The method to detect the adverse drug events through the chronological relationship between the medication period and the presence of adverse reactions from electronic medical record systems. (Preprint)

BACKGROUND Taking medicine may cause a variety of adverse reactions. An enormous amount of money and effort are spent investigating adverse drug events (ADEs) in clinical trials and post-marketing surveillance. Real world data from multiple electronic medical records (EMRs) can make it easy to understand the ADEs that occur in actual patients. OBJECTIVE In this study, we generated a database of the patients’ medication history from the records of physician orders of EMR, which allowed the period of medication to be clearly identified. METHODS We developed the method to detect the ADE based on the chronological relationship between the presence of the adverse event and the medication period. To verify our method, we detected the ADE with alanine aminotransferase (ALT) elevation for aspirin, clopidogrel and ticlopidine. The accuracy of detecting ADE were examined by chart review and by the comparison with Roussel Uclaf Causality Assessment Method (RUCAM) which was known as standard method for detecting drug induced liver injury. RESULTS The calculated rates of ADE with ALT elevation for aspirin, clopidogrel and ticlopidine were 3.33%, 3.70% and 5.69%, respectively, which were in line with the rates of previous reports. We reviewed the medical records of the patients in whom ADE were detected. Our method accurately predicted ADE in 90%, 100% and 100%, of patients with ALT elevation from aspirin, clopidogrel, and ticlopidine, respectively. With the comparison of the RUCAM, only 3 patients were not detected as ADE by our method. CONCLUSIONS These findings demonstrate that the present method is effective for detecting ADE from EMR data.

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A method for systematic discovery of adverse drug events from clinical notes

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocv102 ◽

2015 ◽

Vol 22 (6) ◽

pp. 1196-1204 ◽

Cited By ~ 31

Author(s):

Guan Wang ◽

Kenneth Jung ◽

Rainer Winnenburg ◽

Nigam H Shah

Keyword(s):

Electronic Medical Records ◽

Medical Records ◽

Adverse Drug Events ◽

Area Under The Curve ◽

Data Sources ◽

Clinical Notes ◽

Post Marketing Surveillance ◽

Post Marketing ◽

Harmful Effects ◽

Positive Support

Abstract Objective Adverse drug events (ADEs) are undesired harmful effects resulting from use of a medication, and occur in 30% of hospitalized patients. The authors have developed a data-mining method for systematic, automated detection of ADEs from electronic medical records. Materials and Methods This method uses the text from 9.5 million clinical notes, along with prior knowledge of drug usages and known ADEs, as inputs. These inputs are further processed into statistics used by a discriminative classifier which outputs the probability that a given drug–disorder pair represents a valid ADE association. Putative ADEs identified by the classifier are further filtered for positive support in 2 independent, complementary data sources. The authors evaluate this method by assessing support for the predictions in other curated data sources, including a manually curated, time-indexed reference standard of label change events. Results This method uses a classifier that achieves an area under the curve of 0.94 on a held out test set. The classifier is used on 2 362 950 possible drug–disorder pairs comprised of 1602 unique drugs and 1475 unique disorders for which we had data, resulting in 240 high-confidence, well-supported drug-AE associations. Eighty-seven of them (36%) are supported in at least one of the resources that have information that was not available to the classifier. Conclusion This method demonstrates the feasibility of systematic post-marketing surveillance for ADEs using electronic medical records, a key component of the learning healthcare system.

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Circulatory Inflammatory Mediators in the Prediction of Anti-Tuberculous Drug-Induced Liver Injury Using RUCAM for Causality Assessment

Biomedicines ◽

10.3390/biomedicines9080891 ◽

2021 ◽

Vol 9 (8) ◽

pp. 891

Author(s):

Cheng-Maw Ho ◽

Chi-Ling Chen ◽

Chia-Hao Chang ◽

Meng-Rui Lee ◽

Jann-Yuan Wang ◽

...

