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Crisafulli S, Bate A, Brown JS, Candore G, Chandler RE, Hammad TA, Lane S, Maro JC, Norén GN, Pariente A, Russom M, Salas M, Segec A, Shakir S, Spini A, Toh S, Tuccori M, van Puijenbroek E, Trifirò G. Interplay of Spontaneous Reporting and Longitudinal Healthcare Databases for Signal Management: Position Statement from the Real-World Evidence and Big Data Special Interest Group of the International Society of Pharmacovigilance. Drug Saf 2025:10.1007/s40264-025-01548-3. [PMID: 40223041 DOI: 10.1007/s40264-025-01548-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/25/2025] [Indexed: 04/15/2025]
Abstract
Signal management, defined as the set of activities from signal detection to recommendations for action, is conducted using different data sources and leveraging data from spontaneous reporting databases (SRDs), which represent the cornerstone of pharmacovigilance. However, the exponentially increasing generation and availability of real-world data collected in longitudinal healthcare databases (LHDs), along with the rapid evolution of artificial intelligence-based algorithms and other advanced analytical methods, offers a wide range of opportunities to complement SRDs throughout all stages of signal management, especially signal detection. Integrating information derived from SRDs and LHDs may reduce their respective limitations, thus potentially enhancing post-marketing surveillance. The aim of this position statement is to critically evaluate the complementary role of SRDs and LHDs in signal management, exploring the potential benefits and challenges in integrating information coming from these two data sources. Furthermore, we presented successful cases of the interplay between SRDs and LHDs for signal management, along with future opportunities and directions to improve such interplay.
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Affiliation(s)
- Salvatore Crisafulli
- Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37124, Verona, Italy
| | - Andrew Bate
- Global Safety, GSK, Brentford, UK
- Department of Non-Communicable Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Jeffrey Stuart Brown
- TriNetX, Cambridge, MA, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA, USA
| | | | | | - Tarek A Hammad
- Takeda Development Center Americas, Inc., Cambridge, MA, USA
| | - Samantha Lane
- Drug Safety Research Unit, Southampton, UK
- University of Portsmouth, Portsmouth, UK
| | | | | | - Antoine Pariente
- Université de Bordeaux, INSERM, BPH, Team AHeaD, U1219, 33000, Bordeaux, France
- Service de Pharmacologie Médicale, CHU de Bordeaux, INSERM, U1219, 33000, Bordeaux, France
| | - Mulugeta Russom
- National Medicines and Food Administration, Ministry of Health, Asmara, Eritrea
- Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Maribel Salas
- Bayer Pharmaceuticals Inc., Whippany, NJ, USA
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Andrej Segec
- Data Analytics and Methods Task Force, European Medicines Agency, Amsterdam, The Netherlands
| | - Saad Shakir
- Drug Safety Research Unit, Southampton, UK
- University of Portsmouth, Portsmouth, UK
| | - Andrea Spini
- Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37124, Verona, Italy
| | - Sengwee Toh
- Department of Population Medicine, Harvard Medical School, Boston, MA, USA
| | - Marco Tuccori
- Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37124, Verona, Italy
| | - Eugène van Puijenbroek
- Netherlands Pharmacovigilance Centre Lareb, 's-Hertogenbosch, The Netherlands
- PharmacoTherapy, Epidemiology and Economics, University of Groningen, Groningen Research Institute of Pharmacy, Groningen, The Netherlands
| | - Gianluca Trifirò
- Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37124, Verona, Italy.
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Davis SE, Zabotka L, Desai RJ, Wang SV, Maro JC, Coughlin K, Hernández-Muñoz JJ, Stojanovic D, Shah NH, Smith JC. Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review. Drug Saf 2023; 46:725-742. [PMID: 37340238 PMCID: PMC11635839 DOI: 10.1007/s40264-023-01325-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/31/2023] [Indexed: 06/22/2023]
Abstract
INTRODUCTION Pharmacovigilance programs protect patient health and safety by identifying adverse event signals through postmarketing surveillance of claims data and spontaneous reports. Electronic health records (EHRs) provide new opportunities to address limitations of traditional approaches and promote discovery-oriented pharmacovigilance. METHODS To evaluate the current state of EHR-based medication safety signal identification, we conducted a scoping literature review of studies aimed at identifying safety signals from routinely collected patient-level EHR data. We extracted information on study design, EHR data elements utilized, analytic methods employed, drugs and outcomes evaluated, and key statistical and data analysis choices. RESULTS We identified 81 eligible studies. Disproportionality methods were the predominant analytic approach, followed by data mining and regression. Variability in study design makes direct comparisons difficult. Studies varied widely in terms of data, confounding adjustment, and statistical considerations. CONCLUSION Despite broad interest in utilizing EHRs for safety signal identification, current efforts fail to leverage the full breadth and depth of available data or to rigorously control for confounding. The development of best practices and application of common data models would promote the expansion of EHR-based pharmacovigilance.
