@article{ref1,
title="A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)",
journal="PLoS one",
year="2022",
author="Tillmann, Hans L. and Suzuki, Ayako and Merz, Michael and Hermann, Richard and Rockey, Don C.",
volume="17",
number="9",
pages="e0271304-e0271304",
abstract="BACKGROUND AND AIMS: 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. <br><br>METHODS: 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 &quot;core&quot;) for the 3 variables in published datasets. <br><br>RESULTS: 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. <br><br>CONCLUSIONS: 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.<p /> <p>Language: en</p>",
language="en",
issn="1932-6203",
doi="10.1371/journal.pone.0271304",
url="http://dx.doi.org/10.1371/journal.pone.0271304"
}