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Purpose: This study aims to determine the optimal cut-off value of Ki-67 to better predict the recurrence of early low-risk endometrial cancer (EC).
Methods: Seven hundred and forty-eight patients diagnosed with low-risk EC from West China Second Hospital of Sichuan University and the First Affiliated Hospital of Chongqing Medical University were retrospectively analyzed. The receiver operating characteristic curve (ROC) and Youden index were used to calculate the optimal cut-off value of Ki-67 expression. The clinicopathological indexes between two groups divided by cut-off value of Ki-67 were compared. The univariate and multivariate regression analyses were performed to investigate risk factors connected to the recurrence of early low-risk EC. The survival analysis was shown in Kaplan-Meier curve.
Result: Thirty-three patients were detected with tumor recurrence after primary surgery (4.4%); 33% was the optimal cut-off value of the Ki-67 index. A high Ki-67 was significantly associated with age ( = .002), myometrial invasion ( < .001), and the expression of P53 ( = .007). The multivariate regression analysis verified that Ki67 ≥ 33% was an independent prognostic factor for predicting recurrence. The recurrence-free survival (RFS) and the overall survival (OS) in high Ki-67 group was significantly lower than that in low Ki-67 group ( < .001 and = .029, respectively). The prognostic values of ER, PR, and P53 in combination with Ki-67 were superior to each single predictor.
Conclusions: The optimal cut-off value of Ki-67 for predicting recurrence is 33%, which quantitatively defines the specific value of Ki-67 that causes high-risk recurrence in early low-risk EC.
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http://dx.doi.org/10.1177/10732748231206929 | DOI Listing |
Front Oncol
August 2025
Department of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China.
Objectives: Lymph node metastasis (LNM) is an important factor affecting the stage and prognosis of patients with lung adenocarcinoma. The purpose of this study is to explore the predictive value of the stacking ensemble learning model based on F-FDG PET/CT radiomic features and clinical risk factors for LNM in lung adenocarcinoma, and elucidate the biological basis of predictive features through pathological analysis.
Methods: Ninety patients diagnosed with lung adenocarcinoma who underwent PET/CT were retrospectively analyzed and randomly divided into the training and testing sets in a 7:3 ratio.
Sci Rep
August 2025
Division of Breast Surgery, Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Progesterone-induced blocking factor 1 (PIBF1) is linked to pregnancy-induced immunity and tumor evasion of maternal immunity. PIBF1 is overexpressed in several cancers, including breast, cervical, and lymphoma. However, limited research is available on the role of PIBF1 in breast cancer and its clinical outcomes.
View Article and Find Full Text PDFJ Clin Ultrasound
August 2025
Department of Ultrasound, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu Province, China.
Objective: To investigate the correlation between contrast-enhanced ultrasound (CEUS) features and Ki-67 expression in patients with hepatocellular carcinoma (HCC).
Methods: It was a retrospective analysis involving 94 patients with HCC receiving surgeries and diagnosed by postoperative pathology from January 2020 to December 2021. All patients were examined by preoperative CEUS and postoperative Ki-67 immunohistochemistry.
Medicina (Kaunas)
July 2025
Department of Medical Oncology, Bezmialem Vakif University Hospital, 34093 Istanbul, Turkey.
We aim to determine the efficacy and the factors associated with the effectiveness of first-line CDK4/6i (ribociclib or palbociclib) treatment in HR-positive, HER2-negative MBC patients. This is a retrospective, cross-sectional, and descriptive study. Ninety patients with metastatic breast cancer receiving CDK 4/6i treatment from three different oncology clinics were included in this study.
View Article and Find Full Text PDFBMC Cancer
July 2025
Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Background: Metastatic liver tumor burden (LTB) is a prognostic factor affecting the survival of gastroenteropancreatic neuroendocrine tumors (GEP-NETs), but evaluation of the LTB usually depends on radiologic and functional imaging. This study aimed to develop a clinical model based on easily accessible clinicopathological markers to predict LTB level in GEP-NET patients.
Methods: LTB was quantified based on Ga-DOTANOC PET/CT scan.