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Affiliation(s)
- Sharon E Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, 2525 West End Ave, Suite 1475, Nashville, TN, 37203, USA
- Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | - Rishi J Desai
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Shirley V Wang
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Judith C Maro
- Harvard Medical School, Boston, MA, USA
- Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | | | | | | | - Nigam H Shah
- School of Medicine, Stanford University, Stanford, CA, USA
- Stanford Health Care, Palo Alto, CA, USA
| | - Joshua C Smith
- Department of Biomedical Informatics, Vanderbilt University Medical Center, 2525 West End Ave, Suite 1475, Nashville, TN, 37203, USA.
- Vanderbilt University School of Medicine, Nashville, TN, USA.
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Bordon KDCF, Cologna CT, Fornari-Baldo EC, Pinheiro-Júnior EL, Cerni FA, Amorim FG, Anjolette FAP, Cordeiro FA, Wiezel GA, Cardoso IA, Ferreira IG, de Oliveira IS, Boldrini-França J, Pucca MB, Baldo MA, Arantes EC. From Animal Poisons and Venoms to Medicines: Achievements, Challenges and Perspectives in Drug Discovery. Front Pharmacol 2020; 11:1132. [PMID: 32848750 PMCID: PMC7396678 DOI: 10.3389/fphar.2020.01132] [Citation(s) in RCA: 152] [Impact Index Per Article: 30.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 07/13/2020] [Indexed: 12/16/2022] Open
Abstract
Animal poisons and venoms are comprised of different classes of molecules displaying wide-ranging pharmacological activities. This review aims to provide an in-depth view of toxin-based compounds from terrestrial and marine organisms used as diagnostic tools, experimental molecules to validate postulated therapeutic targets, drug libraries, prototypes for the design of drugs, cosmeceuticals, and therapeutic agents. However, making these molecules applicable requires extensive preclinical trials, with some applications also demanding clinical trials, in order to validate their molecular target, mechanism of action, effective dose, potential adverse effects, as well as other fundamental parameters. Here we go through the pitfalls for a toxin-based potential therapeutic drug to become eligible for clinical trials and marketing. The manuscript also presents an overview of the current picture for several molecules from different animal venoms and poisons (such as those from amphibians, cone snails, hymenopterans, scorpions, sea anemones, snakes, spiders, tetraodontiformes, bats, and shrews) that have been used in clinical trials. Advances and perspectives on the therapeutic potential of molecules from other underexploited animals, such as caterpillars and ticks, are also reported. The challenges faced during the lengthy and costly preclinical and clinical studies and how to overcome these hindrances are also discussed for that drug candidates going to the bedside. It covers most of the drugs developed using toxins, the molecules that have failed and those that are currently in clinical trials. The article presents a detailed overview of toxins that have been used as therapeutic agents, including their discovery, formulation, dosage, indications, main adverse effects, and pregnancy and breastfeeding prescription warnings. Toxins in diagnosis, as well as cosmeceuticals and atypical therapies (bee venom and leech therapies) are also reported. The level of cumulative and detailed information provided in this review may help pharmacists, physicians, biotechnologists, pharmacologists, and scientists interested in toxinology, drug discovery, and development of toxin-based products.
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Affiliation(s)
- Karla de Castro Figueiredo Bordon
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Camila Takeno Cologna
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | | | - Ernesto Lopes Pinheiro-Júnior
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Felipe Augusto Cerni
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Fernanda Gobbi Amorim
- Postgraduate Program in Pharmaceutical Sciences, Vila Velha University, Vila Velha, Brazil
| | | | - Francielle Almeida Cordeiro
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Gisele Adriano Wiezel
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Iara Aimê Cardoso
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Isabela Gobbo Ferreira
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Isadora Sousa de Oliveira
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | | | | | - Mateus Amaral Baldo
- Health and Science Institute, Paulista University, São José do Rio Pardo, Brazil
| | - Eliane Candiani Arantes
- Laboratory of Animal Toxins, Department of BioMolecular Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
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Kim SH. Active Pharmacovigilance of Drug-Induced Liver Injury Using Electronic Health Records. ALLERGY, ASTHMA & IMMUNOLOGY RESEARCH 2020; 12:378-380. [PMID: 32141253 PMCID: PMC7061153 DOI: 10.4168/aair.2020.12.3.378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/22/2020] [Accepted: 02/24/2020] [Indexed: 11/24/2022]
Affiliation(s)
- Sang Heon Kim
- Department of Internal Medicine, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Korea.
