title: A nomogram for predicting the risk of invasive pulmonary adenocarcinoma for patients with solitary peripheral subsolid nodules.
abstract: The subsolid nodule is a common clinical concern. The aim of this study was to construct a nomogram to predict the risk of invasive pulmonary adenocarcinoma in patients with a solitary peripheral subsolid nodule.
  
  
  
  We reviewed the records of 293 patients who had undergone resection of a solitary peripheral subsolid nodule, including the results of pathologic examinations after surgical resection. Clinical parameters and imaging features were analyzed by the use of univariable and multivariable logistic regression analysis. A nomogram to predict the risk of invasive pulmonary adenocarcinoma was constructed and validated with bootstrap resampling.
  
  
  
  Two hundred seventy-three patients were included for analysis; 35 were diagnosed as benign, 3 as atypical adenomatous hyperplasia, 18 as adenocarcinoma in situ, 58 as minimally invasive adenocarcinoma, and 159 as invasive pulmonary adenocarcinoma. After final regression analysis, the computed tomography attenuation, nodule size, spiculation, signs of vascular convergence, pleural tags, and solid proportion were identified and were entered into the nomogram. The nomogram showed a robust discrimination, with an area under the receiver operating characteristic curve of 0.894. The calibration curves for the probability of invasive pulmonary adenocarcinoma showed optimal agreement between the probability as predicted by the nomogram and the actual probability.
  
  
  
  We developed a nomogram that can predict the risk of invasive pulmonary adenocarcinoma for patients with a solitary peripheral subsolid nodule. Validation by the use of bootstrap resampling revealed optimal discrimination and calibration, indicating that the nomogram may have clinical utility. This model has the potential to assist clinicians in making treatment recommendations.
authors.affiliation: Department of Thoracic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China; Department of Thoracic Surgery, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang, China.
authors.forename: Chenghua
authors.initials: C
authors.lastname: Jin
authors.affiliation: Department of Thoracic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Jinlin
authors.initials: J
authors.lastname: Cao
authors.affiliation: Department of Radiology, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Cai
authors.affiliation: Department of Thoracic Surgery, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang, China.
authors.forename: Lijie
authors.initials: L
authors.lastname: Wang
authors.affiliation: Department of Thoracic Surgery, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang, China.
authors.forename: Kai
authors.initials: K
authors.lastname: Liu
authors.affiliation: Department of Thoracic Surgery, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang, China.
authors.forename: Weiyu
authors.initials: W
authors.lastname: Shen
authors.affiliation: Department of Thoracic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China. Electronic address: hujian_med2@163.com.
authors.forename: Jian
authors.initials: J
authors.lastname: Hu
mesh_terms: D000230:Adenocarcinoma; D003657:Decision Making; D006801:Humans; D008175:Lung Neoplasms; D049451:Nomograms; D012189:Retrospective Studies
keywords: invasive adenocarcinoma; nomogram; predictive model; risk factors; solitary pulmonary sub-solid nodules