title: Assessment of the cancer risk factors of solitary pulmonary nodules.
abstract: There are no large samples or exact prediction models for assessing the cancer risk factors of solitary pulmonary nodules (SPNs) in the Chinese population. We retrospectively analyzed the clinical and imaging data of patients with SPNs who underwent computer tomography guided needle biopsy in our hospital from Jan 1st of 2011 to March 30th of 2016. These patients were divided into a development data set and a validation data set. These groups included 1078 and 344 patients, respectively. A prediction model was developed from the development data set and was validated with the validation data set using logistic regression. The predictors of cancer in our model included female gender, age, pack-years of smoking, a previous history of malignancy, nodule size, lobulated and spiculated edges, lobulation alone and spiculation alone. The Area Under the Curves, sensitivity and specificity of our model in the development and validation data sets were significantly higher than those of the Mayo model and VA model (p < 0.001). We established the largest sampling risk prediction model of SPNs in a Chinese cohort. This model is particularly applicable to SPNs > 8 mm in size. SPNs in female patients, as well as SPNs featuring a combination of lobulated and spiculated edges or lobulated edges alone, should be evaluated carefully due to the probability that they are malignant.
authors.affiliation: Interventional Radiology Department, the First Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Li
authors.initials: L
authors.lastname: Yang
authors.affiliation: Institute of Respiratory Diseases, the Second Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Qiao
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Institute of Respiratory Diseases, the Second Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Li
authors.initials: L
authors.lastname: Bai
authors.affiliation: Interventional Radiology Department, the First Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Ting-Yuan
authors.initials: TY
authors.lastname: Li
authors.affiliation: Interventional Radiology Department, the First Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Chuang
authors.initials: C
authors.lastname: He
authors.affiliation: Institute of Respiratory Diseases, the Second Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Qian-Li
authors.initials: QL
authors.lastname: Ma
authors.affiliation: Interventional Radiology Department, the First Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Liang-Shan
authors.initials: LS
authors.lastname: Li
authors.affiliation: Interventional Radiology Department, the First Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Xue-Quan
authors.initials: XQ
authors.lastname: Huang
authors.affiliation: Institute of Respiratory Diseases, the Second Hospital of the Third Military Medical University, Chongqing 400038, China.
authors.forename: Gui-Sheng
authors.initials: GS
authors.lastname: Qian
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D012307:Risk Factors; D003074:Solitary Pulmonary Nodule / Q000150:complications* / Q000473:pathology; D055815:Young Adult
keywords: malignancy; model; pulmonary nodule; risk factor; solitary