Adult Prostate Sarcoma: Demographics, Treatment Patterns, and Survival

Background: This study aimed to examine clinicopathologic characteristics, treatment patterns, and survival rates in a contemporary population-based cohort of adult prostate sarcoma patients. Methods: In the Surveillance, Epidemiology, and End Results database (2004–2020), adult patients with prostate sarcoma were identified. Descriptive statistics, Kaplan–Meier analyses, smoothed cumulative incidence plots, and Cox regression models were used. Results: Of 125 patients, 45 (36%) harbored leiomyosarcoma, 17 (14%) had rhabdomyosarcoma, 15 (12%) had stromal sarcoma, 17 (14%) had sarcoma not otherwise specified (NOS), and 31 (25%) had other sarcoma subtypes. Metastatic stage was most common in the rhabdomyosarcoma patients (44%) and least common in the leiomyosarcoma (21%) and stromal sarcoma (20%) patients. Most of the rhabdomyosarcoma patients received the combination of systemic and radiation therapy with (24%) or without radical surgery (35%), whereas most of the leiomyosarcoma and stromal sarcoma patients underwent radical surgery with (22 and 13%) or without (22 and 47%) radiation. In the overall population, the median overall survival was 27 months. The 5-years overall versus cancer-specific versus other-cause mortality rates were respectively 71 versus 58 versus 13%. In the multivariable Cox regression models, the highest overall mortality was exhibited by the patients with metastatic disease (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.55–5.31; p < 0.001) or unknown disease stage (HR 2.94; 95% CI 2.20–7.21; p = 0.019). Conversely, of all the histologic subtypes, only stromal sarcoma distinguished itself by lower overall mortality (HR 0.41; 95% CI 0.18–0.96; p = 0.039). Conclusions: Four major histologic subtypes were identified. Among most adult sarcoma patients, treatment patterns vary according to histology, from multimodal therapy to radical prostatectomy alone. These treatment differences reflect equally important heterogeneity in survival patterns.