title: Predicting distant failure in early stage NSCLC treated with SBRT using clinical parameters.
abstract: The aim of this study is to predict early distant failure in early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT) using clinical parameters by machine learning algorithms.
  
  
  
  The dataset used in this work includes 81 early stage NSCLC patients with at least 6months of follow-up who underwent SBRT between 2006 and 2012 at a single institution. The clinical parameters (n=18) for each patient include demographic parameters, tumor characteristics, treatment fraction schemes, and pretreatment medications. Three predictive models were constructed based on different machine learning algorithms: (1) artificial neural network (ANN), (2) logistic regression (LR) and (3) support vector machine (SVM). Furthermore, to select an optimal clinical parameter set for the model construction, three strategies were adopted: (1) clonal selection algorithm (CSA) based selection strategy; (2) sequential forward selection (SFS) method; and (3) statistical analysis (SA) based strategy. 5-cross-validation is used to validate the performance of each predictive model. The accuracy was assessed by area under the receiver operating characteristic (ROC) curve (AUC), sensitivity and specificity of the system was also evaluated.
  
  
  
  The AUCs for ANN, LR and SVM were 0.75, 0.73, and 0.80, respectively. The sensitivity values for ANN, LR and SVM were 71.2%, 72.9% and 83.1%, while the specificity values for ANN, LR and SVM were 59.1%, 63.6% and 63.6%, respectively. Meanwhile, the CSA based strategy outperformed SFS and SA in terms of AUC, sensitivity and specificity.
  
  
  
  Based on clinical parameters, the SVM with the CSA optimal parameter set selection strategy achieves better performance than other strategies for predicting distant failure in lung SBRT patients.
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Zhiguo
authors.initials: Z
authors.lastname: Zhou
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Michael
authors.initials: M
authors.lastname: Folkert
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Nathan
authors.initials: N
authors.lastname: Cannon
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Puneeth
authors.initials: P
authors.lastname: Iyengar
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Kenneth
authors.initials: K
authors.lastname: Westover
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Hak
authors.initials: H
authors.lastname: Choy
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Robert
authors.initials: R
authors.lastname: Timmerman
authors.affiliation: Department of Clinical Science, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Jingsheng
authors.initials: J
authors.lastname: Yan
authors.affiliation: Department of Clinical Science, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Xian-J
authors.initials: XJ
authors.lastname: Xie
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States.
authors.forename: Steve
authors.initials: S
authors.lastname: Jiang
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, United States. Electronic address: jing.wang@utsouthwestern.edu.
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
mesh_terms: D000368:Aged; D000465:Algorithms; D019540:Area Under Curve; D002289:Carcinoma, Non-Small-Cell Lung / Q000473:pathology / Q000532:radiotherapy*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008175:Lung Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D016571:Neural Networks, Computer; D016634:Radiosurgery; D017211:Treatment Failure
keywords: Clinical parameter; Distant failure; Feature selection; Machine learning; SBRT