New approach uses real-world data to identify the most potentially hepatotoxic medications

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Key takeaways:

  • Using real-world data, researchers identified 17 medications with acute liver injury incidence rates of at least 5 events per 10,000 person-years.
  • Of these, 11 were not included when based on case reports.

Researchers have developed a data-driven, systematic approach for classification of the most potentially hepatotoxic medications based on incidence rates of severe acute liver injury, rather than published case report counts.

“From a clinical standpoint, knowing the rate of severe ALI after starting a medication in real-world data will help determine which patients should be monitored more closely with liver-related laboratory tests during treatment,” Vincent Lo Re III, MD, MSCE, senior study author and associate professor of medicine and epidemiology at Penn Medicine, sad in a related university press release. “Incidence rates of severe ALI can be a valuable tool for determining a medication’s toxicity to the liver and when patients should be monitored, since incidence rates provide a truer, real-world look at this toxicity.

According to results, incidence of severe acute liver injury ranged from: 0 events; per 10,000 person-years to 86.4 events; per 10,000 person-years
Data derived from: Torgersen J, et al. JAMA Intern Med. 2024;doi:10.1001/jamainternmed.2024.1836.

“Case reports did not accurately reflect observed rates of ALI because they do not consider the number of persons exposed to a medication and cases of drug-induced liver injury are often underreported.”

Using data from the U.S. Department of Veterans Affairs, Lo Re and colleagues conducted a series of cohort studies to identify the most potentially hepatotoxic medications based on real-world incidence rates of severe acute liver injury (ALI). They included 7,899,888 patients (mean age, 64.4 years; 92.5% men) without preexisting liver or biliary disease who initiated any one of 194 medications — with at least four published reports of hepatotoxicity — in an outpatient setting between October 2000 and September 2021.

The primary outcome was hospitalization for severe ALI, defined as inpatient alanine aminotransferase level greater than 120 U/L with total bilirubin greater than 2 mg/dL or an international normalized ratio of 1.5 or higher with total bilirubin greater than 2 mg/dL, within the first 2 days of hospital admission.

According to results published in JAMA Internal Medicine, there were 1,739 hospitalizations for severe ALI, and researchers excluded 91 medications from primary analysis based on age- and sex-adjusted rates of severe ALI.

Overall, incidence rates of severe ALI ranged from 0 events per 10,000 person-years to 86.4 events per 10,000 person-years. Researchers identified seven medications — stavudine, erlotinib, lenalidomide or thalidomide, chlorpromazine, metronidazole, prochlorperazine and isoniazid — that demonstrated ALI incidence rates of at least 10 events and 10 medications — moxifloxacin, azathioprine, levofloxacin, clarithromycin, ketoconazole, fluconazole, captopril, amoxicillin-clavulanate, sulfamethoxazole-trimethoprim and ciprofloxacin — with rates between 5 and 9.9 events per 10,000 person-years.

Although these 17 medications had the highest reported rates of severe ALI, researchers classified 11 of them (64%) in lower categories of hepatotoxicity based on case report counts “that were likely not reflective of their true risk, since their incidence rates revealed higher levels of toxicity,” the release stated.

“The systematic approach that we developed enables successful measurement of the rates of liver toxicity after starting a medication,” Lo Re said in the release. “It wasn’t surprising that the case report counts did not accurately reflect observed rates of severe acute liver injury given the inherent limitations with case reports.”

He continued: “Importantly, our approach offers a method to allow regulatory agencies and the pharmaceutical industry to systematically investigate reports of drug-induced ALI in large populations.”


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