Nomograms Predict Cancer-Specific and Overall Survival of Patients With Primary Limb Leiomyosarcoma.

To date, there have been no data to predict the survival of patients with leiomyosarcoma from soft limb tissue because of the rarity of this disease. Nomograms have been widely applied in clinical oncology to precisely predict the survival of individual patients. This was a retrospective study to construct and validate nomograms to predict the cancer-specific survival (CSS) and overall survival (OS) of patients with primary limb leiomyosarcoma (PL-LMS). A total of 1,208 patients with LMS from limb soft tissue were collected from the Surveillance, Epidemiology, and End Results database from 1975 to 2015. We identified independent prognostic factors using univariate and multivariate Cox analyses. These prognostic factors were then included in the nomograms to predict 3- and 5-year CSS and OS rates. Finally, we validated the nomograms internally and externally. A total of 1208 patients were collected and divided into validation (N = 604) and training (N = 604) groups. Age, race, grade, tumor size, stage, and surgical types were demonstrated as independent prognostic factors for CSS and OS (all p < 0.05) and further used to construct the nomograms. The concordance index (C-index) for CSS was 0.857 for internal validation and 0.727 for external validation. The C-index for OS and CSS both demonstrated that the nomogram prediction agreed perfectly with actual survival. We developed nomograms to predict CSS and OS in PL-LMS patients and can benefit from using them to identify patients' mortality risk and make more precise assessments regarding survival.