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A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)

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  • Hans L Tillmann
  • Ayako Suzuki
  • Michael Merz
  • Richard Hermann
  • Don C Rockey

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. 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 “core”) for the 3 variables in published datasets. 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

Suggested Citation

  • Hans L Tillmann & Ayako Suzuki & Michael Merz & Richard Hermann & Don C Rockey, 2022. "A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT)," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-15, September.
    • Handle: RePEc:plo:pone00:0271304
    DOI: 10.1371/journal.pone.0271304
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