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Prognostic Factors and Nomogram Construction for First Local Recurrent Retroperitoneal Sarcoma Following Surgical Resection: A Single Asian Cohort of 169 Cases
- Source :
- Frontiers in Oncology, Vol 12 (2022)
- Publication Year :
- 2022
- Publisher :
- Frontiers Media S.A., 2022.
-
Abstract
- ObjectiveThis 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.MethodsIn 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.ResultsWith 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.ConclusionsFor 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.
Details
- Language :
- English
- ISSN :
- 2234943X
- Volume :
- 12
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Oncology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.37c8947750dc4b5491b8539d3e34980d
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fonc.2022.856754