A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)
<h4>Background and aims</h4> 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 amoxici...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521919/?tool=EBI |
| _version_ | 1811181661981769728 |
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| author | Hans L. Tillmann Ayako Suzuki Michael Merz Richard Hermann Don C. Rockey |
| author_facet | Hans L. Tillmann Ayako Suzuki Michael Merz Richard Hermann Don C. Rockey |
| author_sort | Hans L. Tillmann |
| collection | DOAJ |
| description | <h4>Background and aims</h4> 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. <h4>Methods</h4> 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. <h4>Results</h4> 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. <h4>Conclusions</h4> 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. |
| first_indexed | 2024-04-11T09:21:24Z |
| format | Article |
| id | doaj.art-548948ce8b004c42a7b62caad4263eed |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-11T09:21:24Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-548948ce8b004c42a7b62caad4263eed2022-12-22T04:32:10ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01179A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)Hans L. TillmannAyako SuzukiMichael MerzRichard HermannDon C. Rockey<h4>Background and aims</h4> 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. <h4>Methods</h4> 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. <h4>Results</h4> 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. <h4>Conclusions</h4> 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.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521919/?tool=EBI |
| spellingShingle | Hans L. Tillmann Ayako Suzuki Michael Merz Richard Hermann Don C. Rockey A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT) PLoS ONE |
| title | A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT) |
| title_full | A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT) |
| title_fullStr | A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT) |
| title_full_unstemmed | A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT) |
| title_short | A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT) |
| title_sort | novel quantitative computer assisted drug induced liver injury causality assessment tool dili cat |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521919/?tool=EBI |
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