Bronchiectasis Phenotype Identification Model
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorAssiut University
About this trial
The Bronchiectasis Phenotype Identification Model (BPIM) is a prospective observational development-validation study within the Assiut University bronchiectasis translational research platform.
The study evaluates whether latent class trajectory analysis (LCTA)-derived bronchiectasis phenotype classes can be translated into a supervised baseline classifier for adults with non-cystic fibrosis bronchiectasis (NCFB).
Latent class trajectory analysis (LCTA) will first identify trajectory-derived phenotype classes using prospectively collected longitudinal disease-signature data. The Bronchiectasis Phenotype Identification Model (BPIM) will then be trained to predict the accepted latent class trajectory analysis (LCTA)-derived phenotype class using the locked baseline disease-signature architecture.
This study is observational and non-interventional. No treatment, medication, intervention, exposure, or management strategy is assigned by the protocol. All participants receive routine clinical care according to institutional practice and treating physician judgment.
The locked methodological disclosure, protocol, and deterministic statistical analysis plan are archived in the version-specific Zenodo record: https://doi.org/10.5281/zenodo.20157926.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Adult patients aged 18 years or older.
Diagnosis of non-cystic fibrosis bronchiectasis (NCFB) based on clinical assessment and high-resolution computed tomography (HRCT).
Patients attending outpatient clinics, inpatient wards, or respiratory follow-up services at Assiut University Hospitals during the study enrollment period.
Patients suitable for baseline disease-signature assessment within the Bronchiectasis Phenotype Identification Model (BPIM) framework.
Disqualifiers
Cystic fibrosis-related bronchiectasis.
Traction bronchiectasis due to advanced fibrotic interstitial lung disease as the dominant respiratory diagnosis.
Active pulmonary tuberculosis at enrollment.
Active nontuberculous mycobacterial pulmonary disease requiring specific treatment at enrollment.
Trial population
Adult patients with clinically and radiologically confirmed non-cystic fibrosis bronchiectasis (NCFB) attending outpatient clinics, inpatient wards, or respiratory follow-up services at Assiut University Hospitals during the enrollment period will be prospectively screened. Eligible participants will undergo baseline disease-signature assessment within the Bronchiectasis Phenotype Identification Model (BPIM) framework and planned longitudinal follow-up for latent class trajectory analysis (LCTA), supervised BPIM classifier development, and validation. Participants receive routine clinical care; no treatment or intervention is assigned by the protocol.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
750 Participants
are grouped into 2 trial groupsGroup A: Development Cohort
Group B: Validation Cohort
Trial outcomes
Primary outcomes
1
Validation Classification Accuracy of the Bronchiectasis Phenotype Identification Model (BPIM) for Latent Class Trajectory Analysis-Derived Phenotype Classes
Assessment of the validation performance of the Bronchiectasis Phenotype Identification Model (BPIM) for prediction of accepted latent class trajectory analysis (LCTA)-derived bronchiectasis phenotype classes in adults with non-cystic fibrosis bronchiectasis (NCFB). The Bronchiectasis Phenotype Identification Model (BPIM) is a supervised baseline phenotype classifier trained in the development cohort and applied unchanged to the validation cohort. The accepted latent class trajectory analysis (LCTA)-derived phenotype class will serve as the phenotype ground truth. Higher classification accuracy indicates better agreement between Bronchiectasis Phenotype Identification Model (BPIM)-predicted phenotype class and accepted latent class trajectory analysis (LCTA)-derived phenotype class. Unit of Measure: Percentage of participants correctly classified.
Time frame
Baseline to 12 months follow-up.Secondary outcomes
1
Accepted Latent Class Trajectory Analysis-Derived Phenotype Class
Identification of the accepted latent class trajectory analysis (LCTA)-derived bronchiectasis phenotype class using prospectively collected longitudinal disease-signature data. Latent class trajectory analysis (LCTA) will use prespecified functional, oxygenation, and inflammatory longitudinal domains according to the locked variable-combination hierarchy. Depending on the accepted class-number solution, phenotype classes may include Stable phenotype, Progressive/Frequent Exacerbator phenotype, Frequent Exacerbator/Inflammatory phenotype, Advanced Multidomain phenotype, and End-stage/Terminal-risk phenotype according to the locked labeling convention. Unit of Measure: Percentage of participants in each phenotype class.
