Clinical factors predicting drug-induced liver injury due to flucloxacillin

Lindh, Mikaela; Hallberg, Pär; Yue, Qun‐Ying; Wadelius, Mia

doi:10.2147/dhps.s178394

Cited by 8 publications

(6 citation statements)

References 23 publications

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“…For ulipristal acetate, it was due to the structural features shared with telapristone acetate [49] and onapristone [50], which had been demonstrated to be idiosyncratic. Flucloxacillin HLA-B*57:01 is indicated as a clinical risk factor for idiosyncratic DILI [47]. However, the DNN model identified only fasiglifam and flucloxacillin as DILI-positives; the DILI properties of the two drugs might arise from their structures, although there has been no supportive report in that regard.…”

Section: Discussionmentioning

confidence: 99%

“…Although they had various indications, the DILI test results demonstrated that, except for ulipristal acetate and ligandrol, all drugs were predicted correctly as DILI-positives with a mean accuracy of 0.867. In particular, three of the 15 drugs, namely, fasiglifam, ulipristal acetate [46], and flucloxacillin [47], showed liabilities for idiosyncratic DILI. Fasiglifam was suggested to be idiosyncratic due to the delayed increase in alanine aminotransferase in some patients [48].…”

Section: Discussionmentioning

confidence: 99%

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Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space

Kang

2021

Molecules

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Drug-induced liver injury (DILI) is a major concern for drug developers, regulators, and clinicians. However, there is no adequate model system to assess drug-associated DILI risk in humans. In the big data era, computational models are expected to play a revolutionary role in this field. This study aimed to develop a deep neural network (DNN)-based model using extended connectivity fingerprints of diameter 4 (ECFP4) to predict DILI risk. Each data set for the predictive model was retrieved and curated from DILIrank, LiverTox, and other literature. The best model was constructed through ten iterations of stratified 10-fold cross-validation, and the applicability domain was defined based on integer ECFP4 bits of the training set which represented substructures. For the robustness test, we employed the concept of the endurance level. The best model showed an accuracy of 0.731, a sensitivity of 0.714, and a specificity of 0.750 on the validation data set in the complete applicability domain. The model was further evaluated with four external data sets and attained an accuracy of 0.867 on 15 drugs with DILI cases reported since 2019. Overall, the results suggested that the ECFP4-based DNN model represents a new tool to identify DILI risk for the evaluation of drug safety.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space

Kang

2021

Molecules

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“…Other studies showed that in general the incidence of hypokalaemia and associated hospitalization is higher among females 1,11–14 . Females are also more at risk for other flucloxacillin‐induced adverse events, including drug‐induced liver injury and metabolic acidosis 15,16 …”

Section: Introductionmentioning

confidence: 99%

“…1,[11][12][13][14] Females are also more at risk for other flucloxacillin-induced adverse events, including drug-induced liver injury and metabolic acidosis. 15,16 Considering the limited knowledge about the incidence, risk factors and potential influence of sex on flucloxacillin-induced hypokalaemia, a retrospective cohort study was performed. The primary aim of this study was to determine the incidence of flucloxacillininduced hypokalaemia.…”

Section: Introductionmentioning

confidence: 99%

Hypokalaemia in patients treated with intravenous flucloxacillin: Incidence and risk factors

Leegwater

Westgeest

Schippers

et al. 2022

Brit J Clinical Pharma

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Introduction Hypokalaemia is a potentially life‐threatening adverse event of flucloxacillin with unknown incidence. The risk of flucloxacillin‐induced hypokalaemia has recently been suggested to be increased among females compared to males. The aim of this study is to describe the incidence and to determine the influence of sex and other risk factors on flucloxacillin‐induced hypokalaemia. Methods A retrospective single‐centre cohort study was performed. Patients treated with intravenous flucloxacillin for >24 hours between January 2017 and October 2020, a baseline potassium level of ≥3.5 mmol/L and potassium measurement during treatment were included. The primary endpoint was incidence of hypokalaemia defined as the percentage of patients with a potassium measurement <3.5 mmol/L during flucloxacillin treatment. Logistic regression modelling was used to establish risk factors for hypokalaemia. Results A total of 835 patients were included, 58.2% male and median age 71.0 years (interquartile range 61.0‐81.0). The incidence of hypokalaemia was 23.7% (28.4% in females vs 20.4% in males). A dose‐dependent relation between sex and the incidence of hypokalaemia was found. The risk of hypokalaemia was 4.41 (95% confidence interval 1.47‐13.24) times higher in females compared to males when receiving a flucloxacillin dose of >8 g/24 h. No sex differences were found for lower daily doses. Other risk factors for hypokalaemia were older age, concomitant antibiotic use, lower bodyweight, lower baseline plasma potassium concentration and longer treatment duration. Conclusion Hypokalaemia is a frequent complication in patients treated with intravenous flucloxacillin. Females receiving >8 g intravenous flucloxacillin per day are more prone to develop hypokalaemia compared to males.

