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Preoperative tumor size is associated with deep myometrial invasion and lymph node metastases and is a negative prognostic indicator for patients with endometrial carcinoma
We examined the usefulness of evaluating tumor size determined using preoperative magnetic resonance imaging (MRI) for prognosis in patients with endometrial carcinoma (EC). Patients (N = 184) with EC who underwent surgery at Shimane University Hospital between 1997 and 2013 were enrolled. We invest...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955431/ https://www.ncbi.nlm.nih.gov/pubmed/29796179 http://dx.doi.org/10.18632/oncotarget.25248 |
Sumario: | We examined the usefulness of evaluating tumor size determined using preoperative magnetic resonance imaging (MRI) for prognosis in patients with endometrial carcinoma (EC). Patients (N = 184) with EC who underwent surgery at Shimane University Hospital between 1997 and 2013 were enrolled. We investigated the association between the tumor size of EC assessed prior to surgery by MRI (anteroposterior [AP], transverse [TV], and craniocaudal [CC] diameters) and various clinical parameters including deep myometrial invasion and lymph node metastases. We subsequently examined the prognostic significance of tumor size in patients with EC. Survival analysis was performed using the Kaplan-Meier method, and prognostic factors were evaluated using the Cox’s proportional hazards regression model. Multivariate analysis identified increased AP diameter as an independent negative prognostic factor for overall survival (OS) (P = 0.037). A long AP diameter has prognostic value and the potential to be a predictive marker for surgical outcomes in patients with EC. Furthermore, AP diameter exhibited the greatest area under the curve (AUC) (0.727) for deep myometrial invasion, and CC diameter had the greatest AUC for lymph node metastases (0.854). Evaluation of tumor size parameters may aid in the identification of high-risk populations, which could improve treatment selection and patient outcomes. |
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