Prognostic Factors and Nomogram Construction for First Local Recurrent Retroperitoneal Sarcoma Following Surgical Resection: A Single Asian Cohort of 169 Cases - Zhuang, Aobo; Lu, Weiqi; Fang, Yuan; Ma, Lijie; Xu, Jing; Wang, Jiongyuan; Tong, Hanxing; Zhang, Yong (Frontiers in Oncology, 2022)
Objective This study aimed to explore the prognostic factors for first local recurrent retroperitoneal soft tissue sarcoma (FLR-RPS) and construct predictive nomograms in the Asian population. Methods In a single Asian sarcoma center, data of patients with FLR-RPS were retrospectively analyzed from January 2011 to September 2020. We developed and internally validated prognostic factors determined by the Cox regression model, as well as nomograms for predicting recurrence-free survival (RFS) and overall survival (OS). The concordance index and calibration curve were used to determine the nomogram’s discriminative and predictive ability. Results With 169 patients, the median follow-up duration was 48 months and the 5-year OS rate was 60.9% (95% confidence interval (CI), 51.9%–69.9%). OS was correlated with chemotherapy at the time of initial surgery and tumor grading. The 5-year cumulative local recurrence rate and distant metastasis rate were 75.9% (95% CI, 67.5%–84.3%) and 10.1% (95% CI, 4.2%–16.0%), respectively, and the length of the disease-free interval following the primary operation was associated with disease recurrence. The 6-year OS and cumulative recurrence rate after surgery in our cohort were comparable with those in the TARPSWG cohort, but the proportion of local recurrence was higher (80.4% vs. 59.0%), and distant metastasis was less common (10.1% vs. 14.6%). In this study, two nomogram prediction models were established, which could predict the 1-, 2-, and 5-year OS and RFS, and the concordance indices were 0.74 and 0.70, respectively. The calibration plots were excellent. Conclusions For the FLR-RPS patients, some can still achieve an ideal prognosis. The treatment of FLR-RPS in Asian populations can be aided by the predictive model established in this study.