Keyword(s):

Liver Injury ◽

Inflammatory Mediators ◽

Cox Regression ◽

Causality Assessment ◽

Area Under The Curve ◽

Assessment Method ◽

Drug Induced ◽

Drug Induced Liver Injury ◽

Tb Treatment ◽

Pre Treatment

Background: Anti-tuberculous (TB) medications are common causes of drug-induced liver injury (DILI). Limited data are available on systemic inflammatory mediators as biomarkers for predicting DILI before treatment. We aimed to select predictive markers among potential candidates and to formulate a predictive model of DILI for TB patients. Methods: Adult active TB patients from a prospective cohort were enrolled, and all participants received standard anti-tuberculous treatment. Development of DILI, defined as ≥5× ULN for alanine transaminase or ≥2.6× ULN of total bilirubin with causality assessment (RUCAM, Roussel Uclaf causality assessment method), was regularly monitored. Pre-treatment plasma was assayed for 15 candidates, and a set of risk prediction scores was established using Cox regression and receiver-operating characteristic analyses. Results: A total of 19 (7.9%) in 240 patients developed DILI (including six carriers of hepatitis B virus) following anti-TB treatment. Interleukin (IL)-22 binding protein (BP), interferon gamma-induced protein 1 (IP-10), soluble CD163 (sCD163), IL-6, and CD206 were significant univariable factors associated with DILI development, and the former three were backward selected as multivariable factors, with adjusted hazards of 0.20 (0.07–0.58), 3.71 (1.35–10.21), and 3.28 (1.07–10.06), respectively. A score set composed of IL-22BP, IP-10, and sCD163 had an improved area under the curve of 0.744 (p < 0.001). Conclusions: Pre-treatment IL-22BP was a protective biomarker against DILI development under anti-TB treatment, and a score set by additional risk factors of IP-10 and sCD163 employed an adequate DILI prediction.

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Causality assessment in drug-induced liver injury using a structured expert opinion process: Comparison to the Roussel-Uclaf causality assessment method

Hepatology ◽

10.1002/hep.23577 ◽

2010 ◽

Vol 51 (6) ◽

pp. 2117-2126 ◽

Cited By ~ 217

Author(s):

Don C. Rockey ◽

Leonard B. Seeff ◽

James Rochon ◽

James Freston ◽

Naga Chalasani ◽

...

Keyword(s):

Liver Injury ◽

Expert Opinion ◽

Causality Assessment ◽

Assessment Method ◽

Drug Induced ◽

Drug Induced Liver Injury ◽

Process Comparison

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Drug-induced neuropsychiatric adverse events using post-marketing surveillance

Current Clinical Pharmacology ◽

10.2174/1574884716666210215104540 ◽

2021 ◽

Vol 16 ◽

Author(s):

Tomohito Wakabayashi ◽

Takahiro Nakatsuji ◽

Hiroko Kambara ◽

Iku Niinomi ◽

Saki Oyama ◽

...

Keyword(s):

Spontaneous Reporting ◽

Abnormal Behavior ◽

Drug Event ◽

Reporting Odds Ratio ◽

Neuraminidase Inhibitors ◽

Disproportionality Analysis ◽

Drug Induced ◽

Real World Setting ◽

Post Marketing Surveillance ◽

Post Marketing

Background: Several studies reported that abnormal behavior was noted in pediatric patients receiving several drugs including neuraminidase inhibitors (NIs). However, information on drugs associated with abnormal behavior in a real-world setting remains limited. The purpose of this study was to clarify drugs associated with abnormal behavior using a spontaneous reporting system database. Methods: We performed a retrospective pharmacovigilance disproportionality analysis using the Japanese Adverse Drug Event Report database. Adverse event reports submitted to the Pharmaceuticals and Medical Devices Agency were analyzed. Drug associated with abnormal behavior were estimated using disproportionality analysis with calculation of the reporting odds ratio and 95% confidence interval. Results: A total of 1,144 reports of abnormal behavior were identified. Signals were detected showing the association of 4 including neuraminidase inhibitors (oseltamivir, zanamivir, laninamivir, and peramivir) with abnormal behavior, and these signals were stronger for oseltamivir than other neuraminidase inhibitors. Signals were also detected for acetaminophen and montelukast. Conclusion: Our results should raise physicians’ awareness of drugs associated with abnormal behavior, but further investigation of these medications is warranted.

