Dynamic Nomogram Based on the Metastatic Number and Sites and Therapy Strategies Predicting the Prognosis of Patients with Metastatic Cervical Cancer

Abstract

Background Individual survival prediction is of vital importance to optimize the individualized treatment of metastatic cervical cancer (mCC) patients. The goal of this study was to identify the potential risk factors for the survival of mCC patients and construct a nomogram for their prognosis. Methods Medical records of patients with newly diagnosed mCC at the First Affiliated Hospital of Xi’an Jiaotong University were reviewed retrospectively. Risk factors were identified using Cox proportional hazards analysis and Kaplan–Meier curves. Random forest was used to identify factors associated with therapy strategy. Nomogram and dynamic nomogram were established using ‘rms’ and “DynNom” R package. Results A total of 98 patients with mCC were finally identified. In Cox analyses, multiple metastases and concurrent chemoradiotherapy (CCRT) were identified as independent predictors for overall survival (OS). We further explored the prognostic value of metastatic number and sites and therapy strategies for mCC patients by Kaplan–Meier curves. A dynamic nomogram including metastases number and sites (multiple metastases, liver and lymph node (LN) above diaphragm metastases) and chemoradiotherapy strategies (CCRT, postradiotherapy chemotherapy, and radiotherapy to metastatic sites) was constructed for predicting the prognosis of mCC patients. For newly diagnosed patients, we strongly recommended the combination of chemotherapy and definitive pelvic radiotherapy and, if possible, radiation to metastatic site, but CCRT should be implemented with caution. We constructed a dynamic nomogram indicating that patients with younger age, shorter symptom duration, and better laboratory test results are suitable for CCRT. Conclusion Survival analyses showed that the metastatic number and sites and therapy strategies are associated with the prognosis of mCC patients. The CCRT and prognostic nomograms may help clinicians to make better clinical decisions and effectively predict the prognosis for newly diagnosed mCC patients.