Alternative Title卵巣悪性腫瘍と良性内膜症性嚢胞の鑑別における各予測インデックスの特徴と有用性の比較
Note (General)type:Thesis
This study aimed to evaluate the prediction efficacy of malignant transformation of ovarianendometrioma (OE) using the Copenhagen Index (CPH-I), the risk of ovarian malignancy algorithm(ROMA), and the R2 predictive index. This retrospective study was conducted at the Departmentof Gynecology, Nara Medical University Hospital, from January 2008 to July 2021. A total of171 patients were included in the study. In the current study, cases were divided into three cohorts:pre-menopausal, post-menopausal, and a combined cohort. Patients with benign ovarian tumormainly received laparoscopic surgery, and patients with suspected malignant tumors underwentlaparotomy. Information from a review chart of the patients’ medical records was collected. In thecombined cohort, a multivariate analysis confirmed that the ROMA index, the R2 predictive index,and tumor laterality were extracted as independent factors for predicting malignant tumors (hazardratio (HR): 222.14, 95% confidence interval (CI): 22.27–2215.50, p < 0.001; HR: 9.80, 95% CI: 2.90–33.13,p < 0.001; HR: 0.15, 95% CI: 0.03–0.75, p = 0.021, respectively). In the pre-menopausal cohort, amultivariate analysis confirmed that the CPH index and the R2 predictive index were extracted asindependent factors for predicting malignant tumors (HR: 6.45, 95% CI: 1.47–28.22, p = 0.013; HR:31.19, 95% CI: 8.48–114.74, p < 0.001, respectively). Moreover, the R2 predictive index was onlyextracted as an independent factor for predicting borderline tumors (HR: 45.00, 95% CI: 7.43–272.52,p < 0.001) in the combined cohort. In pre-menopausal cases or borderline cases, the R2 predictiveindex is useful; while, in post-menopausal cases, the ROMA index is better than the other indexes.
博士（医学）・甲第875号・令和5年3月15日
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
identifier:Diagnostics Vol.12 No.5 Article No.1212 (2022 May)
identifier:20754418
identifier:http://ginmu.naramed-u.ac.jp/dspace/handle/10564/4107
identifier:Diagnostics, 12(5): Article No.1212
Collection (particular)国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
Date Accepted (W3CDTF)2023-12-05T21:41:07+09:00
Data Provider (Database)国立国会図書館 : 国立国会図書館デジタルコレクション