Ignite Creation Date:
2025-12-24 @ 9:56 PM
Ignite Modification Date:
2025-12-29 @ 5:56 PM
Study NCT ID:
NCT04680832
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2025-06-18
First Post:
2020-12-11
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Exhaled Breath Analysis Using eNose Technology as a Biomarker for Diagnosis and Disease Progression in Fibrotic ILD
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D011658', 'term': 'Pulmonary Fibrosis'}], 'ancestors': [{'id': 'D017563', 'term': 'Lung Diseases, Interstitial'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}, {'id': 'D005355', 'term': 'Fibrosis'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 600}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2020-11-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-01', 'completionDateStruct': {'date': '2026-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-06-13', 'studyFirstSubmitDate': '2020-12-11', 'studyFirstSubmitQcDate': '2020-12-17', 'lastUpdatePostDateStruct': {'date': '2025-06-18', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-12-23', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Diagnostic accuracy for IPF - CHP', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating IPF from CHP'}, {'measure': 'AUC for IPF - CHP', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating IPF from CHP'}, {'measure': 'AUC for IPF - iNSIP', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating IPF from iNSIP'}, {'measure': 'Diagnostic accuracy for IPF - iNSIP', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating IPF from iNSIP'}, {'measure': 'AUC for IPF - IPAF', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating IPF from IPAF'}, {'measure': 'Diagnostic accuracy for IPF - IPAF', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating IPF from IPAF'}, {'measure': 'Diagnostic accuracy for IPF - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating IPF from CTD-ILD'}, {'measure': 'AUC for IPF - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating IPF from CTD-ILD'}, {'measure': 'Diagnostic accuracy for IPF - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating IPF from unclassifiable ILD'}, {'measure': 'AUC for IPF - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating IPF from unclassifiable ILD'}, {'measure': 'Diagnostic accuracy for CHP - iNSIP', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating CHP from iNSIP'}, {'measure': 'AUC for CHP - iNSIP', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating CHP from iNSIP'}, {'measure': 'Diagnostic accuracy for CHP - IPAF', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating CHP from IPAF'}, {'measure': 'AUC for CHP - IPAF', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating CHP from IPAF'}, {'measure': 'Diagnostic accuracy for CHP - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating CHP from CTD-ILD'}, {'measure': 'AUC for CHP - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating CHP from CTD-ILD'}, {'measure': 'Diagnostic accuracy for CHP - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating CHP from unclassifiable ILD'}, {'measure': 'AUC for CHP - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating CHP from unclassifiable ILD'}, {'measure': 'Diagnostic accuracy for iNSIP - IPAF', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating iNSIP from IPAF'}, {'measure': 'AUC for iNSIP - IPAF', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating iNSIP from IPAF'}, {'measure': 'Diagnostic accuracy for iNSIP - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating iNSIP from CTD-ILD'}, {'measure': 'AUC for iNSIP - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating iNSIP from CTD-ILD'}, {'measure': 'Diagnostic accuracy for iNSIP - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating iNSIP from unclassifiable ILD'}, {'measure': 'AUC for iNSIP - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating iNSIP from unclassifiable ILD'}, {'measure': 'Diagnostic accuracy for IPAF - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating IPAF from CTD-ILD'}, {'measure': 'AUC for IPAF - CTD-ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating IPAF from CTD-ILD'}, {'measure': 'Diagnostic accuracy for IPAF - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating IPAF from unclassifiable ILD'}, {'measure': 'AUC for IPAF - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating IPAF from unclassifiable ILD'}, {'measure': 'Diagnostic accuracy for CTD-ILD - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'Accuracy for differentiating CTD-ILD from unclassifiable ILD'}, {'measure': 'AUC for CTD-ILD - unclassifiable ILD', 'timeFrame': 'Baseline', 'description': 'AUC for differentiating CTD-ILD from unclassifiable ILD'}, {'measure': 'Disease progression', 'timeFrame': '12 months after inclusion', 'description': 'FVC decline in combination with worsening of respiratory symptoms (cough and/or dyspnea) and/or progressive fibrosis on CT scan'}, {'measure': 'Disease progression', 'timeFrame': '24 months after inclusion', 'description': 'FVC decline in combination with worsening of respiratory symptoms (cough and/or dyspnea) and/or progressive