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.
The Bronchiectasis Phenotype Identification Model (BPIM) is developed within the Assiut University prospective bronchiectasis translational research platform as a supervised baseline phenotype-translation framework for adults with non-cystic fibrosis bronchiectasis (NCFB). The Bronchiectasis Phenotype Identification Model (BPIM) follows a two-step analytical architecture. First, latent class trajectory analysis (LCTA) identifies trajectory-derived bronchiectasis phenotype classes using prospectively collected longitudinal disease-signature data. Second, the Bronchiectasis Phenotype Identification Model (BPIM) translates the accepted latent class trajectory analysis (LCTA)-derived phenotype structure into a supervised baseline classifier using the locked baseline disease-signature architecture. The Bronchiectasis Phenotype Identification Model (BPIM) is methodologically separated from the Bronchiectasis Assessment of Severity and Exacerbations (BASE) framework while remaining scientifically linked to it. The Bronchiectasis Assessment of Severity and Exacerbations Severity model (BASE-S) classifies current bronchiectasis severity at baseline. The Bronchiectasis Assessment of Severity and Exacerbations Prognostic model (BASE-P) predicts 12-month bronchiectasis exacerbation risk. The Bronchiectasis Phenotype Identification Model (BPIM) predicts the accepted latent class trajectory analysis (LCTA)-derived phenotype class. The study uses a prospective observational development-validation design. The development cohort will be used to execute the prespecified latent class trajectory analysis (LCTA) hierarchy, identify the accepted trajectory-derived phenotype structure, assign phenotype labels according to the locked convention, and train the supervised Bronchiectasis Phenotype Identification Model (BPIM) classifier. The validation cohort will be used only to evaluate the locked Bronchiectasis Phenotype Identification Model (BPIM) classifier without refitting, recalibration, predictor substitution, phenotype relabeling, threshold retuning, or post hoc classifier rescue. The latent class trajectory analysis (LCTA) component will use a prespecified top-down variable-combination hierarchy based on longitudinal functional, oxygenation, and inflammatory disease-signature domains. Three-domain latent class trajectory analysis (LCTA) options will be attempted first. If no acceptable three-domain solution is identified, two-domain options will be attempted. If all three-domain and two-domain options fail, one-domain options will be attempted as the final fallback level. Class-number selection, acceptability criteria, failure criteria, and phenotype-labeling rules are prespecified in the locked protocol and statistical analysis plan. Following acceptance of the latent class trajectory analysis (LCTA) solution, phenotype classes will be ordered according to increasing composite inflammatory and functional disease burden. Depending on the accepted class number, phenotype labels 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. The Bronchiectasis Phenotype Identification Model (BPIM) classifier will be trained as a supervised baseline classifier. Binary logistic regression will be used if the accepted latent class trajectory analysis (LCTA) solution contains two classes. Multinomial logistic regression will be used if the accepted latent class trajectory analysis (LCTA) solution contains three or four classes. Classification performance will be evaluated using confusion matrix, overall accuracy, class-specific sensitivity, class-specific specificity, positive predictive value, negative predictive value, macro-average F1 score where applicable, and agreement between predicted Bronchiectasis Phenotype Identification Model (BPIM) class and accepted latent class trajectory analysis (LCTA)-derived class. Where predicted class probabilities are generated, probability calibration will be assessed using calibration plots, observed-versus-predicted class probability summaries, and calibration metrics where appropriate. The Bronchiectasis Phenotype Identification Model (BPIM) study is observational and non-interventional. No treatment, medication, intervention, exposure, or management strategy is assigned by this protocol. All clinical care follows routine institutional practice and treating physician judgment. The study is not designed to estimate causal treatment effects. The locked methodological disclosure, protocol, deterministic statistical analysis plan, latent class trajectory analysis (LCTA) variable ledger, phenotype-labeling convention, supervised classifier structure, and validation governance are archived in the version-specific Zenodo record: https://doi.org/10.5281/zenodo.20157926. The related Bronchiectasis Assessment of Severity and Exacerbations (BASE) structural lock is archived separately at: https://doi.org/10.5281/zenodo.20143505.
Study Type
OBSERVATIONAL
Enrollment
750
Assiut university-Faculty of Medicine
Asyut, Assiut Egypt, Egypt
RECRUITINGValidation 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.
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.
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.
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.
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.
Positive Predictive Value of the Bronchiectasis Phenotype Identification Model for Phenotype Classification
Assessment of positive predictive value for each Bronchiectasis Phenotype Identification Model (BPIM)-predicted phenotype class. Positive predictive value represents the proportion of participants predicted by Bronchiectasis Phenotype Identification Model (BPIM) to belong to a given phenotype class who truly belong to the accepted latent class trajectory analysis (LCTA)-derived class. Higher values indicate better precision of phenotype assignment. Unit of Measure: Percentage.
Time frame: Baseline to 12 months follow-up.
