Jiabin Chen1, Chung Chang2, Hung-Chi Huang3, Yu-Che Chung2, Huan-Jung Huang2, Wen Shiung Liou4, An Jen Chiang5, Nelson N H Teng6. 1. Multidisciplinary Science Research Center, National Sun Yat-sen University, Kaohsiung, Taiwan. 2. Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan. 3. Department of Obstetrics and Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Graduate School of Business and Operations Management, Chang Jung Christian University, Tainan, Taiwan. 4. Department of Obstetrics and Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. 5. Department of Obstetrics and Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan; Department of Obstetrics and Gynecology, National Defense Medical Center, Taipei, Taiwan. Electronic address: ajchiang490111@gmail.com. 6. Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA.
Abstract
OBJECTIVE: The objective of this study was to build a model to differentiate between borderline and invasive ovarian tumors. MATERIALS AND METHODS: We performed a retrospective study involving 148 patients with borderline or invasive ovarian tumors in our institute between 1997 and 2012. Clinical and pathologic data were collected. Logistic regression was used to build the model. RESULTS: The model was created based on the following variables (p < 0.05): menopausal status; preoperative serum level of cancer antigen 125; the greatest diameter of the tumor; and the presence of solid parts on ultrasound imaging. The sensitivity and specificity of the model were 94.6% [95% confidence interval (CI), 0.887-1] and 78.3% (95% CI, 0.614-0.952) for patients aged ≥ 50 years, and 76.0% (95% CI, 0.622-0.903) and 60.0% (95% CI, 0.438-0.762) for those aged < 50 years, respectively. The performance of the model was tested using cross-validation. CONCLUSION: Differentiation between borderline and invasive ovarian tumors can be achieved using a model based on the following criteria: menopausal status; cancer antigen 125 level; and ultrasound parameters. The model is helpful to oncologists and patients in the initial evaluation phase of ovarian tumors.
OBJECTIVE: The objective of this study was to build a model to differentiate between borderline and invasive ovarian tumors. MATERIALS AND METHODS: We performed a retrospective study involving 148 patients with borderline or invasive ovarian tumors in our institute between 1997 and 2012. Clinical and pathologic data were collected. Logistic regression was used to build the model. RESULTS: The model was created based on the following variables (p < 0.05): menopausal status; preoperative serum level of cancer antigen 125; the greatest diameter of the tumor; and the presence of solid parts on ultrasound imaging. The sensitivity and specificity of the model were 94.6% [95% confidence interval (CI), 0.887-1] and 78.3% (95% CI, 0.614-0.952) for patients aged ≥ 50 years, and 76.0% (95% CI, 0.622-0.903) and 60.0% (95% CI, 0.438-0.762) for those aged < 50 years, respectively. The performance of the model was tested using cross-validation. CONCLUSION: Differentiation between borderline and invasive ovarian tumors can be achieved using a model based on the following criteria: menopausal status; cancer antigen 125 level; and ultrasound parameters. The model is helpful to oncologists and patients in the initial evaluation phase of ovarian tumors.
Authors: Rosa A Salcedo-Hernández; David F Cantú-de-León; Delia Pérez-Montiel; Leticia García-Pérez; Leonardo S Lino-Silva; César Zepeda-Najar; Salim A Barquet-Muñoz Journal: Ann Transl Med Date: 2021-02
Authors: Alicja Ogrodniczak; Janusz Menkiszak; Jacek Gronwald; Joanna Tomiczek-Szwiec; Marek Szwiec; Cezary Cybulski; Tadeusz Dębniak; Tomasz Huzarski; Aleksandra Tołoczko-Grabarek; Tomasz Byrski; Katarzyna Białkowska; Karolina Prajzendanc; Piotr Baszuk; Jan Lubiński; Anna Jakubowska Journal: Hered Cancer Clin Pract Date: 2022-03-21 Impact factor: 2.857