Accuracy of cytokeratin 18 (M30 and M65) in detecting non-alcoholic steatohepatitis and fibrosis: A systematic review and meta-analysis
Introduction Association between elevated cytokeratin 18 (CK-18) levels and hepatocyte death has made circulating CK-18 a candidate biomarker to differentiate non-alcoholic fatty liver from non-alcoholic steatohepatitis (NASH). Yet studies produced variable diagnostic performance. We aimed to provid...
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| creator | Lee, Jenny Vali, Yasaman Boursier, Jérôme Duffin, Kevin Verheij, Joanne Brosnan, M. Julia Zwinderman, Koos Anstee, Quentin M Bossuyt, Patrick M Zafarmand, Mohammad Hadi |
| description | Introduction Association between elevated cytokeratin 18 (CK-18) levels and hepatocyte death has made circulating CK-18 a candidate biomarker to differentiate non-alcoholic fatty liver from non-alcoholic steatohepatitis (NASH). Yet studies produced variable diagnostic performance. We aimed to provide summary estimates with increased precision for the accuracy of CK-18 (M30, M65) in detecting NASH and fibrosis among non-alcoholic fatty liver disease (NAFLD) adults. Methods We searched five databases to retrieve studies evaluating CK-18 against a liver biopsy in NAFLD adults. Reference screening, data extraction and quality assessment (QUADAS-2) were independently conducted by two authors. Meta-analyses were performed for five groups based on the CK-18 antigens and target conditions, using one of two methods: linear mixed-effects multiple thresholds model or bivariate logit-normal random-effects model. Results We included 41 studies, with data on 5,815 participants. A wide range of disease prevalence was observed. No study reported a pre-defined cut-off. Thirty of 41 studies provided sufficient data for inclusion in any of the meta-analyses. Summary AUC [95% CI] were: 0.75 [0.69-0.82] (M30) and 0.82 [0.69-0.91] (M65) for NASH; 0.73 [0.57-0.85] (M30) for fibrotic NASH; 0.68 (M30) for significant (F2-4) fibrosis; and 0.75 (M30) for advanced (F3-4) fibrosis. Thirteen studies used CK-18 as a component of a multimarker model. Conclusions For M30 we found lower diagnostic accuracy to detect NASH compared to previous meta-analyses, indicating a limited ability to act as a stand-alone test, with better performance for M65. Additional external validation studies are needed to obtain credible estimates of the diagnostic accuracy of multimarker models. |
| doi_str_mv | 10.1371/journal.pone.0238717 |
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Julia ; Zwinderman, Koos ; Anstee, Quentin M ; Bossuyt, Patrick M ; Zafarmand, Mohammad Hadi</creator><contributor>Strnad, Pavel</contributor><creatorcontrib>Lee, Jenny ; Vali, Yasaman ; Boursier, Jérôme ; Duffin, Kevin ; Verheij, Joanne ; Brosnan, M. Julia ; Zwinderman, Koos ; Anstee, Quentin M ; Bossuyt, Patrick M ; Zafarmand, Mohammad Hadi ; Strnad, Pavel</creatorcontrib><description>Introduction Association between elevated cytokeratin 18 (CK-18) levels and hepatocyte death has made circulating CK-18 a candidate biomarker to differentiate non-alcoholic fatty liver from non-alcoholic steatohepatitis (NASH). Yet studies produced variable diagnostic performance. We aimed to provide summary estimates with increased precision for the accuracy of CK-18 (M30, M65) in detecting NASH and fibrosis among non-alcoholic fatty liver disease (NAFLD) adults. Methods We searched five databases to retrieve studies evaluating CK-18 against a liver biopsy in NAFLD adults. Reference screening, data extraction and quality assessment (QUADAS-2) were independently conducted by two authors. Meta-analyses were performed for five groups based on the CK-18 antigens and target conditions, using one of two methods: linear mixed-effects multiple thresholds model or bivariate logit-normal random-effects model. Results We included 41 studies, with data on 5,815 participants. A wide range of disease prevalence was observed. No study reported a pre-defined cut-off. Thirty of 41 studies provided sufficient data for inclusion in any of the meta-analyses. Summary AUC [95% CI] were: 0.75 [0.69-0.82] (M30) and 0.82 [0.69-0.91] (M65) for NASH; 0.73 [0.57-0.85] (M30) for fibrotic NASH; 0.68 (M30) for significant (F2-4) fibrosis; and 0.75 (M30) for advanced (F3-4) fibrosis. Thirteen studies used CK-18 as a component of a multimarker model. Conclusions For M30 we found lower diagnostic accuracy to detect NASH compared to previous meta-analyses, indicating a limited ability to act as a stand-alone test, with better performance for M65. Additional external validation studies are needed to obtain credible estimates of the diagnostic accuracy of multimarker models.