Acute liver failure requiring transplantation: A possible link to ulipristal acetate treatment?

Dinis-Oliveira, Ricardo Jorge; Vieira, Duarte Nuno

doi:10.1111/bcpt.13631

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…Another study reported frequent adverse symptoms and a higher rate of treatment discontinuation in women with adenomyosis or uterine leiomyomas [ 81 ]. Additionally, sporadic cases of liver injury and liver failure were reported during post-marketing experience, which decrease the UPA use worldwide [ 82 , 83 ]. Therefore, healthcare professionals should provide comprehensive information about the potential incidence of adverse symptoms to women considering ulipristal acetate treatment.…”

Section: The Role Of Medical Therapy For Treating Symptoms Related To...mentioning

confidence: 99%

Current Medical Therapy for Adenomyosis: From Bench to Bedside

Etrusco,

Barra,

Chiantera

et al. 2023

Drugs

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Adenomyosis, characterized by the growth of endometrial tissue within the uterine wall, poses significant challenges in treatment. The literature primarily focuses on managing abnormal uterine bleeding (AUB) and dysmenorrhea, the main symptoms of adenomyosis. Nonsteroidal anti-inflammatory drugs (NSAIDs) and tranexamic acid provide limited support for mild symptoms or symptom re-exacerbation during hormone therapy. The levonorgestrel-releasing intrauterine system (LNG-IUS) is commonly employed in adenomyosis management, showing promise in symptom improvement and reducing uterine size, despite the lack of standardized guidelines. Dienogest (DNG) also exhibits potential benefits, but limited evidence hinders treatment recommendations. Danazol, while effective, is limited by androgenic side effects. Combined oral contraceptives (COCs) may be less effective than progestins but can be considered for contraception in young patients. Gonadotropin-releasing hormone (GnRH) agonists effectively manage symptoms but induce menopausal symptoms with prolonged use. GnRH antagonists are a recent option requiring further investigation. Aromatase inhibitors (AIs) show promise in alleviating AUB and pelvic pain, but their safety necessitates exploration and limited use within trials for refractory patients. This review highlights the complexity of diagnosing adenomyosis, its coexistence with endometriosis and uterine leiomyomas, and its impact on fertility and quality of life, complicating treatment decisions. It emphasizes the need for research on guidelines for medical management, fertility outcomes, long-term effects of therapies, and exploration of new investigational targets. Future research should optimize therapeutic strategies, expand our understanding of adenomyosis and its management, and establish evidence-based guidelines to improve patient outcomes and quality of life.

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Section: The Role Of Medical Therapy For Treating Symptoms Related To...mentioning

confidence: 99%

Current Medical Therapy for Adenomyosis: From Bench to Bedside

Etrusco,

Barra,

Chiantera

et al. 2023

Drugs

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“…These results implied that our model had a good predictive performance to accurately identify DILI drugs. [27] 5,493,444 7.0% DILI-positive 0.999 Rilpivirine [28] 6,451,164 5.0% DILI-positive 0.994 Escitalopram [29] 146,570 5.0% DILI-positive 0.989 Nilotinib [30] 644,241 7.6% DILI-positive 0.982 Olmesartan [31] 158,781 6.3% DILI-positive 0.974 Mesterolone [32] 15,020 4.1% DILI-positive 0.971 Levothyroxine [33] 5819 3.9% DILI-positive 0.965 Zanubrutinib [34] 135,565,884 6.4% DILI-positive 0.922 Phenprobamate [35] 4770 2.8% DILI-positive 0.896 Apixaban [36] 10,182,969 5.5% DILI-positive 0.804 Fasiglifam [37] 24,857,286 7.0% DILI-positive 0.660 Pirfenidone [38] 40,632 2.6% DILI-positive 0.608 Ligandrol [39] 44,137,686 4.6% DILI-negative 0.378 Ulipristal acetate [40] 130,904 6.5% DILI-negative 0.036 DILI, drug-induced liver injury.…”

Section: Dili Prediction On Drugs That Have Case Reports On Liver Injurymentioning

confidence: 99%

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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Ulipristal

2022

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Acute liver failure requiring transplantation: A possible link to ulipristal acetate treatment?

Cited by 5 publications

References 19 publications

Current Medical Therapy for Adenomyosis: From Bench to Bedside

Current Medical Therapy for Adenomyosis: From Bench to Bedside

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

Ulipristal

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