title: Chemotherapy-induced neutropenia during adjuvant treatment for cervical cancer patients: development and validation of a prediction model.
abstract: An artificial neuron network (ANN) model combining both the genetic risk factors and clinical factorsmay be effective in prediction of chemotherapy-induced adverse events.
  
  
  OBJECTIVE
  To identify genetic factors and clinical factors associated with bone marrow suppression in cervical cancer patient, and to build a model for chemotherapy-induced neutropenia prediction.
  
  
  METHODS
  We performed a genome wide association study on a cohort to identify genetic determinants. Samples were genotyped using the Axiom CHB 1.0. The primary analyses focused on the scan of 657178 single-nucleotide polymorphisms (SNPs). Artificial neural network were used to integrating clinical factors and genetic factors to predict the occurrence of neutropenia.
  
  
  RESULTS
  32 variants associated with neutropenia in the patients after chemotherapy were found (P<1 × 10(-4)). During internal validation and external validation, artificial neural network performed well in predicting neutropenia with considerable accuracy, which is 88.9% and 81.7% respectively. ROC analysis had acceptable areas under the curve of 0.897 for the internal validation sample and 0.782 for the external validation sample.
  
  
  CONCLUSIONS
  Neutropenia may be associated with both genetic factors and clinical factors. Our study found that the artificial neural networks model based on the multiple risk factors jointly, can effectively predict the occurring of neutropenia, which provides some guidance before the starting of chemotherapy.
authors.affiliation: Department of Gynecology & Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430030, Hubei, China.
authors.forename: Kecheng
authors.initials: K
authors.lastname: Huang
authors.affiliation: Department of Gynecology & Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430030, Hubei, China.
authors.forename: Aiyue
authors.initials: A
authors.lastname: Luo
authors.affiliation: Department of Gynecology & Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430030, Hubei, China.
authors.forename: Xiong
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Gynecology & Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430030, Hubei, China.
authors.forename: Shuang
authors.initials: S
authors.lastname: Li
authors.affiliation: Department of Gynecology & Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430030, Hubei, China.
authors.forename: Shixuan
authors.initials: S
authors.lastname: Wang
keywords: Cervical cancer; artificial neuron network; genome-wide association study; platinum; single-nucleotide polymorphism