influence interpretation.
Why is the time frame important?
An endpoint measured at 4 years answers a different question from an early change measurement. The time horizon defines the clinical outcome being evaluated.
8. Limitations
- The registry does not report posted statistical analyses or endpoint results.
- The registered record lists one arm and behavioral interventions but does not provide additional analysis details in the available record.
- Interpretation of long-term metabolic effects requires the prespecified statistical analysis plan and reported results.
9. Why This Trial Matters Statistically
| Concept | Application |
|---|---|
| Behavioral intervention analysis | Comparison of lifestyle-focused approaches using measurable clinical outcomes |
| Continuous outcomes | Body weight and lipid measures require methods designed for quantitative endpoints |
| Longitudinal follow-up | Four-year endpoint timing emphasizes sustained change over time |
| Clinical interpretation | Statistical estimates describe population-level effects rather than individual guarantees |