A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)
We hypothesized that a drug's clinical signature (or phenotype) of liver injury can be assessed and used to quantitatively develop a computer-assisted DILI causality assessment-tool (DILI-CAT). Therefore, we evaluated drug-specific DILI-phenotypes for amoxicillin-clavulanate (AMX/CLA), cefazoli...
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| Veröffentlicht in: | PloS one 2022-09, Vol.17 (9), p.e0271304 |
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| creator | Tillmann, Hans L Suzuki, Ayako Merz, Michael Hermann, Richard Rockey, Don C |
| description | We hypothesized that a drug's clinical signature (or phenotype) of liver injury can be assessed and used to quantitatively develop a computer-assisted DILI causality assessment-tool (DILI-CAT). Therefore, we evaluated drug-specific DILI-phenotypes for amoxicillin-clavulanate (AMX/CLA), cefazolin, cyproterone, and Polygonum multiflorum using data from published case series, to develop DILI-CAT scores for each drug. Drug specific phenotypes were made up of the following three clinical features: (1) latency, (2) R-value, and (3) AST/ALT ratio. A point allocation system was developed with points allocated depending on the variance from the norm (or "core") for the 3 variables in published datasets. The four drugs had significantly different phenotypes based on latency, R-value, and AST/ALT ratio. The median cyproterone latency was 150 days versus < 43 days for the other three drugs (median: 26 for AMX/CLA, 20 for cefazolin, and 20 for Polygonum multiflorum; p |
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Therefore, we evaluated drug-specific DILI-phenotypes for amoxicillin-clavulanate (AMX/CLA), cefazolin, cyproterone, and Polygonum multiflorum using data from published case series, to develop DILI-CAT scores for each drug. Drug specific phenotypes were made up of the following three clinical features: (1) latency, (2) R-value, and (3) AST/ALT ratio. A point allocation system was developed with points allocated depending on the variance from the norm (or "core") for the 3 variables in published datasets. The four drugs had significantly different phenotypes based on latency, R-value, and AST/ALT ratio. The median cyproterone latency was 150 days versus < 43 days for the other three drugs (median: 26 for AMX/CLA, 20 for cefazolin, and 20 for Polygonum multiflorum; p<0.001). The R-value for the four drugs was also significantly different among drugs (cyproterone [median 12.4] and Polygonum multiflorum [median 10.9]) from AMX/CLA [median 1.44] and cefazolin [median 1.57; p<0.001]). DILI-CAT scores effectively separated cyproterone and Polygonum multiflorum from AMX/CLA and cefazolin, respectively (p<0.001). As expected, because of phenotypic overlap, AMX/CLA and cefazolin could not be well differentiated. DILI-CAT is a data-driven, diagnostic tool built to define drug-specific phenotypes for DILI adjudication. The data provide proof of principle that a drug-specific, data-driven causality assessment tool can be developed for different drugs and raise the possibility that such a process could enhance causality assessment methods.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0271304</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Adverse and side effects ; Amoxicillin ; Analysis ; Aquatic plants ; Biology and Life Sciences ; Causality ; Cefazolin ; Computer-aided medical diagnosis ; Diagnosis ; Drugs ; Genotype & phenotype ; Latency ; Liver ; Liver diseases ; Medical diagnosis ; Medicine and Health Sciences ; Methods ; Normal distribution ; Phenotype ; Phenotypes ; Physical Sciences ; Polygonum multiflorum ; Research and Analysis Methods ; Variables</subject><ispartof>PloS one, 2022-09, Vol.17 (9), p.e0271304</ispartof><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c669t-5cc1896fdd195c062e15f8c1ff064e06ac152ecd207e3d89dcc82dfe779af9833</citedby><cites>FETCH-LOGICAL-c669t-5cc1896fdd195c062e15f8c1ff064e06ac152ecd207e3d89dcc82dfe779af9833</cites><orcidid>0000-0003-1401-2208</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/PMC9521919/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521919/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids></links><search><creatorcontrib>Tillmann, Hans L</creatorcontrib><creatorcontrib>Suzuki, Ayako</creatorcontrib><creatorcontrib>Merz, Michael</creatorcontrib><creatorcontrib>Hermann, Richard</creatorcontrib><creatorcontrib>Rockey, Don C</creatorcontrib><title>A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)</title><title>PloS one</title><description>We hypothesized that a drug's clinical signature (or phenotype) of liver injury can be assessed and used to quantitatively develop a computer-assisted DILI causality assessment-tool (DILI-CAT). Therefore, we evaluated drug-specific DILI-phenotypes for amoxicillin-clavulanate (AMX/CLA), cefazolin, cyproterone, and Polygonum multiflorum using data from published case series, to develop DILI-CAT scores for each drug. Drug