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Simultaneous Detection of Drug-Induced Liver Injury Protein and microRNA Biomarkers Using Dynamic Chemical Labelling on a Luminex MAGPIX System

Analytica ◽

10.3390/analytica2040013 ◽

2021 ◽

Vol 2 (4) ◽

pp. 130-139

Author(s):

Antonio Marín-Romero ◽

Mavys Tabraue-Chávez ◽

Bárbara López-Longarela ◽

Mario A. Fara ◽

Rosario M. Sánchez-Martín ◽

...

Keyword(s):

Liver Injury ◽

Simultaneous Detection ◽

Single Step ◽

Qualitative And Quantitative Analysis ◽

Serum Samples ◽

Drug Induced ◽

Drug Induced Liver Injury ◽

Qualitative And Quantitative ◽

Post Marketing ◽

Mechanistic Basis

Drug-induced liver injury (DILI) is a potentially fatal adverse event and a leading cause for pre- and post-marketing drug withdrawal. Several multinational DILI initiatives have now recommended a panel of protein and microRNA (miRNA) biomarkers that can detect early liver injury and inform about mechanistic basis. This manuscript describes the development of seqCOMBO, a unique combo-multiplexed assay which combines the dynamic chemical labelling approach and an antibody-dependant method on the Luminex MAGPIX system. SeqCOMBO enables a versatile multiplexing platform to perform qualitative and quantitative analysis of proteins and miRNAs in patient serum samples simultaneously. To the best of our knowledge, this is the first method to profile protein and miRNA biomarkers to diagnose DILI in a single-step assay.

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ESTIMATION OF POSSIBILITY OF APPLICATION OF TIGERASE® (DORNASE ALFA) DRUG ON THE RESULTS OF A MULTICENTER SCIENTIFIC PROGRAM OF POST-MARKETING USE OF THE DRUG

PEDIATRIA Journal named after G N SPERANSKY ◽

10.24110/0031-403x-2021-100-3-218-226 ◽

2021 ◽

Vol 100 (3) ◽

pp. 218-226

Author(s):

E.I. Kondratyeva ◽

◽

V.V. Shadrina ◽

E.G. Furman ◽

A.Yu. Voronkova ◽

...

Keyword(s):

Medical Records ◽

Adverse Reactions ◽

Clinical Manifestations ◽

Scientific Program ◽

Bronchial Secretion ◽

Patient Complaints ◽

Clinical Observations ◽

Number Of Patients ◽

Gender And Age ◽

Post Marketing

The aim of the program was to study the tolerability of Tigerase® in patients with cystic fibrosis (CF) of all ages in rutine clinical practice. Study design: retrospective open uncontrolled comparative multicenter solid. Materials and methods of research: retrospective data of clinical observations were collected from medical records of patients with CF on the use of Tigerase®. Results: therapy with Tigerase® was well tolerated by 668 (93,4%) of 715 patients included in the study. In 47 (6,6%) patients, 127 adverse reactions (ADRs) associated with the use of Tigerase® were recorded. ADRs from the respiratory system were the most common. Of these, 24 (3,4%) were coughing and 10 (1,4%) had increased viscosity of bronchial secretion. Among all patients included in the study, the proportion of patients in whom ADRs were registered based on clinical manifestations (3,9%) did not differ statistically significantly from the proportion of patients in whom ADRs were recorded based on complaints only (2,8%) (p=0,30). The distribution of ADRs by the source of registration and place of residence of patients did not depend on their gender and age. Registration of ADRs in different regions of the country differed statistically significantly both in frequency and in the source of detection (p<0,001). ADRs were not recorded in several regions, and the largest number of ADRs were registered in patients living in Moscow, and most of them were based only on patient complaints. 22 patients (47% of the number of patients with ADR) had medical commissions for ADR, and only in 8 (17% of the number of patients with ADR) of them had expertise of specialists with experience in the treatment of patients with CF. In 29 patients (62% of the number of patients with ADR), the development of ADR did not require cessation of the Tigerase® therapy. Conclusion: in the majority of CF patients (93,4%) tolerated the Tigerase® therapy well.

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