BACKGROUND: Current the surveillance and management are controversial for patients with IPMN. We aimed to develop an alternative nomogram to individualize IPMN prognosis and LNM. METHODS: Based on the data from SEER database of patients diagnosed with IPMN between 2004 and 2015, a nomogram predicting the survival and LNM of IPMN based on univariate and multivariate and Lasso regression analysis was performed, internally and externally validated, and measured by C-index, and decision curve analysis (DCA), and compared to the 7th TNM stage. RESULTS: A total of 941 patients were included. Age, T stage examined nodes, tumor size, and pathology grade were identified as an independent factor for predicting LNM. The nomogram we established to predict LNM had a high predicting value with a C-index value of 0.735 and an AUC value of 0.753. Interestingly, including T1 stage, we found an inverse correlation was between age and LNM. In addition, nomogram for predicting CSS also performed better than TNM stage both in the internal validation group (1-year AUC:0.753 vs. 0.693, 3-year AUC: 0.801 vs. 0.731, 5-year AUC: 0.803 vs. 0.733) and external validation group (1-year AUC: 0.761 vs. 0.701, 3-year AUC: 0.772 vs. 0.713, 5-year AUC:0.811 vs. 0.735). DCA analysis showed the nomogram showed a greater benefit across the period of follow-up compared to 7th TNM stage. CONCLUSION: A nomogram based on multivariate and Lasso regression analysis showed great clinical usability compared with current criteria. Also, for LNM of IPMN, younger age patients with IPMN should be attached more importance.
BACKGROUND: Current the surveillance and management are controversial for patients with IPMN. We aimed to develop an alternative nomogram to individualize IPMN prognosis and LNM. METHODS: Based on the data from SEER database of patients diagnosed with IPMN between 2004 and 2015, a nomogram predicting the survival and LNM of IPMN based on univariate and multivariate and Lasso regression analysis was performed, internally and externally validated, and measured by C-index, and decision curve analysis (DCA), and compared to the 7th TNM stage. RESULTS: A total of 941 patients were included. Age, T stage examined nodes, tumor size, and pathology grade were identified as an independent factor for predicting LNM. The nomogram we established to predict LNM had a high predicting value with a C-index value of 0.735 and an AUC value of 0.753. Interestingly, including T1 stage, we found an inverse correlation was between age and LNM. In addition, nomogram for predicting CSS also performed better than TNM stage both in the internal validation group (1-year AUC:0.753 vs. 0.693, 3-year AUC: 0.801 vs. 0.731, 5-year AUC: 0.803 vs. 0.733) and external validation group (1-year AUC: 0.761 vs. 0.701, 3-year AUC: 0.772 vs. 0.713, 5-year AUC:0.811 vs. 0.735). DCA analysis showed the nomogram showed a greater benefit across the period of follow-up compared to 7th TNM stage. CONCLUSION: A nomogram based on multivariate and Lasso regression analysis showed great clinical usability compared with current criteria. Also, for LNM of IPMN, younger age patients with IPMN should be attached more importance.
Authors: Olca Basturk; Seung-Mo Hong; Laura D Wood; N Volkan Adsay; Jorge Albores-Saavedra; Andrew V Biankin; Lodewijk A A Brosens; Noriyoshi Fukushima; Michael Goggins; Ralph H Hruban; Yo Kato; David S Klimstra; Günter Klöppel; Alyssa Krasinskas; Daniel S Longnecker; Hanno Matthaei; G Johan A Offerhaus; Michio Shimizu; Kyoichi Takaori; Benoit Terris; Shinichi Yachida; Irene Esposito; Toru Furukawa Journal: Am J Surg Pathol Date: 2015-12 Impact factor: 6.394
Authors: Rym El Khoury; Christopher Kabir; Vijay K Maker; Mihaela Banulescu; Margaret Wasserman; Ajay V Maker Journal: Ann Surg Oncol Date: 2018-03-20 Impact factor: 5.344
Authors: Taylor S Riall; Victoria M Stager; William H Nealon; Courtney M Townsend; Yong-fang Kuo; James S Goodwin; Jean L Freeman Journal: J Am Coll Surg Date: 2007-03-23 Impact factor: 6.113