AUTHOR=Zou YuChi , Yang QianKun , Wu YuTong , Ai HongBo , Yao ZhongXiang , Zhang ChengMin , Luo Fei 

TITLE=Prognosticators and Prognostic Nomograms for Leiomyosarcoma Patients With Metastasis

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.840962

DOI=10.3389/fonc.2022.840962

ISSN=2234-943X

ABSTRACT=Individual survival prediction and risk stratification is of vital importance to optimize the individualized treatment of leiomyosarcoma (LMS) patients with metastasis. This study aimed to identify the prognostic factors for LMS patients with metastasis and establish prognostic models for overall survival (OS) and cancer-specific survival (CSS). The data of LMS patients with metastasis between 2010 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The entire cohort was randomly divided into a training cohort and a validation cohort. The Kaplan-Meier method and Log-rank test were utilized to identify the prognosticators for survival in the whole cohort and in the cohort of distant metastasis. Based on the independent prognostic factors identified from the training cohort, two prognostic nomograms were established. The predictive performances of the developed nomograms were assessed by the methods of receiver operating characteristic (ROC) curves, time-dependent ROC curves, calibration curves, decision curve analysis (DCA). A total of 498 patients were finally collected from the SEER database and were randomly assigned to the training set (N=332) and validation set (N=166). Distant metastasis was associated with worse survival in the whole cohort, while the sites and number of metastasis were not closely associated with survival in the cohort of distant metastasis. In univariate and multivariate Cox analyses, variables of surgery, chemotherapy, age, and tumor size were identified as independent predictors for OS and CSS, and distant metastasis was also independently associated with CSS. The AUCs of ROC curves of nomogram for predicting 1-, 3- and 5-year OS were 0.770, 0.800, and 0.843, respectively, and those for CSS were 0.777, 0.758 and 0.761, respectively. The AUCs of time-dependent AUCs curves were all over 0.750. The calibration curves and DCA curves also showed excellent performance of prognostic nomograms. The established nomogram is a useful and robust tool for prognosis prediction and individualized clinical decisions in LMS patients with metastasis.