Shi M, et al. - By performing this retrospective cohort analysis of patients who had surgical resection for lung cancer between 2009 to 2013, researchers defined a prediction model based on clinical data, routine physical and blood examinations, and molecular markers, given available models for non-small cell lung cancer (NSCLC) patients with complete resection are unsatisfactory. They developed a complete prediction model based on a multivariable Cox regression analysis, using potential prognostic factors. They built a nomogram. In this study including 368 NSCLC patients with R0 resection, the factors that were independently related to poor OS and were suggested in the final multivariable model were: low diffusing capacity of the lung for carbon monoxide, high platelet-to-lymphocyte ratio, histology type of squamous cell carcinoma and others, N > 0 status, high serum carcinoembryonic antigen levels, and postoperative chemotherapy. In this study, the successful development of a nomogram was accomplished based on multivariable analysis, and the differentiation of OS of NSCLC patients based on risk categories could be done using this nomogram. Nevertheless, external validation is still required.