Pharmacoepidemiology and drug safety · 2025
High-Throughput Screening Using the Self-Controlled Tree-Based Scan Statistic to Identify Medications Associated With Hospitalization for Severe Acute Liver Injury.
СтатьяПоддержка NIH: внешняя программаПоддержка правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Lo Re Vincent, Newcomb Craig W, Carbonari Dean M, Leonard Charles E, Rentsch Christopher T, Maro Judith C
Аннотация
BACKGROUND: Medications associated with acute liver injury (ALI) are primarily identified by case reports. High-throughput screening of real-world data could be leveraged to detect hepatotoxicity signals.
OBJECTIVE: To apply tree-based scan statistics in real-world data to identify drugs associated with hospitalization for severe ALI among patients without liver/biliary disease and with chronic liver disease (CLD).
METHODS: We implemented a self-controlled case-crossover design in Veterans Health Administration data (2000-2023) among patients hospitalized for laboratory-confirmed severe ALI. We identified all newly dispensed drugs within 365 days prior to their hospitalization and used conditional Bernoulli tree-based scan statistics to identify potential associations (p < 0.3). We performed analyses separately in patients without liver/biliary disease and with CLD.
RESULTS: Among 12 860 patients without liver/biliary disease and 17 512 with CLD hospitalized for severe ALI, we evaluated associations with 450 and 543 drugs, respectively. Drugs associated with severe ALI among patients without liver/biliary disease included: acid-suppressives (ranitidine [p < 0.001], omeprazole [p = 0.004]), antiemetics (ondansetron [p < 0.001], promethazine [p = 0.06]), antibiotics (amoxicillin/clavulanate [p = 0.008], ciprofloxacin [p = 0.02], mupirocin [p = 0.032], ethambutol [p = 0.275]), anticoagulants (heparin [p = 0.015]), and chemotherapy (pazopanib [p = 0.275]). Drugs associated with severe ALI among CLD patients were: diuretics (spironolactone, furosemide [both p < 0.001]), antiemetics (ondansetron, metoclopramide, promethazine [all p < 0.001]), appetite stimulants (p < 0.001), analgesics (morphine, oxycodone, fentanyl [all p < 0.001]), chemotherapy (sorafenib [p < 0.001]), antibiotics (ciprofloxacin [p = 0.011], metronidazole [p = 0.020]), antipsychotics (prochlorperazine [p = 0.105]), vitamins (p = 0.134), acid-suppressives (omeprazole [p = 0.164]), and gastrointestinal/liver disease treatments (lactulose, senna, docusate, silicones, antiflatulents [all p < 0.001]; sucralfate [p = 0.005], albumin [p = 0.228]).
CONCLUSIONS: High-throughput screening using tree-based scan statistics detected potentially hepatotoxic drugs for investigation in future pharmacoepidemiology studies.
OBJECTIVE: To apply tree-based scan statistics in real-world data to identify drugs associated with hospitalization for severe ALI among patients without liver/biliary disease and with chronic liver disease (CLD).
METHODS: We implemented a self-controlled case-crossover design in Veterans Health Administration data (2000-2023) among patients hospitalized for laboratory-confirmed severe ALI. We identified all newly dispensed drugs within 365 days prior to their hospitalization and used conditional Bernoulli tree-based scan statistics to identify potential associations (p < 0.3). We performed analyses separately in patients without liver/biliary disease and with CLD.
RESULTS: Among 12 860 patients without liver/biliary disease and 17 512 with CLD hospitalized for severe ALI, we evaluated associations with 450 and 543 drugs, respectively. Drugs associated with severe ALI among patients without liver/biliary disease included: acid-suppressives (ranitidine [p < 0.001], omeprazole [p = 0.004]), antiemetics (ondansetron [p < 0.001], promethazine [p = 0.06]), antibiotics (amoxicillin/clavulanate [p = 0.008], ciprofloxacin [p = 0.02], mupirocin [p = 0.032], ethambutol [p = 0.275]), anticoagulants (heparin [p = 0.015]), and chemotherapy (pazopanib [p = 0.275]). Drugs associated with severe ALI among CLD patients were: diuretics (spironolactone, furosemide [both p < 0.001]), antiemetics (ondansetron, metoclopramide, promethazine [all p < 0.001]), appetite stimulants (p < 0.001), analgesics (morphine, oxycodone, fentanyl [all p < 0.001]), chemotherapy (sorafenib [p < 0.001]), antibiotics (ciprofloxacin [p = 0.011], metronidazole [p = 0.020]), antipsychotics (prochlorperazine [p = 0.105]), vitamins (p = 0.134), acid-suppressives (omeprazole [p = 0.164]), and gastrointestinal/liver disease treatments (lactulose, senna, docusate, silicones, antiflatulents [all p < 0.001]; sucralfate [p = 0.005], albumin [p = 0.228]).
CONCLUSIONS: High-throughput screening using tree-based scan statistics detected potentially hepatotoxic drugs for investigation in future pharmacoepidemiology studies.