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Tang Y, Yang J, Ang PS, Dorajoo SR, Foo B, Soh S, Tan SH, Tham MY, Ye Q, Shek L, Sung C, Tung A. Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer. Int J Med Inform 2019; 128:62-70. [PMID: 31160013 DOI: 10.1016/j.ijmedinf.2019.04.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 03/22/2019] [Accepted: 04/21/2019] [Indexed: 12/19/2022]
Abstract
BACKGROUND Hospital discharge summaries offer a potentially rich resource to enhance pharmacovigilance efforts to evaluate drug safety in real-world clinical practice. However, it is infeasible for experts to read through all discharge summaries to find cases of drug-adverse event (AE) relations. PURPOSE The objective of this paper is to develop a natural language processing (NLP) framework to detect drug-AE relations from unstructured hospital discharge summaries. BASIC PROCEDURES An NLP algorithm was designed using customized dictionaries of drugs, adverse event (AE) terms, and rules based on trigger phrases, negations, fuzzy logic and word distances to recognize drug, AE terms and to detect drug-AE relations. Furthermore, a customized annotation tool was developed to facilitate expert review of discharge summaries from a tertiary hospital in Singapore in 2011. MAIN FINDINGS A total of 33 trial sets with 50 to 100 records per set were evaluated (1620 discharge summaries) by our algorithm and reviewed by pharmacovigilance experts. After every 6 trial sets, drug and AE dictionaries were updated, and rules were modified to improve the system. Excellent performance was achieved for drug and AE entity recognition with over 92% precision and recall. On the final 6 sets of discharge summaries (600 records), our algorithm achieved 75% precision and 59% recall for identification of valid drug-AE relations. PRINCIPAL CONCLUSIONS Adverse drug reactions are a significant contributor to health care costs and utilization. Our algorithm is not restricted to particular drugs, drug classes or specific medical specialties, which is an important attribute for a national regulatory authority to carry out comprehensive safety monitoring of drug products. Drug and AE dictionaries may be updated periodically to ensure that the tool remains relevant for performing surveillance activities. The development of the algorithm, and the ease of reviewing and correcting the results of the algorithm as part of an iterative machine learning process, is an important step towards use of hospital discharge summaries for an active pharmacovigilance program.
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Affiliation(s)
- Yixuan Tang
- Department of Computer Science, School of Computing, National University of Singapore, Singapore
| | - Jisong Yang
- Department of Computer Science, School of Computing, National University of Singapore, Singapore
| | - Pei San Ang
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore
| | - Sreemanee Raaj Dorajoo
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore
| | - Belinda Foo
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore
| | - Sally Soh
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore
| | - Siew Har Tan
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore
| | - Mun Yee Tham
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore
| | - Qing Ye
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore; Genome Institute of Singapore, Agency for Science and Technology, Singapore
| | - Lynette Shek
- Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore
| | - Cynthia Sung
- Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore; Health Services and Systems Research, Duke-NUS Medical School, Singapore
| | - Anthony Tung
- Department of Computer Science, School of Computing, National University of Singapore, Singapore.
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Wei R, Jia LL, Yu YC, Nie XL, Song ZY, Fan DF, Xie YF, Peng XX, Zhao ZG, Wang XL. Pediatric drug safety signal detection of non-chemotherapy drug-induced neutropenia and agranulocytosis using electronic healthcare records. Expert Opin Drug Saf 2019; 18:435-441. [PMID: 31002530 DOI: 10.1080/14740338.2019.1604682] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Objectives: This study aimed to develop a procedure to explore the adverse drug reaction signals of drug-induced neutropenia (DIN) or drug-induced agranulocytosis (DIA) in children using an electronic health records (EHRs) database. Methods: A two-stage design was presented. First, the suspected drugs to induce DIN or DIA were selected. Second, the associations were evaluated by a retrospective cohort study. Results: Ten and five drugs were potentially identified to be associated with DIN and DIA, respectively. Finally, five (oseltamivir, chlorpheniramine, vancomycin, meropenem, and ganciclovir) and two (chlorpheniramine, and vancomycin) drugs were found to be associated with DIN and DIA, respectively. Of these, the association between oseltamivir and neutropenia (P = 9.83 × 10-9; OR, 2.10; 95% CI, 1.62-2.69) was considered as a new signal for both adults and children. Chlorpheniramine-induced neutropenia (P = 3.01 × 10-8; OR, 1.59; 95% CI, 1.35-1.87) and agranulocytosis (P = 3.16 × 10-7; OR, 3.76; 95% CI, 2.25-6.26) were considered as new signals in children. Other drugs associated with DIN or DIA were confirmed by previous studies. Conclusion: A method to detect signals for DIN and DIA has been described. Several pediatric drugs were found to be associated with DIN or DIA.
