Article ID Journal Published Year Pages File Type
5526843 European Journal of Cancer 2016 10 Pages PDF
Abstract

•A nationwide analysis of recurrence in early-stage endometrial cancer was conducted.•Women with early-stage endometrial cancer have a low risk of recurrence (7%).•Survival was closely related to site of recurrence.•Severe comorbidity and being outside of the workforce were predictive of recurrence.•Inclusion of sociodemographic predictors may improve future risk stratification.

Background and aimsThe aim of the study was to present a comprehensive analysis of disease recurrence in a large Danish cohort of women with early-stage endometrial cancer treated according to national guidelines.MethodsAll women diagnosed with stage I or II endometrial cancer in 2005-2009 were included in a population-based historical cohort derived from the Danish Gynaecological Cancer Database. Disease recurrence up to 3 years after the primary diagnosis was identified using national registers and hospital charts. Follow-up on survival ended on 31st December 2014. We evaluated the predictive value of clinico-pathological and sociodemographic variables using multivariate logistic regression.ResultsRecurrence within 3 years of the primary treatment was diagnosed in 183 (7%) of the included 2612 women. Site of recurrence significantly impacted on overall survival as the 5-year survival rate was 64.8% for women with vaginal recurrence and 17.5% in women with distant recurrence. Factors predictive of recurrence included the International Federation of Gynaecology and Obstetrics (FIGO) stage (OR: IB = 1.91, stage II = 3.91), Charlson comorbidity index of 3 (OR 1.86), non-endometrioid histology (OR 1.81) and being outside of the workforce (OR 1.81). Vaginal recurrence was predicted by FIGO stage only (OR: IB = 1.88, II = 2.79), while extra-vaginal recurrence was predicted by FIGO stage (OR: IB = 2.12, II = 3.31), Charlson comorbidity index of 3 (OR 1.88) and non-endometrioid histology (OR 2.51).ConclusionsFuture research should seek to understand the underlying mechanisms of the identified predictive factors to improve recurrence prediction and to reduce morbidity and mortality.

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