Are polypharmacy side effects predicted by public data still valid in real-world data?

Background and Objective: Although interest in predicting drug-drug interactions is growing, many predictions are not verified by real-world data. This study aimed to confirm whether predicted polypharmacy side effects using public data also occur in data from actual patients. Methods: We utilized a deep learning-based polypharmacy side effects prediction model to identify cefpodoxime-chlorpheniramine-lung edema combination with a high prediction score and a significant patient population. The retrospective study analyzed patients over 18 years old who were admitted to the Asan medical center between January 2000 and December 2020 and took cefpodoxime or chlorpheniramine orally. The three groups, cefpodoxime-treated, chlorpheniramine-treated, and cefpodoxime &amp; chlorpheniramine-treated were compared using inverse probability of treatment weighting (IPTW) to balance them. Differences between the three groups were analyzed using the Kaplan-Meier method and Cox proportional hazards model. Results: The study population comprised 54,043 patients with a history of taking cefpodoxime, 203,897 patients with a history of taking chlorpheniramine, and 1,628 patients with a history of taking cefpodoxime and chlorpheniramine simultaneously. After adjustment, the 1-year cumulative incidence of lung edema in the patient group that took cefpodoxime and chlorpheniramine simultaneously was significantly higher than in the patient groups that took cefpodoxime or chlorpheniramine only (p=0.001). Patients taking cefpodoxime and chlorpheniramine together had an increased risk of lung edema compared to those taking cefpodoxime alone [hazard ratio (HR) 2.10, 95% CI 1.26–3.52, p<0.005] and those taking chlorpheniramine alone, which also increased the risk of lung edema (HR 1.64, 95% CI 0.99-2.69, p=0.05). Conclusions: Validation of polypharmacy side effect predictions with real-world data can aid patient and clinician decision-making before conducting randomized controlled trials. Simultaneous use of cefpodoxime and chlorpheniramine was associated with a higher long-term risk of lung edema compared to the use of cefpodoxime or chlorpheniramine alone

Machine learning models to predict the warfarin discharge dosage using clinical information of inpatients from South Korea

Abstract As warfarin has a narrow therapeutic window and obvious response variability among individuals, it is difficult to rapidly determine personalized warfarin dosage. Adverse drug events(ADE) resulting from warfarin overdose can be critical, so that typically physicians adjust the warfarin dosage through the INR monitoring twice a week when starting warfarin. Our study aimed to develop machine learning (ML) models that predicts the discharge dosage of warfarin as the initial warfarin dosage using clinical data derived from electronic medical records within 2 days of hospitalization. During this retrospective study, adult patients who were prescribed warfarin at Asan Medical Center (AMC) between January 1, 2018, and October 31, 2020, were recruited as a model development cohort (n = 3168). Additionally, we created an external validation dataset (n = 891) from a Medical Information Mart for Intensive Care III (MIMIC-III). Variables for a model prediction were selected based on the clinical rationale that turned out to be associated with warfarin dosage, such as bleeding. The discharge dosage of warfarin was used the study outcome, because we assumed that patients achieved target INR at discharge. In this study, four ML models that predicted the warfarin discharge dosage were developed. We evaluated the model performance using the mean absolute error (MAE) and prediction accuracy. Finally, we compared the accuracy of the predictions of our models and the predictions of physicians for 40 data point to verify a clinical relevance of the models. The MAEs obtained using the internal validation set were as follows: XGBoost, 0.9; artificial neural network, 0.9; random forest, 1.0; linear regression, 1.0; and physicians, 1.3. As a result, our models had better prediction accuracy than the physicians, who have difficulty determining the warfarin discharge dosage using clinical information obtained within 2 days of hospitalization. We not only conducted the internal validation but also external validation. In conclusion, our ML model could help physicians predict the warfarin discharge dosage as the initial warfarin dosage from Korean population. However, conducting a successfully external validation in a further work is required for the application of the models

Anticoagulation therapy promotes the tumor immune-microenvironment and potentiates the efficacy of immunotherapy by alleviating hypoxia

Purpose Here, this study verifies that cancer-associated thrombosis (CAT) accelerates hypoxia, which is detrimental to the tumor immune microenvironment by limiting tumor perfusion. Therefore, we designed an oral anticoagulant therapy to improve the immunosuppressive tumor microenvironment and potentiate the efficacy of immunotherapy by alleviating tumor hypoxia. Experimental design A novel oral anticoagulant (STP3725) was developed to consistently prevent CAT formation. Tumor perfusion and hypoxia were analyzed with or without treating STP3725 in wild-type and P selectin knockout mice. Immunosuppressive cytokines and cells were analyzed to evaluate the alteration of the tumor microenvironment. Effector lymphocyte infiltration in tumor tissue was assessed by congenic CD45.1 mouse lymphocyte transfer model with or without anticoagulant therapy. Finally, various tumor models including K-Ras mutant spontaneous cancer model were employed to validate the role of the anticoagulation therapy in enhancing the efficacy of immunotherapy. Results CAT was demonstrated to be one of the perfusion barriers, which fosters immunosuppressive microenvironment by accelerating tumor hypoxia. Consistent treatment of oral anticoagulation therapy was proved to promote tumor immunity by alleviating hypoxia. Furthermore, this resulted in decrease of both hypoxia-related immunosuppressive cytokines and myeloid-derived suppressor cells while improving the spatial distribution of effector lymphocytes and their activity. The anticancer efficacy of alpha PD-1 antibody was potentiated by co-treatment with STP3725, also confirmed in various tumor models including the K-Ras mutant mouse model, which is highly thrombotic. Conclusions Collectively, these findings establish a rationale for a new and translational combination strategy of oral anticoagulation therapy with immunotherapy, especially for treating highly thrombotic cancers. The combination therapy of anticoagulants with immunotherapies can lead to substantial improvements of current approaches in the clinic.Y

Proceedings of the first MadAnalysis 5 workshop on LHC recasting in Korea

International audienceWe present the activities performed during the first MadAnalysis 5 workshop on LHC recasting that has been organized at High 1 (Gangwon privince, Korea) on August 20-27, 2017. This report includes details on the implementation in the MadAnalysis 5 framework of eight ATLAS and CMS analyses, as well as a description of the corresponding validation and the various issues that have been observed