Development and validation of a risk prediction model for post-traumatic stress disorder among Chinese breast cancer survivors

This study thoroughly assesses the factors affecting the posttraumatic stress disorder (PTSD) in patients with breast cancers from a multidimensional perspective according to the theory of unpleasant symptoms (TOUS). Additionally, it develops a nomogram prediction model tailored for this group. A cross-section analysis involving seven major hospitals in northern Anhui Province was performed to collect data from 1135 breast cancer survivors. The self-reported Posttraumatic Stress Disorder Checklist-Civilian Version (PCL-C) was applied to evaluate PTSD. Multiple logistic regression analysis was conducted for identifying significant predictive factors of PTSD, and these predictive factors were used to develop and validate a nomogram on an independent validation cohort comprising 481 patients with breast cancers. In the training cohort, 274 patients with breast cancers (24.1%) were identified as having PTSD. The factors independently associated with PTSD included menopause, blood cholesterol levels, fear of cancer progression, psychological distress, depression, social support, and smoking status (all P < 0.05). The area under the curve (AUC) values for training and validation cohorts were 0.889 and 0.770, respectively, indicating strong predictive performance. The calibration plot showed optimal agreement of the observed value with the predicted value, and the decision curve analysis demonstrated strong clinical utility of the nomogram. This study explores the factors affecting PTSD in patients with breast cancers based on the physiological, psychological, and background dimensions of TOUS, and firstly constructs a model for predicting PTSD risk in patients with breast cancers, which demonstrates satisfactory predictive ability and fills a gap in this research field.