Time frame
Baseline to 12 months follow-up.2
Agreement Between Bronchiectasis Phenotype Identification Model-Predicted Class and Accepted Latent Class Trajectory Analysis-Derived Class
Agreement between Bronchiectasis Phenotype Identification Model (BPIM)-predicted phenotype class and accepted latent class trajectory analysis (LCTA)-derived phenotype class. Agreement may be assessed using agreement statistics appropriate to the accepted class structure. Higher agreement indicates better reproducibility of latent class trajectory analysis (LCTA)-derived phenotype classes using the supervised Bronchiectasis Phenotype Identification Model (BPIM) baseline classifier. Unit of Measure: Kappa coefficient
Time frame
Baseline to 12 months follow-up.3
Class-Specific Sensitivity of the Bronchiectasis Phenotype Identification Model
Assessment of class-specific sensitivity of the Bronchiectasis Phenotype Identification Model (BPIM) for each accepted latent class trajectory analysis (LCTA)-derived phenotype class. Sensitivity represents the proportion of participants in a given accepted phenotype class who are correctly classified by Bronchiectasis Phenotype Identification Model (BPIM) into that same class. Higher values indicate better class-specific recognition. Unit of Measure: Percentage.
Time frame
Baseline to 12 months follow-up.4
Class-Specific Specificity of the Bronchiectasis Phenotype Identification Model
Assessment of class-specific specificity of the Bronchiectasis Phenotype Identification Model (BPIM) for each accepted latent class trajectory analysis (LCTA)-derived phenotype class. Specificity represents the proportion of participants not belonging to a given phenotype class who are correctly classified by Bronchiectasis Phenotype Identification Model (BPIM) as not belonging to that class. Higher values indicate better class-specific exclusion. Unit of Measure: Percentage.
Time frame
Baseline to 12 months follow-up.Other outcomes
1
Bayesian Information Criterion of Latent Class Trajectory Analysis Solutions
Assessment of Bayesian Information Criterion (BIC) for prespecified latent class trajectory analysis (LCTA) class-number solutions within each variable-combination option. Bayesian Information Criterion (BIC) will guide class-number selection among acceptable models but will not override convergence, entropy, minimum class size, or clinical interpretability. Unit of Measure: Bayesian Information Criterion (BIC), unitless.
Time frame
Baseline to 12 months follow-up.2
Entropy of Latent class Trajectory Analysis Solutions
Assessment of entropy for latent class trajectory analysis (LCTA) class solutions. Entropy reflects classification quality of latent class assignment. Higher entropy indicates better class separation, with entropy of at least 0.70 required for an acceptable primary latent class trajectory analysis (LCTA) solution. Unit of Measure: Entropy, 0 to 1 scale.
Time frame
Baseline to 12 months follow-up.3
Minimum Class Size of Latent class Trajectory Analysis Solutions
Assessment of the minimum class size across accepted or attempted latent class trajectory analysis (LCTA) solutions. No accepted latent class trajectory analysis (LCTA) solution may contain a class smaller than 5% of the total analyzable cohort. Unit of Measure: Percentage of total analyzable cohort.
Time frame
Baseline to 12 months follow-up.4
Posterior Class-Assignment Probability of Accepted Latent class Trajectory Analysis Phenotype Classes
Assessment of posterior class-assignment probability for accepted latent class trajectory analysis (LCTA)-derived phenotype classes where supported by the modeling framework. Higher posterior assignment probability indicates greater certainty of latent phenotype class assignment. Unit of Measure: Probability, 0 to 1 scale.
Time frame
Baseline to 12 months follow-up.Sponsors and contacts
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Source ClinicalTrials.gov