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RecruitingNCT07599969BPIMUpdated May 20, 2026

Bronchiectasis Phenotype Identification Model

An observational study in Bronchiectasis, Non-cystic Fibrosis Bronchiectasis and Bronchiectasis With Acute Exacerbation, sponsored by Assiut University. Recruiting at 1 site in Egypt. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-05-20.

Sponsored by Assiut University · Observational

From the registry’s dates

  • Started Sep 2025; still recruiting 1 year 2 months later.
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
750
Ages
18 Years and older
Sex
All
01

Study summary

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.

Read the detailed description

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.

02

Conditions studied

  • Bronchiectasis
  • Non-cystic Fibrosis Bronchiectasis
  • Bronchiectasis With Acute Exacerbation

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Keywords

  • Non-cystic fibrosis bronchiectasis (NCFB)
  • Bronchiectasis
  • Bronchiectasis Phenotype Identification Model (BPIM)
  • Bronchiectasis exacerbation
  • Exacerbation risk
  • One-year exacerbation risk
  • Baseline risk prediction
  • Disease-signature model
  • Prospective observational cohort
  • Development-validation study
  • Latent class trajectory analysis (LCTA)
  • supervised phenotype classifier
03

In context

Bronchiectasis

404 studies on the registry are indexed under Bronchiectasis; 125 are open to participants now.

This study's planned enrollment of 750 is above the median of 160 across 137 observational studies indexed under Bronchiectasis.

Browse Bronchiectasis studies →

Lead sponsor

Assiut University is the lead sponsor of 5,078 studies on the registry; 2,178 are open to participants now.

Of its 14 completed or terminated interventional studies of FDA-regulated products, 0 (0%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study 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.

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • 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.
  • Ability to undergo routine clinical, functional, radiological, oxygenation, and inflammatory assessment according to the study protocol.
  • Ability to complete planned longitudinal follow-up required for latent class trajectory analysis (LCTA) and Bronchiectasis Phenotype Identification Model (BPIM) validation.
  • Written obtained from the patient or legal representative.

Exclusion criteria

Exclusion Criteria:

  • 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.
  • Active or terminal non-respiratory illness expected to prevent planned follow-up.
  • Acute life-threatening illness preventing safe enrollment or reliable baseline assessment.
  • Recent major thoracic surgery or acute thoracic trauma interfering with baseline respiratory assessment.
  • Inability to complete required baseline disease-signature assessment according to the Bronchiectasis Phenotype Identification Model (BPIM) protocol.
  • Inability or unwillingness to complete planned longitudinal follow-up.
  • Refusal to participate.
Terms in these criteria, in plain language(2)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

Cancer (malignancy)

Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.

Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.

05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
750 participants (estimated)
Patient registry
No

Groups and cohorts

  • Development Cohort

    Adults with clinically and radiologically confirmed non-cystic fibrosis bronchiectasis (NCFB) assigned to the analytical development cohort. This 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 using the locked baseline disease-signature architecture. No treatment, medication, intervention, exposure, or management strategy is assigned by the study protocol.

  • Validation Cohort

    Adults with clinically and radiologically confirmed non-cystic fibrosis bronchiectasis (NCFB) assigned to the analytical validation cohort. This cohort will be used only to evaluate the locked Bronchiectasis Phenotype Identification Model (BPIM) classifier after training in the development cohort. No validation-stage refitting, recalibration, predictor substitution, phenotype relabeling, threshold retuning, or post hoc classifier rescue will be performed. No treatment, medication, intervention, exposure, or management strategy is assigned by the study protocol.

06

What researchers measure

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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

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.

  5. Discrimination Performance of the Bronchiectasis Phenotype Identification Model

    Assessment of discrimination performance of the Bronchiectasis Phenotype Identification Model (BPIM) classifier for prediction of accepted latent class trajectory analysis (LCTA)-derived phenotype classes. For two-class solutions, discrimination will be assessed using area under the receiver operating characteristic curve. For three-class or four-class solutions, discrimination will be assessed using one-versus-rest or multiclass area under the receiver operating characteristic curve where applicable. Higher values indicate better discrimination performance. Unit of Measure: Area under the receiver operating characteristic curve, 0 to 1 scale.

    Time frame: Baseline to 12 months follow-up.

  6. Ablation Analysis of Bronchiectasis Phenotype Identification Model Input Domains Using Classification Accuracy Difference

    Assessment of change in Bronchiectasis Phenotype Identification Model (BPIM) classification accuracy after sequential removal of individual baseline disease-signature domains from the classifier. The full locked baseline disease-signature architecture will remain the primary classifier regardless of ablation findings. Larger decreases in accuracy after removing a domain indicate greater contribution of that domain to phenotype classification. Unit of Measure: Difference in classification accuracy, percentage points

    Time frame: Baseline to 12 months follow-up.