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0238717</identifier><identifier>PMID: 32915852</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Accuracy ; Adults ; Antigens ; Apoptosis ; Biology and Life Sciences ; Biomarkers ; Biopsy ; Bivariate analysis ; Cytokeratin ; Development and progression ; Diagnosis ; Diagnostic systems ; Epidemiology ; Fatty liver ; Fibrosis ; Health aspects ; Health risks ; Keratin ; Laboratories ; Life Sciences ; Liver ; Liver diseases ; Medicine and Health Sciences ; Meta-analysis ; Methods ; Model accuracy ; Obesity ; Patients ; Physical Sciences ; Physiological aspects ; Proteins ; Quality assessment ; Quality control ; Research and Analysis Methods ; Systematic review</subject><ispartof>PloS one, 2020-09, Vol.15 (9), p.e0238717-e0238717</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Lee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><rights>2020 Lee et al 2020 Lee et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c670t-68d47af6c9c3dd03375c2b61732f788c02847beddb2ff862dad9056c4d37648f3</citedby><cites>FETCH-LOGICAL-c670t-68d47af6c9c3dd03375c2b61732f788c02847beddb2ff862dad9056c4d37648f3</cites><orcidid>0000-0002-9518-0088 ; 0000-0001-7002-118X ; 0000-0003-4024-0933</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485872/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485872/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53770,53772,79347,79348</link.rule.ids><backlink>$$Uhttps://univ-angers.hal.science/hal-03284331$$DView record in HAL$$Hfree_for_read</backlink></links><search><contributor>Strnad, Pavel</contributor><creatorcontrib>Lee, Jenny</creatorcontrib><creatorcontrib>Vali, Yasaman</creatorcontrib><creatorcontrib>Boursier, Jérôme</creatorcontrib><creatorcontrib>Duffin, Kevin</creatorcontrib><creatorcontrib>Verheij, Joanne</creatorcontrib><creatorcontrib>Brosnan, M. Julia</creatorcontrib><creatorcontrib>Zwinderman, Koos</creatorcontrib><creatorcontrib>Anstee, Quentin M</creatorcontrib><creatorcontrib>Bossuyt, Patrick M</creatorcontrib><creatorcontrib>Zafarmand, Mohammad Hadi</creatorcontrib><title>Accuracy of cytokeratin 18 (M30 and M65) in detecting non-alcoholic steatohepatitis and fibrosis: A systematic review and meta-analysis</title><title>PloS one</title><description>Introduction Association between elevated cytokeratin 18 (CK-18) levels and hepatocyte death has made circulating CK-18 a candidate biomarker to differentiate non-alcoholic fatty liver from non-alcoholic steatohepatitis (NASH). Yet studies produced variable diagnostic performance. We aimed to provide summary estimates with increased precision for the accuracy of CK-18 (M30, M65) in detecting NASH and fibrosis among non-alcoholic fatty liver disease (NAFLD) adults. Methods We searched five databases to retrieve studies evaluating CK-18 against a liver biopsy in NAFLD adults. Reference screening, data extraction and quality assessment (QUADAS-2) were independently conducted by two authors. Meta-analyses were performed for five groups based on the CK-18 antigens and target conditions, using one of two methods: linear mixed-effects multiple thresholds model or bivariate logit-normal random-effects model. Results We included 41 studies, with data on 5,815 participants. A wide range of disease prevalence was observed. No study reported a pre-defined cut-off. Thirty of 41 studies provided sufficient data for inclusion in any of the meta-analyses. Summary AUC [95% CI] were: 0.75 [0.69-0.82] (M30) and 0.82 [0.69-0.91] (M65) for NASH; 0.73 [0.57-0.85] (M30) for fibrotic NASH; 0.68 (M30) for significant (F2-4) fibrosis; and 0.75 (M30) for advanced (F3-4) fibrosis. Thirteen studies used CK-18 as a component of a multimarker model. Conclusions For M30 we found lower diagnostic accuracy to detect NASH compared to previous meta-analyses, indicating a limited ability to act as a stand-alone test, with better performance for M65. Additional external validation studies are needed to obtain credible estimates of the diagnostic accuracy of multimarker models.