S74 Assessing the diagnostic accuracy of the British Thoracic Society algorithm for investigation of solid pulmonary nodules
Published on Dec 1, 2015in Thorax8.834
· DOI :10.1136/THORAXJNL-2015-207770.80
Background The British Thoracic Society guidelines (2015) on the investigation and management of pulmonary nodules recommend the use of two risk prediction tools to assess the likelihood of malignancy in solid pulmonary nodules (Brock model following initial CT and the model described by Herder et al . following PET-CT). Management strategies are suggested on the basis of these risk assessments. The aim of this study was to assess the performance of this algorithm in patients with solid pulmonary nodules recruited from a UK teaching hospital. Method Patients with solid pulmonary nodules (4–30 mm) were retrospectively identified from the lung cancer MDT and a nodule follow-up clinic (n = 221). All patients had a final diagnosis confirmed by histology or radiological stability on 2-year follow up. Results The median age was 69 years. The prevalence of malignancy was 37.1% (29.9% primary lung cancer, 7.2% metastatic disease). 25 patients where PET-CT was recommended by the guideline but did not occur were excluded from subsequent analysis. Ten patients had nodules CT surveillance was recommended for 106 patients (37 with nodule Surgical/non-surgical treatment was recommended for 58 patients where the malignant risk was >70% following PET-CT. 81% of these patients had primary lung cancer, 10% had metastatic disease and 9% were benign. For nodules with a malignant risk of between 10 and 70% following PET-CT, the guidelines recommend consideration of biopsy with alternatives of CT surveillance or surgical resection depending on patient preference and fitness. Of the 22 patients with nodules in this range, 36% were benign, 55% primary lung cancer and 9% metastatic disease. Conclusion The solid nodule algorithm from the BTS guidelines shows good accuracy in discriminating benign from malignant nodules, recommending appropriate management in a high proportion of cases. Further studies should evaluate this and the other management algorithms with prospectively collected data.