  7. Longitudinal Mixed-Effects Modeling of Forced Expiratory Volume in One Second Percent Predicted by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of repeated forced expiratory volume in one second percent predicted (FEV1% predicted) measurements according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class using longitudinal mixed-effects modeling. This analysis will evaluate whether FEV1% predicted trajectory differs across accepted BPIM phenotype classes during follow-up. Lower or declining FEV1% predicted indicates worsening airflow limitation and worse functional trajectory. Unit of Measure: FEV1% predicted percentage points

    Time frame: Baseline to 12 months follow-up.

  8. Longitudinal Mixed-Effects Modeling of Resting Room-Air Oxygen Saturation by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of repeated resting room-air oxygen saturation measured by pulse oximetry (SpO2) according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class using longitudinal mixed-effects modeling. This analysis will evaluate whether resting room-air SpO2 trajectory differs across accepted BPIM phenotype classes during follow-up. Lower or declining SpO2 indicates worse oxygenation reserve. Unit of Measure: SpO2 percentage points

    Time frame: Baseline to 12 months follow-up.

  9. Longitudinal Mixed-Effects Modeling of C-Reactive Protein by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of repeated C-reactive protein (CRP) measurements according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class using longitudinal mixed-effects modeling. This analysis will evaluate whether CRP trajectory differs across accepted BPIM phenotype classes during follow-up. Higher or increasing CRP indicates greater systemic inflammatory activity. Unit of Measure: Milligrams per liter (mg/L)

    Time frame: Baseline to 12 months follow-up.

  10. Longitudinal Mixed-Effects Modeling of Neutrophil-to-Lymphocyte Ratio by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of repeated neutrophil-to-lymphocyte ratio (NLR) measurements according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class using longitudinal mixed-effects modeling. Neutrophil-to-lymphocyte ratio (NLR) is calculated as absolute neutrophil count divided by absolute lymphocyte count. Higher or increasing NLR indicates greater neutrophilic inflammatory activity. Unit of Measure: Ratio, unitless

    Time frame: Baseline to 12 months follow-up.

  11. Advanced Survival Modeling for Time to First Bronchiectasis Exacerbation by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of time from baseline to first bronchiectasis exacerbation across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes using survival modeling. Shorter time to first exacerbation indicates earlier clinical deterioration. Unit of Measure: Hazard ratio.

    Time frame: Baseline to 12 months follow-up.

  12. Advanced Survival Modeling for Time to Severe Bronchiectasis Exacerbation Requiring Hospitalization by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of time from baseline to first severe bronchiectasis exacerbation requiring hospitalization across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes using survival modeling. Shorter time to severe exacerbation indicates earlier severe clinical deterioration. Unit of Measure: Hazard ratio.

    Time frame: Baseline to 12 months follow-up.

  13. Advanced Survival Modeling for Time to Bronchiectasis-Related Hospital Admission by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of time from baseline to first bronchiectasis-related hospital admission across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes using survival modeling. Shorter time to hospitalization indicates earlier clinically severe disease instability. Unit of Measure: Hazard ratio.

    Time frame: Baseline to 12 months follow-up.

  14. Joint Longitudinal-Survival Modeling of Forced Expiratory Volume in One Second Percent Predicted and Time to First Bronchiectasis Exacerbation

    Assessment of the association between longitudinal forced expiratory volume in one second percent predicted (FEV1% predicted) trajectory and time to first bronchiectasis exacerbation using joint longitudinal-survival modeling. This analysis is supportive and will not define the accepted latent class trajectory analysis (LCTA) solution or Bronchiectasis Phenotype Identification Model (BPIM) classifier. Unit of Measure: Hazard ratio

    Time frame: Baseline to 12 months follow-up.

  15. Joint Longitudinal-Survival Modeling of Resting Room-Air Oxygen Saturation and Time to First Bronchiectasis Exacerbation

    Assessment of the association between longitudinal resting room-air oxygen saturation measured by pulse oximetry (SpO2) trajectory and time to first bronchiectasis exacerbation using joint longitudinal-survival modeling. This analysis is supportive and will not define the accepted latent class trajectory analysis (LCTA) solution or Bronchiectasis Phenotype Identification Model (BPIM) classifier. Unit of Measure: Hazard ratio

    Time frame: Baseline to 12 months follow-up.