fibrosis on CT scan'}, {'measure': 'Diagnostic accuracy of disease progression', 'timeFrame': '6 months after inclusion', 'description': 'Relating disease progression (based on FVC decline, CT scan and/or symptoms) to change in eNose values'}, {'measure': 'Diagnostic accuracy of disease progression', 'timeFrame': '12 months after inclusion', 'description': 'Relating disease progression (based on FVC decline, CT scan and/or symptoms) to change in eNose values'}, {'measure': 'Diagnostic accuracy of disease progression', 'timeFrame': '24 months after inclusion', 'description': 'Relating disease progression (based on FVC decline, CT scan and/or symptoms) to change in eNose values'}, {'measure': 'Worsening of respiratory symptoms (cough and/or dyspnea)', 'timeFrame': '12 months after inclusion', 'description': 'Worsening of respiratory symptoms (cough and/or dyspnea) measured on a visual analogue scale (0-10, 0 no symptoms, 10 most severe symptoms)'}, {'measure': 'Mortality', 'timeFrame': '12 months after inclusion', 'description': 'Deceased subjects'}, {'measure': 'Mortality', 'timeFrame': '24 months after inclusion', 'description': 'Deceased subjects'}, {'measure': 'Therapeutic effect', 'timeFrame': '6 months after start therapy', 'description': 'Relating start of anti-fibrotic medication to change in eNose values'}, {'measure': 'Therapeutic effect', 'timeFrame': '12 months after start therapy', 'description': 'Relating start of anti-fibrotic medication to change in eNose values'}], 'secondaryOutcomes': [{'measure': 'L-PF evaluation', 'timeFrame': '6 months after inclusion', 'description': 'Relating Longitudinal changes in score of L-PF questionnaire to eNose values'}, {'measure': 'L-PF evaluation', 'timeFrame': '6 months after inclusion', 'description': 'Relating Longitudinal changes in score of L-PF questionnaire to lung function values'}, {'measure': 'L-PF evaluation', 'timeFrame': '12 months after inclusion', 'description': 'Relating Longitudinal changes in score of L-PF questionnaire to eNose values'}, {'measure': 'L-PF evaluation', 'timeFrame': '12 months after inclusion', 'description': 'Relating Longitudinal changes in score of L-PF questionnaire to lung function values'}, {'measure': 'L-PF evaluation', 'timeFrame': '24 months after inclusion', 'description': 'Relating Longitudinal changes in score of L-PF questionnaire to eNose values'}, {'measure': 'L-PF evaluation', 'timeFrame': '24 months after inclusion', 'description': 'Relating Longitudinal changes in score of L-PF questionnaire to lung function values'}, {'measure': 'GRoC evaluation', 'timeFrame': '6 months after inclusion', 'description': 'Relating Longitudinal changes in score of Global Rating of Change Scale to eNose values'}, {'measure': 'GRoC evaluation', 'timeFrame': '6 months after inclusion', 'description': 'Relating Longitudinal changes in score of Global Rating of Change Scale to lung function values'}, {'measure': 'GRoC evaluation', 'timeFrame': '12 months after inclusion', 'description': 'Relating Longitudinal changes in score of Global Rating of Change Scale to eNose values'}, {'measure': 'GRoC evaluation', 'timeFrame': '12 months after inclusion', 'description': 'Relating Longitudinal changes in score of Global Rating of Change Scale to lung function values'}, {'measure': 'GRoC evaluation', 'timeFrame': '24 months after inclusion', 'description': 'Relating Longitudinal changes in score of Global Rating of Change Scale to eNose values'}, {'measure': 'GRoC evaluation', 'timeFrame': '24 months after inclusion', 'description': 'Relating Longitudinal changes in score of Global Rating of Change Scale to lung function values'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Pulmonary Fibrosis']}, 'descriptionModule': {'briefSummary': 'The ILDnose study a multinational, multicenter, prospective, longitudinal study in outpatients with pulmonary fibrosis. The aim is to assess the accuracy of eNose technology as diagnostic tool for diagnosis and differentiation between the most prevalent fibrotic interstitial lung diseases. The value of eNose as biomarker for disease progression and response to treatment is also assessed. Besides, validity of several questionnaires for pulmonary fibrosis is investigated.', 'detailedDescription': 'Patients will be included in the study after signing written informed consent. eNose measurements will take place before or after a routine outpatient clinic visit at the same location as the regular visit, ensuring minimal inconvenience for patients. First, patients will be asked to rinse their mouth thoroughly with water three times. Subsequently, exhaled breath analysis will be performed in duplicate with a 1-minute interval. An eNose measurement consists of five tidal breaths, followed by an inspiratory capacity maneuver to total lung capacity, a five second breath hold, and subsequently a slow expiration (flow \\<0.4L/s) to residual volume. The measurements are non-invasive and will cost approximately 5-10 minutes in total, including explanation and informed consent procedure. There are no risks associated with this study and the burden for patients is minimal.