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Efficient surrogate markers are required to measure disease progression. The cytokeratin 7 (K7) load in a liver specimen is an independent prognostic indicator that can be measured from digitalized slides using artificial intelligence (AI)\u2010based models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A K7\u2010AI model 2.0 was built to measure the hepatocellular K7 load area of the parenchyma, portal tracts, and biliary epithelium. K7\u2010stained PSC liver biopsy specimens (<jats:italic>n<\/jats:italic>\u00a0=\u00a0295) were analyzed. A compound endpoint (liver transplantation, liver\u2010related death, and cholangiocarcinoma) was applied in Kaplan\u2013Meier survival analysis to measure AUC values and positive likelihood ratios for each histological variable detected by the model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The K7\u2010AI model 2.0 was a better prognostic tool than plasma alkaline phosphatase, the fibrosis stage evaluated by Nakanuma classification, or K7 score evaluated by a pathologist based on the AUC values of measured variables. A combination of parameters, such as portal tract volume and area of K7\u2010positive hepatocytes analyzed by the model, produced an AUC of 0.81 for predicting the compound endpoint. Portal tract volume measured by the model correlated with the histological fibrosis stage.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The K7 staining of histological liver specimens in PSC provides significant information on disease outcomes through objective and reproducible data, including variables that cannot be measured by a human pathologist. The K7\u2010AI model 2.0 could serve as a prognostic tool for clinical endpoints and as a surrogate marker in drug trials.<\/jats:p><\/jats:sec>","DOI":"10.1111\/hepr.13867","type":"journal-article","created":{"date-parts":[[2022,12,10]],"date-time":"2022-12-10T06:54:47Z","timestamp":1670655287000},"page":"322-333","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Automated image analysis of keratin 7 staining can predict disease outcome in primary sclerosing cholangitis"],"prefix":"10.1111","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3360-6645","authenticated-orcid":false,"given":"Nelli","family":"Sj\u00f6blom","sequence":"first","affiliation":[{"name":"Department of Pathology University of Helsinki and Helsinki University Hospital  Helsinki Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonja","family":"Boyd","sequence":"additional","affiliation":[{"name":"Department 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