Zuohong Wu1, Tingting Huang1, Shiqi Zhang1, Deyun Cheng1, Weimin Li1, Bojiang Chen2. 1. Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, No. 37, Guo Xue Alley, Chengdu, 610041, Sichuan, China. 2. Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, No. 37, Guo Xue Alley, Chengdu, 610041, Sichuan, China. cjhcbj@gmail.com.
Abstract
PURPOSE: Lung cancer is the leading cause of cancer death and there have been clinical prediction models. This study aimed to evaluate the diagnostic performance of published models and create new models to evaluate the probability of malignant solitary pulmonary nodules (SPNs) in Chinese population. METHODS: We consecutively enrolled 2061 patients with SPNs from West China Hospital between January 2008 and December 2016, each SPN was pathologically confirmed. First, four published prediction models, Mayo clinic model, Veterans Affairs (VA) model, Brock model and People's Hospital of Peking University (PEH) model were validated in our patients. Then, utilizing logistic regression, decision tree and random forest (RF), we developed three new models and internally validated them. RESULTS: Area under the receiver operating characteristic curve (AUC) values of four published models were as follows: Mayo 0.705 (95% CI 0.658-0.752, n = 726), VA 0.64 6 (95% CI 0.598-0.695, n = 800), Brock 0.575 (95% CI 0.502-0.648, n = 550) and PEH 0.675 (95% CI 0.627-0.723, n = 726). Logistic regression model, decision tree model and RF model were developed, AUC values of these models were 0.842 (95% CI 0.778-0.906), 0.734 (95% CI 0.647-0.821), 0.851 (95% CI 0.789-0.914), respectively. CONCLUSION: The four published lung cancer prediction models do not apply to our population, and we have established new models that can be used to predict the probability of malignant SPNs.
PURPOSE:Lung cancer is the leading cause of cancer death and there have been clinical prediction models. This study aimed to evaluate the diagnostic performance of published models and create new models to evaluate the probability of malignant solitary pulmonary nodules (SPNs) in Chinese population. METHODS: We consecutively enrolled 2061 patients with SPNs from West China Hospital between January 2008 and December 2016, each SPN was pathologically confirmed. First, four published prediction models, Mayo clinic model, Veterans Affairs (VA) model, Brock model and People's Hospital of Peking University (PEH) model were validated in our patients. Then, utilizing logistic regression, decision tree and random forest (RF), we developed three new models and internally validated them. RESULTS: Area under the receiver operating characteristic curve (AUC) values of four published models were as follows: Mayo 0.705 (95% CI 0.658-0.752, n = 726), VA 0.64 6 (95% CI 0.598-0.695, n = 800), Brock 0.575 (95% CI 0.502-0.648, n = 550) and PEH 0.675 (95% CI 0.627-0.723, n = 726). Logistic regression model, decision tree model and RF model were developed, AUC values of these models were 0.842 (95% CI 0.778-0.906), 0.734 (95% CI 0.647-0.821), 0.851 (95% CI 0.789-0.914), respectively. CONCLUSION: The four published lung cancer prediction models do not apply to our population, and we have established new models that can be used to predict the probability of malignant SPNs.
Entities:
Keywords:
Chinese population; Lung cancer; Prediction model; Solitary pulmonary nodule
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