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Affiliation(s)
- Ran Wei
- a Clinical Research Center , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Lu-Lu Jia
- a Clinical Research Center , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Yun-Cui Yu
- a Clinical Research Center , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Xiao-Lu Nie
- b Center for Clinical Epidemiology and Evidence-Based Medicine , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Zi-Yang Song
- c Department of Pharmacy , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Duan-Fang Fan
- a Clinical Research Center , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Yue-Feng Xie
- d Information Center , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Xiao-Xia Peng
- b Center for Clinical Epidemiology and Evidence-Based Medicine , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
| | - Zhi-Gang Zhao
- e Department of Pharmacy , Beijing Tiantan Hospital, Capital Medical University , Beijing , China
| | - Xiao-Ling Wang
- a Clinical Research Center , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China.,c Department of Pharmacy , National Center for Children's Health, Beijing Children's Hospital, Capital Medical University , Beijing , China
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Sharma H, Mao C, Zhang Y, Vatani H, Yao L, Zhong Y, Rasmussen L, Jiang G, Pathak J, Luo Y. Developing a portable natural language processing based phenotyping system. BMC Med Inform Decis Mak 2019; 19:78. [PMID: 30943974 PMCID: PMC6448187 DOI: 10.1186/s12911-019-0786-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches. METHODS Our system utilizes UMLS to extract clinically relevant features from the unstructured text and then facilitates portability across different institutions and data systems by incorporating OHDSI's OMOP Common Data Model (CDM) to standardize necessary data elements. Our system can also store the key components of rule-based systems (e.g., regular expression matches) in the format of OMOP CDM, thus enabling the reuse, adaptation and extension of many existing rule-based clinical NLP systems. We experimented with our system on the corpus from i2b2's Obesity Challenge as a pilot study. RESULTS Our system facilitates portable phenotyping of obesity and its 15 comorbidities based on the unstructured patient discharge summaries, while achieving a performance that often ranked among the top 10 of the challenge participants. CONCLUSION Our system of standardization enables a consistent application of numerous rule-based and machine learning based classification techniques downstream across disparate datasets which may originate across different institutions and data systems.
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Affiliation(s)
- Himanshu Sharma
- Cyberinfrastructure, University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Chengsheng Mao
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 USA
| | - Yizhen Zhang
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 USA
| | - Haleh Vatani
- Cyberinfrastructure, University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Liang Yao
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 USA
| | - Yizhen Zhong
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 USA
| | - Luke Rasmussen
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 USA
| | - Guoqian Jiang
- Biomedical Informatics, Mayo Clinic, Rochester, MN USA
| | | | - Yuan Luo
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 USA
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Trifirò G, Gini R, Barone-Adesi F, Beghi E, Cantarutti A, Capuano A, Carnovale C, Clavenna A, Dellagiovanna M, Ferrajolo C, Franchi M, Ingrasciotta Y, Kirchmayer U, Lapi F, Leone R, Leoni O, Lucenteforte E, Moretti U, Mugelli A, Naldi L, Poluzzi E, Rafaniello C, Rea F, Sultana J, Tettamanti M, Traversa G, Vannacci A, Mantovani L, Corrao G. The Role of European Healthcare Databases for Post-Marketing Drug Effectiveness, Safety and Value Evaluation: Where Does Italy Stand? Drug Saf 2019; 42:347-363. [PMID: 30269245 DOI: 10.1007/s40264-018-0732-5] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Enormous progress has been made globally in the use of evidence derived from patients' clinical information as they access their routine medical care. The value of real-world data lies in their complementary nature compared with data from randomised controlled trials: less detailed information on drug efficacy but longer observational periods and larger, more heterogeneous study populations reflecting clinical practice because individuals are included who would not usually be recruited in trials. Real-world data can be collected in various types of electronic sources, such as electronic health records, claims databases and drug or disease registries. These data sources vary in nature from country to country, according to national healthcare system structures and national policies. In Italy, a growing number of healthcare databases have been used to evaluate post-marketing drug utilisation and safety in the last two decades. The aim of this narrative review is to describe the available Italian sources of real-world data and their contribution to generating post-marketing evidence on drug use and safety. We also discuss the strengths and limitations of the most commonly used Italian healthcare databases in addressing various research questions concerning drug utilisation, comparative effectiveness and safety studies, as well as health technology assessment and other areas.