\n\nAfter the measurement, patients will complete a short survey about questions relevant for the data analysis (food intake in the last two hours, smoking history, medication use, comorbidities, and symptoms of respiratory infection). In addition, patients will complete the L-PF questionnaire and the Global Rating of Change scale (GRoC). The L-PF questionnaire consists of 21 questions on a 5-point Likert scale about the impact of pulmonary fibrosis on quality of life, and takes about 3 minutes to complete. The GRoC consists of one question on a scale from -7 to 7: were there any changes in your quality of life since your last visit? Symptoms (cough and dyspnea) will be scored on a 10 cm VAS scale from -5 to 5.\n\nNext to eNose measurements, demographic data and physiological parameters of patients will be collected from the medical records at baseline, month 6, and month 12. Parameters such as age, gender, diagnosis, time since diagnosis, comorbidities, medication, pulmonary function (forced vital capacity (FVC) and diffusion capacity of the lung for carbon monoxide (DLCO)), laboratory parameters (i.e. auto-immune antibodies), HRCT pattern, BAL results and if applicable also genetic mutations, will be recorded and stored in an electronic case report form. These parameters will be collected as part of routine daily care, patients will not undergo any additional tests for study purposes. HRCT scans will be re-analysed centrally by an experienced ILD thoracic radiologist. Mortality and lung function parameters will also be collected at 24 months, if this information is available.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Patients with ILD', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n* Patients with a diagnosis of fibrotic ILD, as discussed in a multidisciplinary team meeting (50% incident patients and 50% prevalent patients). Patients are classified as 'incident' if they received a diagnosed in a multidisciplinary team meeting within the past six months. Patients will be required to have fibrosis on a HRCT scan \\<1 year before enrollment in the study defined as reticular abnormality with traction bronchiectasis, with or without honeycombing, as determined by a radiologist. No minimum extent of fibrosis will be required.\n\nExclusion Criteria:\n\n* Alcohol consumption ≤ 12 hours before the measurement\n* Physically not able to perform eNose measurement"}, 'identificationModule': {'nctId': 'NCT04680832', 'acronym': 'ILDnose', 'briefTitle': 'Exhaled Breath Analysis Using eNose Technology as a Biomarker for Diagnosis and Disease Progression in Fibrotic ILD', 'organization': {'class': 'OTHER', 'fullName': 'Erasmus Medical Center'}, 'officialTitle': 'Exhaled Breath Analysis Using eNose Technology as a Biomarker for Diagnosis and Disease Progression in Fibrotic Interstitial Lung Disease', 'orgStudyIdInfo': {'id': 'MEC-2020-0655'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'ILD patients', 'description': 'Patients diagnosed with one of the most prevalent fibrotic ILDs: IPF, CHP, CTD-ILD, iNSIP, IPAF, and unclassifiable ILD (defined as unclassifiable disease at the time of the first MDT).', 'interventionNames': ['Diagnostic Test: Electronic nose']}], 'interventions': [{'name': 'Electronic nose', 'type': 'DIAGNOSTIC_TEST', 'otherNames': ['SpiroNose', 'eNose'], 'description': 'First, patients will be asked to rinse their mouth thoroughly with water three times. Subsequently, exhaled breath analysis will be performed in duplicate with a 1-minute interval. An eNose measurement consists of five tidal breaths, followed by an inspiratory capacity maneuver to total lung capacity, a five second breath hold, and subsequently a slow expiration (flow \\<0.4L/s) to residual volume. The measurements are non-invasive and will cost approximately 5-10 minutes in total, including explanation and informed consent procedure. There are no risks associated with this study and the burden for patients is minimal.', 'armGroupLabels': ['ILD patients']}]}, 'contactsLocationsModule': {'locations': [{'zip': 'NSW 2050', 'city': 'Camperdown', 'state': 'New South Wales', 'country': 'Australia', 'facility': 'Royal Prince Alfred Hospital', 'geoPoint': {'lat': -33.88965, 'lon': 151.17642}}, {'city': 'Lyon', 'country': 'France', 'facility': 'University Lyon 1, Louis Pradel hospital, Lyon. FranceService de pneumologie, hôpital Louis Pradel', 'geoPoint': {'lat': 45.74906, 'lon': 4.84789}}, {'zip': '69126', 'city': 'Heidelberg', 'country': 'Germany', 'facility': 'Thoraxklinik Heidelberg', 'geoPoint': {'lat': 49.40768, 'lon': 8.69079}}, {'zip': '3000 CA', 'city': 'Rotterdam', 'country': 'Netherlands', 'facility': 'Erasmus MC', 'geoPoint': {'lat': 51.9225, 'lon': 4.47917}}, {'zip': 'SW3 6NP', 'city': 'London', 'country': 'United Kingdom', 'facility': 'Royal Brompton Hospital', 'geoPoint': {'lat': 51.50853, 'lon': -0.12574}}], 'overallOfficials': [{'name': 'Marlies S Wijsenbeek, MD PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Erasmus Medical Center'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Erasmus Medical Center', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator, MD PhD', 'investigatorFullName': 'Marlies Wijsenbeek', 'investigatorAffiliation': 'Erasmus Medical Center'}}}}