Surgically treated pelvic liposarcoma and leiomyosarcoma: the effect of tumor size on cancer-specific survival

Abstract

Introduction: In soft tissue pelvic liposarcoma and leiomyosarcoma, it is unknown whether a specific tumor size cut-off may help to better predict prognosis, defined as cancer-specific survival (CSS). We tested whether different tumor size cut-offs, could improve CSS prediction. Materials and methods: Surgically treated non-metastatic soft tissue pelvic sarcoma patients were identified (Surveillance, Epidemiology, and End Results 2004–2019). Kaplan-Meier plots, univariable and multivariable Cox-regression models and receiver operating characteristic-derived area under the curve (AUC) estimates were used. Results: Overall, 672 (65 %) liposarcoma (median tumor size 11 cm, interquartile range [IQR] 7–16) and 367 (35 %) leiomyosarcoma (median tumor size 8 cm, IQR 5–12) patients were identified. The p-value derived ideal tumor size cut-off was 17.1 cm, in liposarcoma and 7.0 cm, in leiomyosarcoma. In liposarcoma, according to p-value derived cut-off, five-year CSS rates were 92 vs 83 % (≤17.1 vs > 17.1 cm). This cut-off represented an independent predictor of CSS and improved prognostic ability from 83.8 to 86.8 % (Δ = 3 %). Similarly, among previously established cut-offs (5 vs 10 vs 15 cm), also 15 cm represented an independent predictor of CSS and improved prognostic ability from 83.8 to 87.0 % (Δ = 3.2 %). In leiomyosarcoma, according to p-value derived cut-off, five-year CSS rates were 86 vs 55 % (≤7.0 vs > 7.0 cm). This cut-off represented an independent predictor of CSS and improved prognostic ability from 68.6 to 76.5 % (Δ = 7.9 %). Conclusions: In liposarcoma, the p-value derived tumor size cut-off was 17.1 cm vs 7.0 cm, in leiomyosarcoma. In both histologic subtypes, these cut-offs exhibited the optimal statistical characteristics (univariable, multivariable and AUC analyses). In liposarcoma, the 15 cm cut-off represented a valuable alternative. © 2024 Elsevier Ltd