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Affiliation(s)
- Gianluca Trifirò
- Department of Biomedical and Dental Sciences and Morpho-functional Imaging, University of Messina, Messina, Italy.
- Policlinico Universitario G. Martino, Via Consolare Valeria 1, 98125, Messina, Italy.
| | - Rosa Gini
- Agenzia Regionale di Sanità della Toscana, Florence, Italy
| | | | - Ettore Beghi
- Department of Neuroscience, IRCCS-Mario Negri Pharmacology Research Institute, Milan, Italy
| | - Anna Cantarutti
- Laboratory of Pharmacoepidemiology and Healthcare Research, Unit of Biostatistics Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
| | - Annalisa Capuano
- Department of Experimental Medicine, Section of Pharmacology "L. Donatelli", Second University of Naples, Naples, Italy
| | - Carla Carnovale
- Unit of Clinical Pharmacology Department of Biomedical and Clinical Sciences L. Sacco, Luigi Sacco University Hospital, University of Milan, Milan, Italy
| | - Antonio Clavenna
- Pharmacoepidemiology Unit, Department of Public Health, IRCCS, Mario Negri Pharmacology Research Institute, Milan, Italy
| | | | - Carmen Ferrajolo
- Department of Experimental Medicine, Section of Pharmacology "L. Donatelli", Second University of Naples, Naples, Italy
| | - Matteo Franchi
- Laboratory of Pharmacoepidemiology and Healthcare Research, Unit of Biostatistics Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
| | - Ylenia Ingrasciotta
- Department of Biomedical and Dental Sciences and Morpho-functional Imaging, University of Messina, Messina, Italy
| | - Ursula Kirchmayer
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Francesco Lapi
- Health Search, Italian College of General Practitioners and Primary Care, Florence, Italy
| | - Roberto Leone
- Department of Diagnostics and Public Health, Section of Pharmacology, University of Verona, Verona, Italy
| | - Olivia Leoni
- Regional Centre for Pharmacovigilance, Lombardy Region, Milan, Italy
| | - Ersilia Lucenteforte
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Ugo Moretti
- Department of Diagnostics and Public Health, Section of Pharmacology, University of Verona, Verona, Italy
| | - Alessandro Mugelli
- Department of Neurosciences, Psychology, Pharmacology and Child Health (NEUROFARBA), University of Florence, Florence, Italy
| | - Luigi Naldi
- Centro Studi Gruppo Italiano Studi Epidemiologici in Dermatologia (GISED), Bergamo, Italy
| | - Elisabetta Poluzzi
- Department of Medical and Surgical Sciences DIMEC, University of Bologna, Bologna, Italy
| | - Concita Rafaniello
- Department of Experimental Medicine, Section of Pharmacology "L. Donatelli", Second University of Naples, Naples, Italy
| | - Federico Rea
- Laboratory of Pharmacoepidemiology and Healthcare Research, Unit of Biostatistics Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
| | - Janet Sultana
- Department of Biomedical and Dental Sciences and Morpho-functional Imaging, University of Messina, Messina, Italy
| | - Mauro Tettamanti
- Department of Geriatric Neuropsychiatry, Mario Negri Pharmacology Research Institute, Milan, Italy
| | - Giuseppe Traversa
- Pharmacoepidemiology Unit, National Centre for Epidemiology, National Institute of Health, Rome, Italy
| | - Alfredo Vannacci
- Department of Neurosciences, Psychology, Pharmacology and Child Health (NEUROFARBA), University of Florence, Florence, Italy
| | - Lorenzo Mantovani
- Research Centre on Public Health (CESP), University of Milan-Bicocca, Monza, Italy
| | - Giovanni Corrao
- Laboratory of Pharmacoepidemiology and Healthcare Research, Unit of Biostatistics Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
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Zeng Z, Deng Y, Li X, Naumann T, Luo Y. Natural Language Processing for EHR-Based Computational Phenotyping. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019; 16:139-153. [PMID: 29994486 PMCID: PMC6388621 DOI: 10.1109/tcbb.2018.2849968] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping. NLP-based computational phenotyping has numerous applications including diagnosis categorization, novel phenotype discovery, clinical trial screening, pharmacogenomics, drug-drug interaction (DDI), and adverse drug event (ADE) detection, as well as genome-wide and phenome-wide association studies. Significant progress has been made in algorithm development and resource construction for computational phenotyping. Among the surveyed methods, well-designed keyword search and rule-based systems often achieve good performance. However, the construction of keyword and rule lists requires significant manual effort, which is difficult to scale. Supervised machine learning models have been favored because they are capable of acquiring both classification patterns and structures from data. Recently, deep learning and unsupervised learning have received growing attention, with the former favored for its performance and the latter for its ability to find novel phenotypes. Integrating heterogeneous data sources have become increasingly important and have shown promise in improving model performance. Often, better performance is achieved by combining multiple modalities of information. Despite these many advances, challenges and opportunities remain for NLP-based computational phenotyping, including better model interpretability and generalizability, and proper characterization of feature relations in clinical narratives.