</description><subject>Accuracy</subject><subject>Adults</subject><subject>Antigens</subject><subject>Apoptosis</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>Biopsy</subject><subject>Bivariate analysis</subject><subject>Cytokeratin</subject><subject>Development and progression</subject><subject>Diagnosis</subject><subject>Diagnostic systems</subject><subject>Epidemiology</subject><subject>Fatty liver</subject><subject>Fibrosis</subject><subject>Health aspects</subject><subject>Health risks</subject><subject>Keratin</subject><subject>Laboratories</subject><subject>Life Sciences</subject><subject>Liver</subject><subject>Liver diseases</subject><subject>Medicine and Health Sciences</subject><subject>Meta-analysis</subject><subject>Methods</subject><subject>Model accuracy</subject><subject>Obesity</subject><subject>Patients</subject><subject>Physical Sciences</subject><subject>Physiological aspects</subject><subject>Proteins</subject><subject>Quality assessment</subject><subject>Quality control</subject><subject>Research and Analysis Methods</subject><subject>Systematic review</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNptkl1v0zAUhiMEYmPwD5CwxM12keKPxHa4mFRNwCZt4gauLdcfrUsSFzst6i_gb3PSBkSnKReOznne136PTlG8JXhGmCAf1nGbet3ONrF3M0yZFEQ8K85Jw2jJKWbP__s_K17lvMa4ZpLzl8UZow2pZU3Pi99zY7ZJmz2KHpn9EH-4pIfQIyLR5QPDSPcWPfD6CkHNusEZaC5RH_tStyauYhsMyoPTQ1y5DSiHkA8aHxYp5pA_ojnKeyA6aBqU3C64Xweic4MuNUTYA_a6eOF1m92b6bwovn_-9O3mtrz_-uXuZn5fGi7wUHJpK6E9N41h1mLGRG3oghPBqBdSGkxlJRbO2gX1XnJqtW1wzU1lmeCV9OyieHf03bQxq2mGWdGqIjBAWddA3B0JG_VabVLodNqrqIM6FGJaKp0gSusU9QwLgrnnwlSeuMZbQ4W1lFmwkhK8rqfbtovOWeP6Ien2xPS004eVWsadEhXoBQWDq6PB6pHsdn6vxhpmkJgxsiPAXk6Xpfhz6_KgupCNa1vdu7g9ZKQUC85H9P0j9OlJTNRSQ9jQ-whvNKOpmnNWE84aOXrNnqDgs64LBpbTB6ifCKqjwMCC5OT8v2AEq3G1_z5GjautptVmfwCNTesu</recordid><startdate>20200911</startdate><enddate>20200911</enddate><creator>Lee, Jenny</creator><creator>Vali, Yasaman</creator><creator>Boursier, Jérôme</creator><creator>Duffin, Kevin</creator><creator>Verheij, Joanne</creator><creator>Brosnan, M. Julia</creator><creator>Zwinderman, Koos</creator><creator>Anstee, Quentin M</creator><creator>Bossuyt, Patrick M</creator><creator>Zafarmand, Mohammad Hadi</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>1XC</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-9518-0088</orcidid><orcidid>https://orcid.org/0000-0001-7002-118X</orcidid><orcidid>https://orcid.org/0000-0003-4024-0933</orcidid></search><sort><creationdate>20200911</creationdate><title>Accuracy of cytokeratin 18 (M30 and M65) in detecting non-alcoholic steatohepatitis and fibrosis: A systematic review and meta-analysis</title><author>Lee, Jenny ; Vali, Yasaman ; Boursier, Jérôme ; Duffin, Kevin ; Verheij, Joanne ; Brosnan, M. Julia ; Zwinderman, Koos ; Anstee, Quentin M ; Bossuyt, Patrick M ; Zafarmand, Mohammad Hadi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c670t-68d47af6c9c3dd03375c2b61732f788c02847beddb2ff862dad9056c4d37648f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Accuracy</topic><topic>Adults</topic><topic>Antigens</topic><topic>Apoptosis</topic><topic>Biology and Life Sciences</topic><topic>Biomarkers</topic><topic>Biopsy</topic><topic>Bivariate analysis</topic><topic>Cytokeratin</topic><topic>Development and progression</topic><topic>Diagnosis</topic><topic>Diagnostic systems</topic><topic>Epidemiology</topic><topic>Fatty liver</topic><topic>Fibrosis</topic><topic>Health aspects</topic><topic>Health risks</topic><topic>Keratin</topic><topic>Laboratories</topic><topic>Life Sciences</topic><topic>Liver</topic><topic>Liver diseases</topic><topic>Medicine and Health Sciences</topic><topic>Meta-analysis</topic><topic>Methods</topic><topic>Model accuracy</topic><topic>Obesity</topic><topic>Patients</topic><topic>Physical Sciences</topic><topic>Physiological aspects</topic><topic>Proteins</topic><topic>Quality assessment</topic><topic>Quality control</topic><topic>Research and Analysis Methods</topic><topic>Systematic review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Jenny</creatorcontrib><creatorcontrib>Vali, Yasaman</creatorcontrib><creatorcontrib>Boursier, Jérôme</creatorcontrib><creatorcontrib>Duffin, Kevin</creatorcontrib><creatorcontrib>Verheij, Joanne</creatorcontrib><creatorcontrib>Brosnan, M. Julia</creatorcontrib><creatorcontrib>Zwinderman, Koos</creatorcontrib><creatorcontrib>Anstee, Quentin