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
COPDGene is an active, not recruiting study examining genetic factors that may cause chronic obstructive pulmonary disease (COPD). The study includes participants with pulmonary disease conditions including chronic obstructive pulmonary disease, emphysema, and chronic bronchitis.
| Feature | COPDGene |
|---|---|
| NCT ID | NCT00608764 |
| Status | ACTIVE_NOT_RECRUITING |
| Sponsor | Brigham and Women's Hospital |
| Sponsor type | OTHER |
| Conditions | Pulmonary Disease, Chronic Obstructive; Emphysema; Bronchitis, Chronic |
| Enrollment | 10,718 |
2. Clinical Question
Population
Participants evaluated for chronic obstructive pulmonary disease, emphysema, and chronic bronchitis.
Intervention
The registry describes examination of genetic factors associated with COPD rather than a therapeutic intervention.
Comparator
COPD participants versus control group participants.
Primary question
Which measured clinical, imaging, and genetic characteristics are associated with COPD status and related pulmonary phenotypes?
3. Trial Design
The registry lists four arms.
The study enrollment is 10,718 participants.
Started 2007-11 with primary completion date 2028-08.
ACTIVE_NOT_RECRUITING.
4. Endpoints
| Endpoint | Time frame |
|---|---|
| Forced expiratory volume in 1 second (FEV1) | Measured at baseline |
| Emphysema, as shown on chest CT scan | Measured at baseline |
| Airway wall thickness on chest CT scan | Measured at baseline |
| COPD status (COPD participants versus control group participants) | Measured at baseline |
5. Planned Analysis
The registry identifies baseline measurements of pulmonary function, CT imaging characteristics, and COPD status as primary endpoints. These endpoints are generally analyzed using methods appropriate for continuous and categorical baseline outcomes.
Continuous outcomes
Measurements such as forced expiratory volume in 1 second are typically summarized using descriptive statistics and may be evaluated using regression-based approaches when assessing associations with genetic or clinical variables.
Imaging outcomes
Chest CT-derived measures such as emphysema and airway wall thickness are quantitative imaging phenotypes that can be analyzed using statistical models relating imaging measurements to participant characteristics.
Categorical outcomes
COPD status compares COPD participants with control group participants and is commonly evaluated using methods for binary outcomes.
No formal statistical analyses were posted to ClinicalTrials.gov for these endpoints.
6. Statistical Methods Explained
How is FEV1 commonly analyzed statistically?
FEV1 is a continuous pulmonary function measurement. Statistical analyses often focus on differences between groups or associations between FEV1 and explanatory variables while accounting for relevant participant characteristics.
Why are CT measurements useful endpoints?
CT-derived emphysema and airway wall thickness provide quantitative measures of structural lung changes. These measurements may capture aspects of disease phenotype beyond symptom-based classification.
Why compare COPD participants with control participants?
A COPD versus control comparison creates a binary outcome framework that allows statistical models to evaluate characteristics associated with disease status.
Why does baseline measurement matter?
Baseline endpoints describe participant characteristics at study entry. They differ from longitudinal outcomes that measure change over time.
What does an association analysis show?
An association identifies relationships between variables. It does not by itself establish that one variable causes another.
7. Limitations
- The ClinicalTrials.gov record reports baseline endpoint definitions but does not provide posted statistical estimates or confidence intervals.
- Baseline measurements describe characteristics at assessment and do not by themselves establish temporal changes.
- Associations between genetic, imaging, and clinical variables require careful interpretation because correlation does not establish causation.
- Results from observational analyses may depend on participant selection and measurement procedures.
8. Why This Trial Matters Statistically
COPDGene is an example of how statistical methodology is applied to complex biomedical phenotyping. The study combines pulmonary function, imaging measurements, and disease classification, illustrating several important statistical concepts.
| Concept | Application |
|---|---|
| Continuous outcomes | FEV1 measurement |
| Imaging phenotyping | Chest CT measurements of emphysema and airway wall thickness |
| Binary outcomes | COPD status comparison |
| Multivariable modeling | Assessing relationships among clinical and biological characteristics |