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ABSTRACT: Background
The purpose of this study was to assess conditional survival (CS) after resection of primary retroperitoneal tumors (RPTs).Methods
The data of 1594 patients with primary RPTs who underwent surgery between 2004 and 2016 were retrieved from the Surveillance Epidemiology and End Results (SEER) database. Multivariate Cox analysis was used to identify prognostic factors affecting overall survival (OS) and cancer-specific survival (CSS). CS was used to calculate the probability of survival for an additional 3 years after the patient had survived x years, according to the formulas: COS3?=?OS (x?+?3) /OS (x) and CCSS3?=?CSS (x?+?3)/CSS (x).Results
The 1-, 3-, and 5-year OS rates of all patients were 89.8, 71.8, and 60.8%, while the 1-, 3-, and 5-year CSS rates were 91.9, 77.1, and 67.8%, respectively. Age, sex, FNCLCC grade, size, multifocality, histology, and chemotherapy were independent prognostic factors for OS and CSS. Among patients who survived for 1, 3, and 5 years, the COS3 rates were 72.9, 77.9, and 79.3%, and the CCSS3 rates were 78.1, 82.7, and 85.8%, respectively. Patients with poor clinicopathological characteristics achieved greater improvements in COS3 and CCSS3 rates, and the survival gaps between OS and COS3, as well as CSS and CCSS3 were more obvious.Conclusion
Postoperative CS of RPTs was dynamic and increased over time. CS increased more significantly in patients with poor clinicopathological characteristics.
SUBMITTER: Zhao S
PROVIDER: S-EPMC7816497 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Zhao Shutao S Zhao Yixuan Y Liu Shuang S Zhang Chao C Wang Xudong X
Cancer cell international 20210120 1
<h4>Background</h4>The purpose of this study was to assess conditional survival (CS) after resection of primary retroperitoneal tumors (RPTs).<h4>Methods</h4>The data of 1594 patients with primary RPTs who underwent surgery between 2004 and 2016 were retrieved from the Surveillance Epidemiology and End Results (SEER) database. Multivariate Cox analysis was used to identify prognostic factors affecting overall survival (OS) and cancer-specific survival (CSS). CS was used to calculate the probabil ...[more]