Dynamic survival prognosis and the role of radiotherapy in retroperitoneal liposarcoma

Dynamic survival prognosis and the role of radiotherapy in retroperitoneal liposarcoma. Dynamic survival prognosis and the role of radiotherapy in retroperitoneal liposarcoma Article Open access Published: 31 October 2026 Cite this article You have full access to this open access article Download PDF View saved research Dynamic survival prognosis and the role of radiotherapy in retroperitoneal liposarcoma Download PDF Abstract Retroperitoneal liposarcomas (RPLSs) are rare and highly heterogeneous tumors, presenting unique clinical challenges. Despite surgical resection being the primary treatment, achieving complete resection with negative margins is difficult, and the role of adjuvant therapies, such as radiotherapy, remains unclear.

The data for this study was sourced from the SEER (Surveillance, Epidemiology, and End Results) database. Conditional survival (CS) analysis was performed to evaluate survival outcomes over time. Machine learning techniques, including Random Survival Forest (RSF) and Least Absolute Shrinkage and Selection Operator (LASSO) regression, were used to identify prognostic factors and develop a CS-based nomogram.

Propensity score matching (PSM) was employed to assess the survival benefit of radiotherapy. A total of 1,186 patients were analyzed (830 training, 356 validation). The CS analysis demonstrated improved survival probabilities with extended survival time; the probability of reaching 10 years rose from 41% at diagnosis to 87% after surviving 8 years.

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