  16. Joint Longitudinal-Survival Modeling of C-Reactive Protein and Time to First Bronchiectasis Exacerbation

    Assessment of the association between longitudinal C-reactive protein (CRP) trajectory and time to first bronchiectasis exacerbation using joint longitudinal-survival modeling. This analysis is supportive and will not define the accepted latent class trajectory analysis (LCTA) solution or Bronchiectasis Phenotype Identification Model (BPIM) classifier. Unit of Measure: Hazard ratio

    Time frame: Baseline to 12 months follow-up.

  17. Joint Longitudinal-Survival Modeling of Neutrophil-to-Lymphocyte Ratio and Time to First Bronchiectasis Exacerbation

    Assessment of the association between longitudinal neutrophil-to-lymphocyte ratio (NLR) trajectory and time to first bronchiectasis exacerbation using joint longitudinal-survival modeling. Neutrophil-to-lymphocyte ratio (NLR) is calculated as absolute neutrophil count divided by absolute lymphocyte count. This analysis is supportive and will not define the accepted latent class trajectory analysis (LCTA) solution or Bronchiectasis Phenotype Identification Model (BPIM) classifier. Unit of Measure: Hazard ratio

    Time frame: Baseline to 12 months follow-up.

  18. Dynamic Change in Forced Expiratory Volume in One Second Percent Predicted by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of change in forced expiratory volume in one second percent predicted (FEV1% predicted) from baseline to follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Change will be calculated as follow-up value minus baseline value. Lower or declining FEV1% predicted indicates worse functional trajectory. Unit of Measure: Percentage points.

    Time frame: Baseline to 12 months follow-up.

  19. Dynamic Change in Resting Room-Air Oxygen Saturation by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of change in resting room-air oxygen saturation measured by pulse oximetry (SpO2) from baseline to follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Change will be calculated as follow-up value minus baseline value. Lower or declining SpO2 indicates worse oxygenation reserve. Unit of Measure: Percentage points.

    Time frame: Baseline to 12 months follow-up.

  20. Dynamic Change in C-Reactive Protein by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of change in C-reactive protein (CRP) from baseline to follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Change will be calculated as follow-up value minus baseline value. Higher or increasing CRP indicates greater systemic inflammatory activity. Unit of Measure: Milligrams per liter (mg/L).

    Time frame: Baseline to 12 months follow-up.

  21. Dynamic Change in Neutrophil-to-Lymphocyte Ratio by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of change in neutrophil-to-lymphocyte ratio (NLR) from baseline to follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Change will be calculated as follow-up value minus baseline value. Higher or increasing NLR indicates greater neutrophilic inflammatory activity. Unit of Measure: Unitless ratio.

    Time frame: Baseline to 12 months follow-up.

  22. Dynamic Change in Modified Reiff Score by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of change in Modified Reiff score from baseline to follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class, where repeat imaging is clinically available. This contextual analysis will not define the primary latent class trajectory analysis (LCTA) solution or the primary Bronchiectasis Phenotype Identification Model (BPIM) classifier. The Modified Reiff score assesses radiological bronchiectasis extent and bronchial dilatation severity. Higher or increasing Modified Reiff score indicates greater structural radiological bronchiectasis burden or progression. Unit of Measure: Score change on Modified Reiff score scale.

    Time frame: Baseline to 12 months follow-up.

  23. Occupancy Distribution of Bronchiectasis Phenotype Identification Model Phenotype Classes

    Assessment of the distribution of participants across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes. This analysis describes phenotype occupancy within the analyzable cohort. Unit of Measure: Percentage of participants.

    Time frame: Baseline to 12 months follow-up.

  24. Class-Membership Probability of Bronchiectasis Phenotype Identification Model Phenotype Classes

    Assessment of predicted class-membership probabilities for accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes. Higher probability indicates greater certainty of predicted phenotype membership. Unit of Measure: Probability, 0 to 1 scale.

    Time frame: Baseline to 12 months follow-up.

  25. Modified Medical Research Council Dyspnea Scale by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of dyspnea burden using the Modified Medical Research Council (mMRC) dyspnea scale across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes where complete data are available. The Modified Medical Research Council (mMRC) dyspnea scale ranges from 0 to 4, with higher scores indicating greater dyspnea burden and worse functional symptom status. This analysis is contextual and will not define the Bronchiectasis Phenotype Identification Model (BPIM) input engine or accepted latent class trajectory analysis (LCTA) solution. Unit of Measure: Modified Medical Research Council (mMRC) dyspnea score, 0 to 4 scale.

    Time frame: Baseline to 12 months follow-up.

