ArticleTranslational cancer research2026
Prognostic characteristics, recurrence patterns and survival outcomes of uterine papillary serous carcinoma: a single-centre retrospective cohort study.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Uterine papillary serous carcinoma (UPSC) is a rare subtype of endometrial cancer with aggressive characteristics. The aim of our cohort analysis was to examine and present risk factors for recurrence and mortality. Methods: The study is a retrospective analysis led from April 2010 and November 2019. Women older than 18 years, with a histopathological diagnosis of serous carcinoma (SC) and suitable for surgery were included in this study. Univariate and multivariate Cox proportional hazards analysis was conducted to assess individual risk factors for both recurrence and mortality. Survival rates were calculated using Kaplan-Meier curves and compared using log-rank tests. Results: One hundred and eighteen cases of SC were surgically managed. For the entire cohort, 5-year overall survival (OS) was 41.6%, while 5-year disease-free survival (DFS) was 60.7%. Advanced stages had the worst survival and recurrence rate (P=0.001 and 0.01, respectively). Univariate analysis revealed an association with a high risk of mortality for myometrial invasion, cervical, parametrial and lymphovascular space invasion (LVSI) and adnexa involvement, whereas only cervical, lymphovascular and parametrium invasion were associated. However, the multivariate analysis confirmed the cervical invasion as a poor predictor for survival with a hazard ratio of 2.230 (95% confidence interval: 1.252-3.971; P=0.006). Conclusions: UPSC is an aggressive subtype of endometrial cancer where even early stages tend to recur and deteriorate the prognosis. Cervical involvement was the only risk factor associated with increased mortality, while myometrial invasion and LVSI were not confirmed in the multivariate analysis.
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