TY - JOUR T1 - Updates in using a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples JF - Breathe JO - Breathe DO - 10.1183/20734735.0067-2020 VL - 16 IS - 3 SP - 200067 AU - Andrea Crespo AU - Tiago Alfaro AU - Vivien Somogyi AU - Michael Kreuter Y1 - 2020/09/01 UR - http://breathe.ersjournals.com/content/16/3/200067.abstract N2 - The most common fibrosing interstitial lung disease (ILD) is idiopathic pulmonary fibrosis (IPF), with an incidence of 14–60 cases per 100 000 inhabitants per year in North America [1] and 3–9 cases per 100 000 per year in Europe [2]. IPF is a chronic, progressive fibrosing interstitial lung disease characterised by continued scarring of the lung parenchyma and associated with a steady worsening of respiratory symptoms, quality of life and pulmonary function, ultimately leading to death [1, 3], and a median survival of 3–5 years from the time of diagnosis [4, 5]. A precise diagnosis of the underlying ILD entity is essential for prognostication and choice of therapy as treatments differ between ILD subtypes, including that some drugs may be detrimental to an IPF patient. However, the diagnosis of ILD is sometimes difficult, partly imprecise, and frequently characterised by delay, misdiagnosis, use of costly and invasive procedures, and high use of healthcare resources.A molecular classifier using a machine-learning algorithm based on genomic data could provide an objective method to aid clinicians and multidisciplinary teams to establish the diagnosis of IPF in less-invasive transbronchial lung biopsy samples https://bit.ly/2QLdWim ER -