Predicting drug-induced liver injury from anti-tuberculous medications by early monitoring of liver tests

Patterson, Benjamin; Abbara, Ali; Collin, Simon M.; Henderson, Merle; Shehata, Monicka; Gorgui-Naguib, Hannah; Lynn, William; Kon, Onn Min; John, Laurence

doi:10.1016/j.jinf.2020.09.038

Cited by 15 publications

(15 citation statements)

References 13 publications

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“…In Taiwan, 15.9% of patients had liver abnormalities after their tuberculosis (TB) treatment and the authors suggest close monitoring of liver functions in patients with pre-existing liver disease 46 . Another study suggested that patients should routinely have liver tests during tuberculosis treatment to capture early DILI 47 .…”

Section: Discussionmentioning

confidence: 99%

Drug-induced liver injury causality assessment data from a crosssectional study in Brazil: a call for the use of updated RUCAM in hospital Pharmacy

LUNARDELLI¹,

Becker²,

ORTIZ³

et al. 2022

Rev Bras Farm Hosp Serv Saude

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Objective: to identify the frequency of DILI inpatients from abnormal liver enzyme levels using the updated Roussel Uclaf Causality Assessment Method (RUCAM) causality assessment algorithm, as well as to provide a descriptive analysis of DILI cases. Methods: we conducted a crosssectional study in a medium complexity hospital in southern Brazil. Data regarding DILI was collected retrospectively from electronic medical records (EMR) in 2015. Inclusion criteria were all adult patients (≥ 18 years old) who presented alanine aminotransferase (ALT) greater than twice the superior limit of normality (ALT > 60 UI/L) with concomitant change of aspartate aminotransferase (AST) or alkaline phosphatase (ALP) or change of ALP greater than twice the superior limit of normality (ALP > 250 UI/L) during hospitalization. The RUCAM was applied to all suspected DILI cases. Results: 84,134 inpatients in this period; 178 patients had abnormal liver tests, six patients had sufficient medical information to allow DILI causality assessment, and two patients had DILI described in EMR, although our group could not find suficient information to apply RUCAM retrospectively. Absence of information was mainly related to drug reconciliation at hospital admission, time of onset of suspected drug therapy and no description of previous clinical conditions in EMR. Four patients developed hepatic injury as a result of drug treatment initiated during hospitalization. Suspected drugs were antibiotics, nonsteroidal anti-inflammatory drugs, antiviral, tuberculostatics and platelet antiaggregant. Liver injury pattern was identified as hepatocellular and mixed. Conclusion: DILI appeared as a rare ADR, but absence of data in most EMR affected the application of RUCAM and underestimated DILI frequency. There is an urgency to develop DILI knowledge in Brazilian hospitals. Pharmacists must be aware of the use of the updated RUCAM to prospectively assess possible DILI cases. For future research, we suggest to combine cross-linking DILI tracers such as ICD-10 liver injury codes, abnormal liver biomarkers, search for trigger hepatotoxicity drugs and EMR text search tools, adding artificial intelligence to pharmacovigilance and hospital pharmacy.

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Section: Discussionmentioning

confidence: 99%

Drug-induced liver injury causality assessment data from a crosssectional study in Brazil: a call for the use of updated RUCAM in hospital Pharmacy

LUNARDELLI¹,

Becker²,

ORTIZ³

et al. 2022

Rev Bras Farm Hosp Serv Saude

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“…Previous studies have shown that TB-DILI is associated with some demographic characteristics and underlying chronic disease [12,[22][23][24][25][26]. Patterson et al [27] suggested that an increase in pretreatment ALT and the gradient of ALT changes increase the risk of late TB-DILI. Thus, in addition to the cumulative anti-TB drug dose, ALT levels and demographic variable such as age, gender, education level, income, and BMI were included in our model as predictors.…”

Section: Introductionmentioning

confidence: 99%

Predicting Antituberculosis Drug–Induced Liver Injury Using an Interpretable Machine Learning Method: Model Development and Validation Study

Zhong¹,

Zhuang²,

Dong³

et al. 2021

JMIR Med Inform

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Background Tuberculosis (TB) is a pandemic, being one of the top 10 causes of death and the main cause of death from a single source of infection. Drug-induced liver injury (DILI) is the most common and serious side effect during the treatment of TB. Objective We aim to predict the status of liver injury in patients with TB at the clinical treatment stage. Methods We designed an interpretable prediction model based on the XGBoost algorithm and identified the most robust and meaningful predictors of the risk of TB-DILI on the basis of clinical data extracted from the Hospital Information System of Shenzhen Nanshan Center for Chronic Disease Control from 2014 to 2019. Results In total, 757 patients were included, and 287 (38%) had developed TB-DILI. Based on values of relative importance and area under the receiver operating characteristic curve, machine learning tools selected patients’ most recent alanine transaminase levels, average rate of change of patients’ last 2 measures of alanine transaminase levels, cumulative dose of pyrazinamide, and cumulative dose of ethambutol as the best predictors for assessing the risk of TB-DILI. In the validation data set, the model had a precision of 90%, recall of 74%, classification accuracy of 76%, and balanced error rate of 77% in predicting cases of TB-DILI. The area under the receiver operating characteristic curve score upon 10-fold cross-validation was 0.912 (95% CI 0.890-0.935). In addition, the model provided warnings of high risk for patients in advance of DILI onset for a median of 15 (IQR 7.3-27.5) days. Conclusions Our model shows high accuracy and interpretability in predicting cases of TB-DILI, which can provide useful information to clinicians to adjust the medication regimen and avoid more serious liver injury in patients.

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“…1 DILI is the most prevalent and severe complication related to anti-TB treatment, with an incidence ranging from 2% to 28% of treated TB cases. 1,7 The onset of hepatotoxicity can occur within 7-90 days of starting anti-TB treatment. 1 DILI generally cause the temporary interruption of TB treatment due to therapy failure, relapses or drug resistance development.…”

Section: Discussionmentioning

confidence: 99%

Hepatoprotective effects of silymarin in management of liver injury caused by tuberculosis treatment

Lee¹,

Tee²

2023

DIC

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Tuberculosis (TB) is a chronic infection of global-health concern because of its high incidence, costly medical treatment, drug resistance and risk of co-infections. Anti-TB treatment involves a combination of drugs with high degree of liver toxicity, leading to drug-induced liver injury in 2–28% of patients who receive anti-TB treatment. In this case report, a patient with TB experienced drug-induced liver injury, and the initiation of treatment with silymarin 140 mg three-times daily resulted in a significant hepatoprotective effects as shown by the decreased liver enzyme activity. This article is part of the Current clinical use of silymarin in the treatment of toxic liver diseases: a case series Special Issue: https://www.drugsincontext.com/special_issues/current-clinical-use-of-silymarin-in-the-treatment-of-toxic-liver-diseases-a-case-series

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Predicting drug-induced liver injury from anti-tuberculous medications by early monitoring of liver tests

Cited by 15 publications

References 13 publications

Drug-induced liver injury causality assessment data from a crosssectional study in Brazil: a call for the use of updated RUCAM in hospital Pharmacy

Drug-induced liver injury causality assessment data from a crosssectional study in Brazil: a call for the use of updated RUCAM in hospital Pharmacy

Predicting Antituberculosis Drug–Induced Liver Injury Using an Interpretable Machine Learning Method: Model Development and Validation Study

Hepatoprotective effects of silymarin in management of liver injury caused by tuberculosis treatment

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