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Affiliation(s)
- Zexian Zeng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.
| | - Yu Deng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.
| | - Xiaoyu Li
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA 02115.
| | - Tristan Naumann
- Science and Artificial Intelligence Lab, Massachusetts Institue of Technology, Cambridge, MA 02139.
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.
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Antidepressant-Induced Acute Liver Injury: A Case-Control Study in an Italian Inpatient Population. Drug Saf 2018; 41:95-102. [PMID: 28770534 DOI: 10.1007/s40264-017-0583-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Pre-marketing clinical trials show that antidepressant-induced liver injury seems to be a rare adverse event. Because of short follow-up trial duration, the incidence of liver injury due to antidepressant use could be underestimated. OBJECTIVES We aimed to quantify the risk of acute liver injury associated with antidepressant use through a case-control analysis among an inpatient population. METHODS A multicenter study was carried out in nine Italian hospitals from October 2010 to January 2014, within the DILI-IT (Drug-Induced Liver Injury in Italy) study project. After exclusion of all patients with a clear competing cause of liver injury, cases were defined as adults admitted to the hospital with a diagnosis of acute liver injury, while controls had any other acute clinical condition not related to the liver. Antidepressant exposure was evaluated within 90 days prior to the date of the first sign/symptom of liver injury. Odds ratio (OR) with 95% confidence interval (95% CI) was calculated as a measure of risk estimates for liver injury. RESULTS We included 17 cases exposed to antidepressants matched to 99 controls. According to the features of liver injury, all cases showed symptomatic liver function test abnormalities at hospital admission, with the main signs/symptoms represented by fatigue, nausea, asthenia, or dark urine. Citalopram was the antidepressant mostly involved in the increase of liver enzymes, mainly alanine aminotransferase. Compared with non-use, current use of antidepressants was associated with a significantly increased risk of liver injury (adjusted OR, ORADJ, 1.84; 95% CI 1.02-3.32). Specifically, an increased, but not significant, risk of developing liver injury was observed for citalopram, a selective serotonin-reuptake inhibitor (ORADJ 1.82; 95% CI 0.60-5.53). CONCLUSION The use of antidepressants is not as safe in terms of liver injury as expected; instead, the risk of antidepressant-induced liver injury is likely underestimated. The lack of significance does not reflect the absence of risk, but rather suggests the need to evaluate it in a wider setting of antidepressant users.
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Agreement Among Different Scales for Causality Assessment in Drug-Induced Liver Injury. Clin Drug Investig 2018; 38:211-218. [PMID: 29185238 DOI: 10.1007/s40261-017-0601-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
BACKGROUND AND OBJECTIVE The causality assessment of drug-induced liver injury (DILI) remains a challenge and eagerly awaits the development of reliable hepatotoxicity biomarkers. None of the different available algorithms used for the causality assessment of DILI has been universally accepted as the gold standard. This study was conducted to examine the agreement among different causality assessment scales in reporting DILI. METHODS The World Health Organization-Uppsala Monitoring Center (WHO-UMC), Naranjo, Roussel Uclaf Causality Assessment Method (RUCAM), Maria & Victorino (M & V) and Digestive Disease Week-Japan (DDW-J) assessment scales were used to compare the causalities in all the reported cases of DILI in our adverse drug reaction (ADR) monitoring centre from January 2014 to June 2017. The probability of the causality assessment was classified as 'definite', 'probable', 'possible' and 'unlikely'. The agreement obtained among the causality assessments was analysed using the weighted kappa (κ w) test. RESULTS A total of 33 cases of DILI were included in our analyses. Anti-tubercular therapy (ATT) and methotrexate were the drugs that most commonly caused DILI. The overall agreement among the different scales was poor. The best agreement was found between RUCAM and DDW-J scales (κ w: 0.685). CONCLUSION There were discrepancies among the different causality scales in assessing DILI. This might be due to the different definitions of causality criteria and subjective variability during assessment. A personalised assessment scale incorporating the latest information on specific risk factors and evidence-based criteria for DILI is warranted.
