TY - JOUR T1 - Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data JF - ERJ Open Research JO - erjor DO - 10.1183/23120541.00077-2015 VL - 2 IS - 1 SP - 00077-2015 AU - Esther I. Metting AU - Johannes C.C.M. in ’t Veen AU - P.N. Richard Dekhuijzen AU - Ellen van Heijst AU - Janwillem W.H. Kocks AU - Jacqueline B. Muilwijk-Kroes AU - Niels H. Chavannes AU - Thys van der Molen Y1 - 2016/01/01 UR - http://openres.ersjournals.com/content/2/1/00077-2015.abstract N2 - The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population.Data from 9297 primary care patients (45% male, mean age 53±17 years) with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD) service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215).Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS) patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%).Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool.A real-life diagnostic decision tree that can be implemented in digital decision-making programmes http://ow.ly/VnHut ER -