specific phenotypes were made up of the following three clinical features: (1) latency, (2) R-value, and (3) AST/ALT ratio. A point allocation system was developed with points allocated depending on the variance from the norm (or "core") for the 3 variables in published datasets. The four drugs had significantly different phenotypes based on latency, R-value, and AST/ALT ratio. The median cyproterone latency was 150 days versus < 43 days for the other three drugs (median: 26 for AMX/CLA, 20 for cefazolin, and 20 for Polygonum multiflorum; p<0.001). The R-value for the four drugs was also significantly different among drugs (cyproterone [median 12.4] and Polygonum multiflorum [median 10.9]) from AMX/CLA [median 1.44] and cefazolin [median 1.57; p<0.001]). DILI-CAT scores effectively separated cyproterone and Polygonum multiflorum from AMX/CLA and cefazolin, respectively (p<0.001). As expected, because of phenotypic overlap, AMX/CLA and cefazolin could not be well differentiated. DILI-CAT is a data-driven, diagnostic tool built to define drug-specific phenotypes for DILI adjudication. The data provide proof of principle that a drug-specific, data-driven causality assessment tool can be developed for different drugs and raise the possibility that such a process could enhance causality assessment methods.</description><subject>Adverse and side effects</subject><subject>Amoxicillin</subject><subject>Analysis</subject><subject>Aquatic plants</subject><subject>Biology and Life Sciences</subject><subject>Causality</subject><subject>Cefazolin</subject><subject>Computer-aided medical diagnosis</subject><subject>Diagnosis</subject><subject>Drugs</subject><subject>Genotype & phenotype</subject><subject>Latency</subject><subject>Liver</subject><subject>Liver diseases</subject><subject>Medical diagnosis</subject><subject>Medicine and Health Sciences</subject><subject>Methods</subject><subject>Normal distribution</subject><subject>Phenotype</subject><subject>Phenotypes</subject><subject>Physical Sciences</subject><subject>Polygonum multiflorum</subject><subject>Research and 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Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tillmann, Hans L</au><au>Suzuki, Ayako</au><au>Merz, Michael</au><au>Hermann, Richard</au><au>Rockey, Don C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)</atitle><jtitle>PloS one</jtitle><date>2022-09-29</date><risdate>2022</risdate><volume>17</volume><issue>9</issue><spage>e0271304</spage><pages>e0271304-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>We hypothesized that a drug's clinical signature (or phenotype) of liver injury can be assessed and used to quantitatively develop a computer-assisted DILI causality assessment-tool (DILI-CAT). Therefore, we evaluated drug-specific DILI-phenotypes for amoxicillin-clavulanate (AMX/CLA), cefazolin, cyproterone, and Polygonum multiflorum using data from published case series, to develop DILI-CAT scores for each drug. Drug specific phenotypes were made up of the following three clinical features: (1) latency, (2) R-value, and (3) AST/ALT ratio. A point allocation system was developed with points allocated depending on the variance from the norm (or "core") for the 3 variables in published datasets. The four drugs had significantly different phenotypes based on latency, R-value, and AST/ALT ratio. The median cyproterone latency was 150 days versus < 43 days for the other three drugs (median: 26 for AMX/CLA, 20 for cefazolin, and 20 for Polygonum multiflorum; p<0.001). The R-value for the four drugs was also significantly different among drugs (cyproterone [median 12.4] and Polygonum multiflorum [median 10.9]) from AMX/CLA [median 1.44] and cefazolin [median 1.57; p<0.001]). DILI-CAT scores effectively separated cyproterone and Polygonum multiflorum from AMX/CLA and cefazolin, respectively (p<0.001). As expected, because of phenotypic overlap, AMX/CLA and cefazolin could not be well differentiated. DILI-CAT is a data-driven, diagnostic tool built to define drug-specific phenotypes for DILI adjudication. The data provide proof of principle that a drug-specific, data-driven causality assessment tool can be developed for different drugs and raise the possibility that such a process could enhance causality assessment methods.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><doi>10.1371/journal.pone.0271304</doi><tpages>e0271304</tpages><orcidid>https://orcid.org/0000-0003-1401-2208</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adverse and side effects Amoxicillin Analysis Aquatic plants Biology and Life Sciences Causality Cefazolin Computer-aided medical diagnosis Diagnosis Drugs Genotype & phenotype Latency Liver Liver diseases Medical diagnosis Medicine and Health Sciences Methods Normal distribution Phenotype Phenotypes Physical Sciences Polygonum multiflorum Research and Analysis Methods Variables |
| title | A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT) |
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