M</creatorcontrib><creatorcontrib>Bossuyt, Patrick M</creatorcontrib><creatorcontrib>Zafarmand, Mohammad Hadi</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Jenny</au><au>Vali, Yasaman</au><au>Boursier, Jérôme</au><au>Duffin, Kevin</au><au>Verheij, Joanne</au><au>Brosnan, M. Julia</au><au>Zwinderman, Koos</au><au>Anstee, Quentin M</au><au>Bossuyt, Patrick M</au><au>Zafarmand, Mohammad Hadi</au><au>Strnad, Pavel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accuracy of cytokeratin 18 (M30 and M65) in detecting non-alcoholic steatohepatitis and fibrosis: A systematic review and meta-analysis</atitle><jtitle>PloS one</jtitle><date>2020-09-11</date><risdate>2020</risdate><volume>15</volume><issue>9</issue><spage>e0238717</spage><epage>e0238717</epage><pages>e0238717-e0238717</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Introduction Association between elevated cytokeratin 18 (CK-18) levels and hepatocyte death has made circulating CK-18 a candidate biomarker to differentiate non-alcoholic fatty liver from non-alcoholic steatohepatitis (NASH). Yet studies produced variable diagnostic performance. We aimed to provide summary estimates with increased precision for the accuracy of CK-18 (M30, M65) in detecting NASH and fibrosis among non-alcoholic fatty liver disease (NAFLD) adults. Methods We searched five databases to retrieve studies evaluating CK-18 against a liver biopsy in NAFLD adults. Reference screening, data extraction and quality assessment (QUADAS-2) were independently conducted by two authors. Meta-analyses were performed for five groups based on the CK-18 antigens and target conditions, using one of two methods: linear mixed-effects multiple thresholds model or bivariate logit-normal random-effects model. Results We included 41 studies, with data on 5,815 participants. A wide range of disease prevalence was observed. No study reported a pre-defined cut-off. Thirty of 41 studies provided sufficient data for inclusion in any of the meta-analyses. Summary AUC [95% CI] were: 0.75 [0.69-0.82] (M30) and 0.82 [0.69-0.91] (M65) for NASH; 0.73 [0.57-0.85] (M30) for fibrotic NASH; 0.68 (M30) for significant (F2-4) fibrosis; and 0.75 (M30) for advanced (F3-4) fibrosis. Thirteen studies used CK-18 as a component of a multimarker model. Conclusions For M30 we found lower diagnostic accuracy to detect NASH compared to previous meta-analyses, indicating a limited ability to act as a stand-alone test, with better performance for M65. Additional external validation studies are needed to obtain credible estimates of the diagnostic accuracy of multimarker models.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>32915852</pmid><doi>10.1371/journal.pone.0238717</doi><orcidid>https://orcid.org/0000-0002-9518-0088</orcidid><orcidid>https://orcid.org/0000-0001-7002-118X</orcidid><orcidid>https://orcid.org/0000-0003-4024-0933</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Accuracy Adults Antigens Apoptosis Biology and Life Sciences Biomarkers Biopsy Bivariate analysis Cytokeratin Development and progression Diagnosis Diagnostic systems Epidemiology Fatty liver Fibrosis Health aspects Health risks Keratin Laboratories Life Sciences Liver Liver diseases Medicine and Health Sciences Meta-analysis Methods Model accuracy Obesity Patients Physical Sciences Physiological aspects Proteins Quality assessment Quality control Research and Analysis Methods Systematic review |
| title | Accuracy of cytokeratin 18 (M30 and M65) in detecting non-alcoholic steatohepatitis and fibrosis: A systematic review and meta-analysis |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T15%3A18%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Accuracy%20of%20cytokeratin%2018%20(M30%20and%20M65)%20in%20detecting%20non-alcoholic%20steatohepatitis%20and%20fibrosis:%20A%20systematic%20review%20and%20meta-analysis&rft.jtitle=PloS%20one&rft.au=Lee,%20Jenny&rft.date=2020-09-11&rft.volume=15&rft.issue=9&rft.spage=e0238717&rft.epage=e0238717&rft.pages=e0238717-e0238717&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0238717&rft_dat=%3Cgale_plos_%3EA635163981%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2441871855&rft_id=info:pmid/32915852&rft_galeid=A635163981&rft_doaj_id=oai_doaj_org_article_2f307106f67c4f1e9fdc27dd23d18588&rfr_iscdi=true |