  26. Bronchiectasis Severity Index by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of Bronchiectasis Severity Index (BSI) values or categories across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes where complete data are available. This analysis is contextual and will not define the Bronchiectasis Phenotype Identification Model (BPIM) input engine or accepted latent class trajectory analysis (LCTA) solution. Higher scores indicate greater bronchiectasis severity or risk according to the respective scoring system. Unit of Measure: Score on the BSI scale, points

    Time frame: Baseline to 12 months follow-up.

  27. FACED Score by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of FACED score values or categories across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes where complete data are available. This analysis is contextual and will not define the Bronchiectasis Phenotype Identification Model (BPIM) input engine or accepted latent class trajectory analysis (LCTA) solution. Higher scores indicate greater bronchiectasis severity or risk according to the respective scoring system. Unit of Measure: Score on the FACED scale, points.

    Time frame: Baseline to 12 months follow-up.

  28. E-FACED Score by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of E-FACED score values or categories across accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype classes where complete data are available. This analysis is contextual and will not define the Bronchiectasis Phenotype Identification Model (BPIM) input engine or accepted latent class trajectory analysis (LCTA) solution. Higher scores indicate greater bronchiectasis severity or risk according to the respective scoring system. Unit of Measure: Score on the E-FACED scale, points.

    Time frame: Baseline to 12 months follow-up.

  29. Number of Bronchiectasis-Related Outpatient or Emergency Healthcare Visits by Bronchiectasis Phenotype Identification Model Phenotype Class

    Assessment of the number of bronchiectasis-related outpatient or emergency healthcare visits during follow-up according to accepted Bronchiectasis Phenotype Identification Model (BPIM) phenotype class. Higher visit count indicates greater healthcare-use burden and greater clinical instability. This analysis is contextual and will not define the Bronchiectasis Phenotype Identification Model (BPIM) input engine or accepted latent class trajectory analysis (LCTA) solution. Unit of Measure: Number of visits.

    Time frame: Baseline to 12 months follow-up.

07

Study locations

1 of 1 sites recruiting
08

References and documents

Individual participant data

Plan to share: Yes — De-identified individual participant data may be shared only upon reasonable scientific request and after approval by the principal investigator, Faculty of Medicine, Assiut University, and the relevant ethics committee when applicable. Data sharing will be restricted to approved scientific purposes related to non-cystic fibrosis bronchiectasis (NCFB), phenotype classification, latent class trajectory analysis (LCTA), or supervised prediction research. No directly identifiable participant data will be shared. The Bronchiectasis Phenotype Identification Model (BPIM) framework, analytical code, model coefficients, calculators, and related intellectual materials remain protected and are not automatically shared with participant data.

Supporting information: Study protocol, Statistical analysis plan, Informed consent form

Time frame: Beginning 12 months after publication of the primary study results and for 3 years thereafter.

Access criteria: Access may be granted to qualified researchers submitting a methodologically sound proposal related to non-cystic fibrosis bronchiectasis (NCFB), phenotype classification, latent class trajectory analysis (LCTA), supervised prediction modeling, or respiratory translational research. Requests require approval by the principal investigator, Faculty of Medicine, Assiut University, and the relevant ethics committee when applicable. Approved requesters must sign a data use agreement covering confidentiality, restricted use, data security, no re-identification, no unauthorized redistribution, no commercial use, proper acknowledgement, and compliance with ethical and institutional regulations. Code and protected implementation materials require separate written authorization.

Data sharing details ↗ · doi.org

09

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Started Sep 2025 (actual). Primary completion is estimated for Nov 2026, 13 months after the start.

Of 62 observational studies under Bronchiectasis, half reached primary completion within 34 months of starting (the median), counting those still running; a quarter within 12. This study's planned 13 months is below that.

How these figures are worked out, and which studies are left out of them.

Registered
May 15, 2026
First posted
May 20, 2026
StartActual
Sep 11, 2025
Primary completionEst.
Nov 1, 2026
CompletionEst.
Dec 1, 2026
Last update
May 20, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on May 20, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07599969
Lead sponsor
Assiut University
Responsible party
Ahmad Shaddad (Associate Professor, Assiut University) — Principal investigator
First posted
May 20, 2026
Start date
Sep 11, 2025
Primary completion
Nov 1, 2026 (estimated)
Completion
Dec 1, 2026 (estimated)
Last update
May 20, 2026

Study contacts

Ahmad M Shaddad, MD
Contact
shaddad_ahmad@aun.edu.eg
+201111171930
Ahmad M Shaddad, MD
principal investigator · Assiut University
Aliae A. Hussien, MD
principal investigator · Assiut University
Maiada K. Hashem, MD
principal investigator · Assiut University
Alaa S. Ali, MD
principal investigator · Assiut University

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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