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12
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Ferrajolo C, Verhamme KMC, Trifirò G, 't Jong GW, Picelli G, Giaquinto C, Mazzaglia G, Stricker BH, Rossi F, Capuano A, Sturkenboom MCJM. Antibiotic-Induced Liver Injury in Paediatric Outpatients: A Case-Control Study in Primary Care Databases. Drug Saf 2017; 40:305-315. [PMID: 28025733 PMCID: PMC5362651 DOI: 10.1007/s40264-016-0493-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Introduction Antibiotics are the most commonly prescribed drug class in children. Real-world data mining on the paediatric population showed potential associations between antibiotic use and acute liver injury. Objective We assessed risk estimates of liver injury associated with antibiotic use in children and adolescent outpatients. Methods A large, multi-database, population-based, case-control study was performed in people <18 years of age from two European countries (Italy and The Netherlands) during the period 2000–2008. All potential cases of liver injury were automatically extracted from three databases and then manually validated based on Council for International Organizations of Medical Sciences (CIOMS) criteria and by exclusion of all competing causes for liver injury. Up to 100 control participants were sampled for each case and were matched on index date of the event, age, sex and database. Based on prescription data, antibiotic exposure was categorized as current, recent or past use by calculating the time period between the end of prescription and the index date. Multivariate conditional logistic regression analyses were applied to calculate odds ratios (ORs) as a measure of the association (with 95% confidence interval [CI]). Results We identified 938 cases of liver injury and matched to 93,665 controls. Current use of overall antibiotics is associated with a threefold increased risk of liver injury compared with past use (adjusted OR [ORadj] 3.22, 95% CI 2.57–4.03). With regard to individual antibiotics, the risk is significantly increased for current use of each antibiotic (p < 0.005), except for azithromycin. Risk estimates vary from the lowest ORadj of 1.86 (95% CI 1.08–3.21) for amoxicillin to the highest ORadj of 24.16 (95% CI 11.78–49.54) for cotrimoxazole (i.e. sulphamethoxazole/trimethoprim) and 26.70 (95% CI 12.09–58.96) for ceftriaxone. Sensitivity analyses confirm the associations for ceftriaxone, cotrimoxazole, and clarithromycin. Conclusion Antibiotic-induced liver injury in children is heterogeneous across the use of individual antibiotics. When prescribing ceftriaxone, cotrimoxazole and clarithromycin in children, paediatricians should definitely be aware of their potential risk of liver injury, even if for short periods. Electronic supplementary material The online version of this article (doi:10.1007/s40264-016-0493-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Carmen Ferrajolo
- Department of Experimental Medicine, Pharmacology Section, Campania Regional Centre of Pharmacovigilance and Pharmacoepidemiology, University of Campania, Via Santa Maria di Costantinopoli, 16, 80138, Naples, Italy.
- Department of Medical Informatics, Erasmus University Medical Centre, Dr. Molewaterplein 50, 3015 GE, Rotterdam, The Netherlands.
| | - Katia M C Verhamme
- Department of Medical Informatics, Erasmus University Medical Centre, Dr. Molewaterplein 50, 3015 GE, Rotterdam, The Netherlands
| | - Gianluca Trifirò
- Department of Medical Informatics, Erasmus University Medical Centre, Dr. Molewaterplein 50, 3015 GE, Rotterdam, The Netherlands
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Geert W 't Jong
- Department of Medical Informatics, Erasmus University Medical Centre, Dr. Molewaterplein 50, 3015 GE, Rotterdam, The Netherlands
- Department of Paediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada
| | - Gino Picelli
- Pedianet-Società Servizi Telematici SRL, Padua, Italy
| | - Carlo Giaquinto
- Pedianet-Società Servizi Telematici SRL, Padua, Italy
- Department of Paediatrics, University of Padua, Padua, Italy
| | - Giampiero Mazzaglia
- Health Search-IMS HEALTH LPD (Longitudinal Patient Database), Italian College of General Practitioners, Florence, Italy
| | - Bruno H Stricker
- Department of Epidemiology and Biostatistics, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Francesco Rossi
- Department of Experimental Medicine, Pharmacology Section, Campania Regional Centre of Pharmacovigilance and Pharmacoepidemiology, University of Campania, Via Santa Maria di Costantinopoli, 16, 80138, Naples, Italy
| | - Annalisa Capuano
- Department of Experimental Medicine, Pharmacology Section, Campania Regional Centre of Pharmacovigilance and Pharmacoepidemiology, University of Campania, Via Santa Maria di Costantinopoli, 16, 80138, Naples, Italy
| | - Miriam C J M Sturkenboom