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“…Antibiotics are considered the most commonly implicated drug category in idiosyncratic DILI development ( Katarey and Verma, 2016 ; Björnsson, 2017 ). Flucloxacillin and co-amoxiclav are well-tolerated beta-lactam penicillins and widely used in clinical practice with an acceptable safety profile; however, they have been reported to cause DILI ( Donati et al, 2017 ; Lindh et al, 2018 ; Teixeira et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Impact of SLCO1B1*5 on Flucloxacillin and Co-Amoxiclav–Related Liver Injury

2022

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Background: Idiosyncratic drug-induced liver injury (DILI) is a serious uncommon disease that may develop as a result of the intake of certain drugs such as the antimicrobials flucloxacillin and co-amoxiclav. The reported cases showed significant associations between DILI and various human leukocyte (HLA) markers. The solute carrier organic anion transporter 1B1 (SLCO1B1), a non-HLA candidate gene, was previously reported as a risk factor for liver injury induced by rifampin and methimazole. This study presumed that SLCO1B1 may play a general role in the DILI susceptibility and therefore investigated the association of rs4149056 (SLCO1B1*5, T521C) polymorphism with flucloxacillin- and co-amoxiclav–induced liver injury.Methodology: We recruited 155 and 165 DILI cases of white ancestral origin from various European countries but mainly from the United Kingdom owing to flucloxacillin and co-amoxiclav, respectively. Only adult patients (≥18 years) who were diagnosed with liver injury and who showed i) clinical jaundice or bilirubin >2x the upper limit of normal (ULN), ii) alanine aminotransferase (ALT) >5x ULN or iii) alkaline phosphatase (ALP) >2x ULN and bilirubin > ULN were selected. The population reference sample (POPRES), a European control group (n = 282), was used in comparison with the investigated cases. TaqMan SNP genotyping custom assay designed by Applied Biosystems was used to genotype both DILI cohorts for SLCO1B1 polymorphism (rs4149056). Allelic discrimination analysis was performed using a step one real-time PCR machine. Genotype differences between cases and controls were examined using Fisher’s exact test. GraphPad Prism version 5.0 was used to determine the p-value, odds ratio, and 95% confidence interval. Compliance of the control group with Hardy–Weinberg equilibrium was proven using a web-based calculator available at https://wpcalc.com/en/equilibrium-hardy-weinberg/.Results: A small number of cases failed genotyping in each cohort. Thus, only 149 flucloxacillin and 162 co-amoxiclav DILI cases were analyzed. Genotyping of both DILI cohorts did not show evidence of association with the variant rs4149056 (T521C) (OR = 0.71, 95% CI = 0.46–1.12; p = 0.17 for flucloxacillin cases and OR = 0.87, 95% CI = 0.56–1.33; p = 0.58 for co-amoxiclav), although slightly lower frequency (22.8%) of positive flucloxacillin cases was noticed than that of POPRES controls (29.4%).Conclusion: Carriage of the examined allele SLCO1B1*5 is not considered a risk factor for flucloxacillin DILI or co-amoxiclav DILI as presumed. Testing a different allele (SLCO1B1*1B) and another family member gene (SLCO1B3) may still be needed to provide a clearer role of SLCO1B drug transporters in DILI development–related to the chosen antimicrobials.

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Clinical factors predicting drug-induced liver injury due to flucloxacillin

Cited by 8 publications

References 23 publications

Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space

Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space

Hypokalaemia in patients treated with intravenous flucloxacillin: Incidence and risk factors

Impact of SLCO1B1*5 on Flucloxacillin and Co-Amoxiclav–Related Liver Injury

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