Ruiqi Wang1,2, Guilan Xie1,2, Li Shang1,2, Cuifang Qi1, Liren Yang1,2, Liyan Huang1,2, Danyang Li2,3,4, Wenfang Yang1. 1. Department of Obstetrics & Gynecology, Maternal & Child Health 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. Department of Women's & Children's Health, Karolinska Institutet & Child & Adolescent Psychiatry, Stockholm Health Care Services, Stockholm County Council, Stockholm, 17177, Sweden. 4. Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17177, Sweden.
Abstract
Aim: To develop and internally validate nomograms to predict the overall survival (OS) and the cancer-specific survival (CSS) of patients with epithelial ovarian cancer (EOC). Methods: A total of 9001 EOC patients diagnosed between 2010 and 2013 were randomly divided into the training (n = 6301) and validation (n = 2700) cohorts. Nomogram and bootstrap validation were used to assess the predictive values of the models, including discrimination, calibration and clinical benefit. Results: In the validation cohort, the concordance statistic values were 0.733 for OS and 0.747 for CSS. Calibration plots and decision curve analyses demonstrated moderate accuracy and clinical applicability. Conclusion: Nomograms were user-friendly tools for guiding clinical treatment and estimating prognosis.
RCT Entities:
Aim: To develop and internally validate nomograms to predict the overall survival (OS) and the cancer-specific survival (CSS) of patients with epithelial ovarian cancer (EOC). Methods: A total of 9001 EOC patients diagnosed between 2010 and 2013 were randomly divided into the training (n = 6301) and validation (n = 2700) cohorts. Nomogram and bootstrap validation were used to assess the predictive values of the models, including discrimination, calibration and clinical benefit. Results: In the validation cohort, the concordance statistic values were 0.733 for OS and 0.747 for CSS. Calibration plots and decision curve analyses demonstrated moderate accuracy and clinical applicability. Conclusion: Nomograms were user-friendly tools for guiding clinical treatment and estimating prognosis.