Negative Predictive Value of the Bronchiectasis Phenotype Identification Model for Phenotype Classification
Assessment of negative predictive value for each Bronchiectasis Phenotype Identification Model (BPIM)-predicted phenotype class. Negative predictive value represents the proportion of participants not predicted by Bronchiectasis Phenotype Identification Model (BPIM) to belong to a given phenotype class who truly do not belong to that accepted latent class trajectory analysis (LCTA)-derived class. Higher values indicate better exclusion of phenotype membership. Unit of Measure: Percentage.
Time frame: Baseline to 12 months follow-up.
Macro-Average F1 Score of the Bronchiectasis Phenotype Identification Model
Assessment of macro-average F1 score for Bronchiectasis Phenotype Identification Model (BPIM) phenotype classification. Macro-average F1 score summarizes balanced classifier performance across accepted phenotype classes by combining class-specific precision and recall while giving each class equal weight. Higher values indicate better balanced multiclass classification performance. Unit of Measure: F1 score, 0 to 1 scale.
Time frame: Baseline to 12 months follow-up.
Probability Calibration of the Bronchiectasis Phenotype Identification Model
Assessment of calibration of Bronchiectasis Phenotype Identification Model (BPIM)-predicted class probabilities where predicted phenotype probabilities are generated. Calibration will evaluate agreement between predicted class probabilities and observed accepted latent class trajectory analysis (LCTA)-derived phenotype membership. Better calibration indicates closer agreement between predicted probability and observed phenotype membership. Unit of Measure: Calibration slope
Time frame: Baseline to 12 months follow-up.
Confusion Matrix of Bronchiectasis Phenotype Identification Model Classification
Confusion matrix comparing Bronchiectasis Phenotype Identification Model (BPIM)-predicted phenotype class with accepted latent class trajectory analysis (LCTA)-derived phenotype class. The confusion matrix will summarize correct and incorrect class assignment across the accepted phenotype classes. Unit of Measure: Percentage of participants
Time frame: Baseline to 12 months follow-up.
Relationship Between Bronchiectasis Phenotype Identification Model Phenotype Classes and Bronchiectasis Assessment of Severity and Exacerbations Severity Categories
Assessment of the relationship between accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes and Bronchiectasis Assessment of Severity and Exacerbations Severity model (BASE-S) categories. This analysis evaluates whether trajectory-derived phenotype classes show clinically coherent patterns across baseline severity categories. Unit of Measure: Percentage of participants across categories.
Time frame: Baseline
Relationship Between Bronchiectasis Phenotype Identification Model Phenotype Classes and Bronchiectasis Assessment of Severity and Exacerbations Prognostic Risk Categories
Assessment of the relationship between accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes and Bronchiectasis Assessment of Severity and Exacerbations Prognostic model (BASE-P) risk categories. This analysis evaluates whether trajectory-derived phenotype classes show clinically coherent patterns across 12-month exacerbation-risk categories. Unit of Measure: Percentage of participants across categories.
Time frame: Baseline to 12 months follow-up.
Bronchiectasis Exacerbation Occurrence by Bronchiectasis Phenotype Identification Model Phenotype Class
Occurrence of at least one bronchiectasis exacerbation during follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Higher exacerbation occurrence in higher-burden phenotype classes indicates clinically coherent phenotype-outcome association. Unit of Measure: Percentage of participants.
Time frame: Baseline to 12 months follow-up.
Time to First Bronchiectasis Exacerbation by Bronchiectasis Phenotype Identification Model Phenotype Class
Time from baseline assessment to first recorded bronchiectasis exacerbation according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Participants without exacerbation will be censored at last available follow-up or at 12 months. Shorter time to first exacerbation indicates earlier clinical deterioration. Unit of Measure: Days.
Time frame: Baseline to 12 months follow-up.
Number of Bronchiectasis Exacerbations During Follow-Up by Bronchiectasis Phenotype Identification Model Phenotype Class
Total number of bronchiectasis exacerbations during follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Higher exacerbation count indicates greater disease instability. Unit of Measure: Number of events.
Time frame: Baseline to 12 months follow-up.
Severe Bronchiectasis Exacerbation Requiring Hospitalization by Bronchiectasis Phenotype Identification Model Phenotype Class
Occurrence of at least one severe bronchiectasis exacerbation requiring hospital admission during follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Hospitalization-requiring exacerbation indicates more severe clinical deterioration. Unit of Measure: Percentage of participants.
Time frame: Baseline to 12 months follow-up.
Bronchiectasis-Related Hospital Admission by Bronchiectasis Phenotype Identification Model Phenotype Class
Occurrence of bronchiectasis-related hospital admission during follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Bronchiectasis-related hospital admission includes admission related to bronchiectasis deterioration, respiratory infection, bronchiectasis exacerbation, worsening respiratory symptoms, or related respiratory failure. Unit of Measure: Percentage of participants.
Time frame: Baseline to 12 months follow-up.
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