Yasuhiro Shimizu1, Susumu Hijioka2, Seiko Hirono3, Toshifumi Kin4, Takao Ohtsuka5, Atsushi Kanno6, Shinsuke Koshita7, Keiji Hanada8, Masayuki Kitano9, Hiroyuki Inoue10, Takao Itoi11, Toshiharu Ueki12, Keitaro Matsuo13, Akio Yanagisawa14, Hiroki Yamaue3, Masanori Sugiyama15, Kazuichi Okazaki16. 1. Department of Gastroenterological Surgery, Aichi Cancer Center Hospital, Nagoya, Japan. 2. Department of Hepatobiliary and Pancreatic Oncology, National Cancer Center, Tokyo, Japan. 3. The Second Department of Surgery, Wakayama Medical University, School of Medicine, Wakayama, Japan. 4. Center for Gastroenterology, Teine-Keijinkai Hospital, Sapporo, Japan. 5. Department of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan. 6. Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan. 7. Department of Gastroenterology, Sendai City Medical Center, Sendai, Japan. 8. Department of Gastroenterology, JA Onomichi General Hospital, Hiroshima, Japan. 9. Department of Gastroenterology and Hepatology, Kindai University School of Medicine, Osakasayama, Japan. 10. Department of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan. 11. Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan. 12. Department of Gastroenterology, Fukuoka University Chikushi Hospital, Fukuoka, Japan. 13. Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan. 14. Department of Pathology, Kyoto Prefectural University of Medicine, Kyoto, Japan. 15. Department of Surgery, Kyorin University School of Medicine, Tokyo, Japan. 16. Department of Gastroenterology and Hepatology, Kansai Medical University, Osaka, Japan.
Abstract
OBJECTIVE: To create a simple, objective model to predict the presence of malignancy in patients with intraductal papillary mucinous neoplasm (IPMN), which can be easily applied in daily practice and, importantly, adopted for any lesion types. BACKGROUND: No predictive model for malignant IPMN has been widely applied in clinical practice. METHODS: The clinical details of 466 patients with IPMN who underwent pancreatic resection at 3 hospitals were retrospectively analyzed for model development. Then, the model was validated in 664 surgically resected patients at 8 hospitals in Japan.In the preoperative examination, endoscopic ultrasonography (EUS) was considered to be essential to observe mural nodules in both the model development and external validation sets. Malignant IPMNs were defined as those with high-grade dysplasia and associated invasive carcinoma. RESULTS: Of the 466 patients, 258 (55%) had malignant IPMNs (158 high-grade dysplasia, 100 invasive carcinoma), and 208 (45%) had benign IPMNs. Logistic regression analysis resulted in 3 variables (mural nodule size, main pancreatic duct diameter, and cyst size) being selected to construct the model. The area under the receiver operating characteristic curve (AUC) for the model was 0.763. In external validation sets, the pathological diagnosis was malignant and benign IPMN in 351 (53%) and 313 (47%) cases, respectively. For the external validation, the malignancy prediction ability of the model corresponded to an AUC of 0.725. CONCLUSION: This predictive model provides important information for physicians and patients in assessing an individual's risk for malignancy and may help to identify patients who need surgery.
OBJECTIVE: To create a simple, objective model to predict the presence of malignancy in patients with intraductal papillary mucinous neoplasm (IPMN), which can be easily applied in daily practice and, importantly, adopted for any lesion types. BACKGROUND: No predictive model for malignant IPMN has been widely applied in clinical practice. METHODS: The clinical details of 466 patients with IPMN who underwent pancreatic resection at 3 hospitals were retrospectively analyzed for model development. Then, the model was validated in 664 surgically resected patients at 8 hospitals in Japan.In the preoperative examination, endoscopic ultrasonography (EUS) was considered to be essential to observe mural nodules in both the model development and external validation sets. Malignant IPMNs were defined as those with high-grade dysplasia and associated invasive carcinoma. RESULTS: Of the 466 patients, 258 (55%) had malignant IPMNs (158 high-grade dysplasia, 100 invasive carcinoma), and 208 (45%) had benign IPMNs. Logistic regression analysis resulted in 3 variables (mural nodule size, main pancreatic duct diameter, and cyst size) being selected to construct the model. The area under the receiver operating characteristic curve (AUC) for the model was 0.763. In external validation sets, the pathological diagnosis was malignant and benign IPMN in 351 (53%) and 313 (47%) cases, respectively. For the external validation, the malignancy prediction ability of the model corresponded to an AUC of 0.725. CONCLUSION: This predictive model provides important information for physicians and patients in assessing an individual's risk for malignancy and may help to identify patients who need surgery.
Authors: Alba Manuel-Vázquez; Anita Balakrishnan; Paul Agami; Bodil Andersson; Frederik Berrevoet; Marc G Besselink; Ugo Boggi; Damiano Caputo; Alberto Carabias; Lucia Carrion-Alvarez; Carmen Cepeda Franco; Alessandro Coppola; Bobby V M Dasari; Sherley Diaz-Mercedes; Michail Feretis; Constantino Fondevila; Giuseppe Kito Fusai; Giuseppe Garcea; Victor Gonzabay; Miguel Ángel Gómez Bravo; Myrte Gorris; Bart Hendrikx; Camila Hidalgo-Salinas; Prashant Kadam; Dimitrios Karavias; Emanuele Kauffmann; Amar Kourdouli; Vincenzo La Vaccara; Stijn van Laarhoven; James Leighton; Mike S L Liem; Nikolaos Machairas; Dimitris Magouliotis; Adel Mahmoud; Marco V Marino; Marco Massani; Paola Melgar Requena; Keno Mentor; Niccolò Napoli; Jorieke H T Nijhuis; Andrej Nikov; Cristina Nistri; Victor Nunes; Eduardo Ortiz Ruiz; Sanjay Pandanaboyana; Baltasar Pérez Saborido; Radek Pohnán; Mariuca Popa; Belinda Sánchez Pérez; Francisco Sánchez Bueno; Alejandro Serrablo; Mario Serradilla-Martín; James R A Skipworth; Kjetil Soreide; Dimitris Symeonidis; Dimitris Zacharoulis; Piotr Zelga; Daniel Aliseda; María Jesús Castro Santiago; Carlos Fernández Mancilla; Raquel Latorre Fragua; Daniel Llwyd Hughes; Carmen Payá Llorente; Mickaël Lesurtel; Tom Gallagher; José Manuel Ramia Journal: Langenbecks Arch Surg Date: 2022-10-06 Impact factor: 2.895
Authors: Jie Hua; Bo Zhang; Xiu-Jiang Yang; Yi-Yin Zhang; Miao-Yan Wei; Chen Liang; Qing-Cai Meng; Jiang Liu; Xian-Jun Yu; Jin Xu; Si Shi Journal: World J Gastrointest Oncol Date: 2019-11-15