Predictive Factors for Chronic Rejection in Lung Transplant Recipients: COLT Study

2014-07-24 14:11:28 | BioPortfolio


Obliterative Bronchiolitis (OB) is the major cause of long-term lung allograft loss for patients with end stage pulmonary diseases like cystic fibrosis. Numerous cells and proteins are implicated in this process, which have never been studied prospectively in a multicentric longitudinal cohort. The aim of this study is to detect predictive risk factors of OB through a national multicentric cohort of 500 newly transplanted recipients (COLT). COLT will consist in a large database, associated with a recipient bio-collection, and specific projects using these resources. COLT will aggregate all the 10 French centres of pulmonary transplantation. Patient will be followed-up during 5 years. Blood samples will be obtained. Induced sputum, bronchoalveolar lavage fuid, exhaled breath condensate and trans bronchial biopsies will be also taken. T cells, known to be involved in chronic rejection will be studied, and genomic, microarray and proteomic approaches will be used to detect further predictive factors.COLT will prove molecular markers to be predictive of early OB, before the development of severe airway obstruction and will allow the identification of patients at high risk of OB. COLT will identify potential targets for future treatments of OB. This collaborative project makes research and clinical teams working together, and creates the conditions of a long term network, extendable to other laboratories with new projects and additional European transplant centres.

Study Design

Control: Uncontrolled, Intervention Model: Single Group Assignment, Masking: Open Label


Chronic Rejection


Study of predictive factors


CHU Nantes




Nantes University Hospital

Results (where available)

View Results


Published on BioPortfolio: 2014-07-24T14:11:28-0400

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Medical and Biotech [MESH] Definitions

In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.

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Statistical models used in survival analysis that assert that the effect of the study factors on the hazard rate in the study population is multiplicative and does not change over time.

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