OBJECTIVES Lung cancer has a continuously bad prognosis in terms of survival and quality of life, usually because of late detection of malignancies. Given an expected increase in the incidence, overall mortality will increase. Early detection and efficient diagnostic planning may offer additional gain in survival. The diagnostic pathway for patients with suspected lung cancer is characterized by a cascade of different imaging and diagnostic modalities. The main objective of this study is to estimate the health economic impact of diagnostic procedures and the expected gain by  volume-doubling time on low-dose CT as biomarker in suspected lung cancer (NELSON protocol). METHODS A state-transition model is created to simulate the pathway of lung cancer diagnostic procedures, including x-ray, diagnostic CT, PET-CT, bronchoscopy, mediastinoscopy and more. Hospital registries and data from the National Cancer Registry were used to estimate the amount of diagnostic procedures in a cohort of lung cancer patients. Systematic literature search was performed to estimate the diagnostic performance of different modalities. Patient cohort is defined and the pre-test probability for malignancy is estimated through the Swensen criteria. Probabilistic sensitivity analysis is performed using Monte Carlo Simulations. RESULTS Diagnostic procedures for patients with suspected lung cancer can count up to almost €3000 per patient. Pathway was modeled in a microsimulated cohort through Swensen criteria, leading to a mean chance of malignancy of 40%.  Costly steps in the pathway include cervical mediastinoscopy and mutation analysis. Inclusion of NELSON protocol can lead to a reduction in costs. Decision making per patient can reduce overuse of diagnostic modalities. CONCLUSIONS The diagnostic procedure for suspected lung cancer patients is a costly pathway and can be improved with use of the NELSON screening protocol or personalized selection of diagnostic procedures.