{"title":"预测慢性胰腺炎和自身免疫性胰腺炎的胰腺外分泌功能不全:决策树方法","authors":"Tomoyuki Tanaka, Takefumi Kimura, Shun-Ichi Wakabayashi, Takuma Okamura, Shohei Shigeto, Naoki Tanaka, Shohei Kondo, Ichitaro Horiuchi, Yasuhiro Kuraishi, Akira Nakamura, Norihiro Ashihara, Keita Kanai, Tadanobu Nagaya, Takayuki Watanabe, Takeji Umemura","doi":"10.1097/MPA.0000000000002290","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Exocrine pancreatic insufficiency (EPI) is a common manifestation of chronic pancreatitis (CP) and autoimmune pancreatitis (AIP). This study aimed to estimate the presence of EPI in patients with CP or AIP using alternative clinical markers.</p><p><strong>Materials and methods: </strong>A machine learning analysis employing a decision tree model was conducted on a retrospective training cohort comprising 57 patients with CP or AIP to identify EPI, defined as fecal elastase-1 levels less than 200 μg/g. The outcomes were then confirmed in a validation cohort of 26 patients.</p><p><strong>Results: </strong>Thirty-nine patients (68%) exhibited EPI in the training cohort. The decision tree algorithm revealed body mass index (≤21.378 kg/m 2 ) and total protein level (≤7.15 g/dL) as key variables for identifying EPI. The algorithm's performance was assessed using 5-fold cross-validation, yielding area under the receiver operating characteristic curve values of 0.890, 0.875, 0.750, 0.625, and 0.771, respectively. The results from the validation cohort closely replicated those in the training cohort.</p><p><strong>Conclusions: </strong>Decision tree analysis revealed that EPI in patients with CP or AIP can be identified based on body mass index and total protein. These findings may help guide the implementation of appropriate treatments for EPI.</p>","PeriodicalId":19733,"journal":{"name":"Pancreas","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive Insights Into Exocrine Pancreatic Insufficiency in Chronic Pancreatitis and Autoimmune Pancreatitis: A Decision Tree Approach.\",\"authors\":\"Tomoyuki Tanaka, Takefumi Kimura, Shun-Ichi Wakabayashi, Takuma Okamura, Shohei Shigeto, Naoki Tanaka, Shohei Kondo, Ichitaro Horiuchi, Yasuhiro Kuraishi, Akira Nakamura, Norihiro Ashihara, Keita Kanai, Tadanobu Nagaya, Takayuki Watanabe, Takeji Umemura\",\"doi\":\"10.1097/MPA.0000000000002290\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Exocrine pancreatic insufficiency (EPI) is a common manifestation of chronic pancreatitis (CP) and autoimmune pancreatitis (AIP). This study aimed to estimate the presence of EPI in patients with CP or AIP using alternative clinical markers.</p><p><strong>Materials and methods: </strong>A machine learning analysis employing a decision tree model was conducted on a retrospective training cohort comprising 57 patients with CP or AIP to identify EPI, defined as fecal elastase-1 levels less than 200 μg/g. The outcomes were then confirmed in a validation cohort of 26 patients.</p><p><strong>Results: </strong>Thirty-nine patients (68%) exhibited EPI in the training cohort. The decision tree algorithm revealed body mass index (≤21.378 kg/m 2 ) and total protein level (≤7.15 g/dL) as key variables for identifying EPI. The algorithm's performance was assessed using 5-fold cross-validation, yielding area under the receiver operating characteristic curve values of 0.890, 0.875, 0.750, 0.625, and 0.771, respectively. The results from the validation cohort closely replicated those in the training cohort.</p><p><strong>Conclusions: </strong>Decision tree analysis revealed that EPI in patients with CP or AIP can be identified based on body mass index and total protein. These findings may help guide the implementation of appropriate treatments for EPI.</p>\",\"PeriodicalId\":19733,\"journal\":{\"name\":\"Pancreas\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pancreas\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/MPA.0000000000002290\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/25 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pancreas","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/MPA.0000000000002290","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/25 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Predictive Insights Into Exocrine Pancreatic Insufficiency in Chronic Pancreatitis and Autoimmune Pancreatitis: A Decision Tree Approach.
Objective: Exocrine pancreatic insufficiency (EPI) is a common manifestation of chronic pancreatitis (CP) and autoimmune pancreatitis (AIP). This study aimed to estimate the presence of EPI in patients with CP or AIP using alternative clinical markers.
Materials and methods: A machine learning analysis employing a decision tree model was conducted on a retrospective training cohort comprising 57 patients with CP or AIP to identify EPI, defined as fecal elastase-1 levels less than 200 μg/g. The outcomes were then confirmed in a validation cohort of 26 patients.
Results: Thirty-nine patients (68%) exhibited EPI in the training cohort. The decision tree algorithm revealed body mass index (≤21.378 kg/m 2 ) and total protein level (≤7.15 g/dL) as key variables for identifying EPI. The algorithm's performance was assessed using 5-fold cross-validation, yielding area under the receiver operating characteristic curve values of 0.890, 0.875, 0.750, 0.625, and 0.771, respectively. The results from the validation cohort closely replicated those in the training cohort.
Conclusions: Decision tree analysis revealed that EPI in patients with CP or AIP can be identified based on body mass index and total protein. These findings may help guide the implementation of appropriate treatments for EPI.
期刊介绍:
Pancreas provides a central forum for communication of original works involving both basic and clinical research on the exocrine and endocrine pancreas and their interrelationships and consequences in disease states. This multidisciplinary, international journal covers the whole spectrum of basic sciences, etiology, prevention, pathophysiology, diagnosis, and surgical and medical management of pancreatic diseases, including cancer.