Jin Yang1,2, Guoxiang Tian3, Zhenyu Pan1,2,4, Fanfan Zhao1,2, Xiaojie Feng1,2, Qingqing Liu1,2, Jun Lyu1,2. 1. Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China. 2. School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China. 3. Seventh Medical Center, PLA General Hospital, Beijing, 100853, PR China. 4. Department of Pharmacy, The Affiliated Children Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China.
Abstract
Aim: To integrate multiple independent risk factors to establish prognostic nomograms for better predicting overall survival and disease-specific survival in patients with cervical cancer receiving radiation therapy. Materials & methods: Cox analysis used to construct nomograms. The C-index, time-dependent receiver operating characteristic and calibration plots were used to evaluate the performance. The discrimination abilities were compared using the decision curve analysis, net reclassification improvement and integrated discrimination improvement. Results: After randomization, 2869 and 1230 cervical cancer patients were included in the training and validation sets, respectively. Nomograms that incorporated all of the significant independent factors for predicting the 3- and 5-year overall survival and disease-specific survival in the training cohort were established. Conclusion: Compared with the International Federation of Gynecology and Obstetrics staging system, the proposed nomograms exhibit superior prognostic discrimination and survival prediction.
Aim: To integrate multiple independent risk factors to establish prognostic nomograms for better predicting overall survival and disease-specific survival in patients with cervical cancer receiving radiation therapy. Materials & methods: Cox analysis used to construct nomograms. The C-index, time-dependent receiver operating characteristic and calibration plots were used to evaluate the performance. The discrimination abilities were compared using the decision curve analysis, net reclassification improvement and integrated discrimination improvement. Results: After randomization, 2869 and 1230 cervical cancerpatients were included in the training and validation sets, respectively. Nomograms that incorporated all of the significant independent factors for predicting the 3- and 5-year overall survival and disease-specific survival in the training cohort were established. Conclusion: Compared with the International Federation of Gynecology and Obstetrics staging system, the proposed nomograms exhibit superior prognostic discrimination and survival prediction.
Authors: Lele Zang; Qin Chen; Xiaozhen Zhang; Xiaohong Zhong; Jian Chen; Yi Fang; An Lin; Min Wang Journal: Cancer Manag Res Date: 2021-12-29 Impact factor: 3.989