- Department of Medical Informatics, Erasmus University Medical Centre, Dr. Molewaterplein 50, 3015 GE, Rotterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Erasmus University Medical Centre, Rotterdam, The Netherlands
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Shi Q, Yang X, Greenhaw JJ, Salminen AT, Russotti GM, Salminen WF. Drug-Induced Liver Injury in Children: Clinical Observations, Animal Models, and Regulatory Status. Int J Toxicol 2017; 36:365-379. [PMID: 28820004 DOI: 10.1177/1091581817721675] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Drug-induced liver injury in children (cDILI) accounts for about 1% of all reported adverse drug reactions throughout all age groups, less than 10% of all clinical DILI cases, and around 20% of all acute liver failure cases in children. The overall DILI susceptibility in children has been assumed to be lower than in adults. Nevertheless, controversial evidence is emerging about children's sensitivity to DILI, with children's relative susceptibility to DILI appearing to be highly drug-specific. The culprit drugs in cDILI are similar but not identical to DILI in adults (aDILI). This is demonstrated by recent findings that a drug frequently associated with aDILI (amoxicillin/clavulanate) was rarely associated with cDILI and that the drug basiliximab caused only cDILI but not aDILI. The fatality in reported cDILI studies ranged from 4% to 31%. According to the US Food and Drug Administration-approved drugs labels, valproic acid, dactinomycin, and ampicillin appear more likely to cause cDILI. In contrast, deferasirox, isoniazid, dantrolene, and levofloxacin appear more likely to cause aDILI. Animal models have been explored to mimic children's increased susceptibility to valproic acid hepatotoxicity or decreased susceptibility to acetaminophen or halothane hepatotoxicity. However, for most drugs, animal models are not readily available, and the underlying mechanisms for the differential reactions to DILI between children and adults remain highly hypothetical. Diagnosis tools for cDILI are not yet available. A critical need exists to fill the knowledge gaps in cDILI. This review article provides an overview of cDILI and specific drugs associated with cDILI.
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Affiliation(s)
- Qiang Shi
- 1 Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA
| | - Xi Yang
- 1 Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA
| | - James J Greenhaw
- 1 Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA
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15
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Brauer R, Douglas I, Garcia Rodriguez LA, Downey G, Huerta C, de Abajo F, Bate A, Feudjo Tepie M, de Groot MCH, Schlienger R, Reynolds R, Smeeth L, Klungel O, Ruigómez A. Risk of acute liver injury associated with use of antibiotics. Comparative cohort and nested case-control studies using two primary care databases in Europe. Pharmacoepidemiol Drug Saf 2017; 25 Suppl 1:29-38. [PMID: 27038354 DOI: 10.1002/pds.3861] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Revised: 07/10/2015] [Accepted: 07/24/2015] [Indexed: 11/10/2022]
Abstract
PURPOSE To assess the impact of varying study designs, exposure and outcome definitions on the risk of acute liver injury (ALI) associated with antibiotic use. METHODS The source population comprised of patients registered in two primary care databases, in the UK and in Spain. We identified a cohort consisting of new users of antibiotics during the study period (2004-2009) and non-users during the study period or in the previous year. Cases with ALI were identified within this cohort and classified as definite or probable, based on recorded medical information. The relative risk (RR) of ALI associated with antibiotic use was computed using Poisson regression. For the nested case-control analyses, up to five controls were matched to each case by age, sex, date and practice (in CPRD) and odds ratios (OR) were computed with conditional logistic regression. RESULTS The age, sex and year adjusted RRs of definite ALI in the current antibiotic use periods was 10.04 (95% CI: 6.97-14.47) in CPRD and 5.76 (95% CI: 3.46-9.59) in BIFAP. In the case-control analyses adjusting for life-style, comorbidities and use of medications, the OR of ALI for current users of antibiotics was and 5.7 (95% CI: 3.46-9.36) in CPRD and 2.6 (95% CI: 1.26-5.37) in BIFAP. CONCLUSION Guided by a common protocol, both cohort and case-control study designs found an increased risk of ALI associated with the use of antibiotics in both databases, independent of the exposure and case definitions used. However, the magnitude of the risk was higher in CPRD compared to BIFAP.
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Affiliation(s)
- Ruth Brauer
- London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.,Amgen Limited, London, UK
| | - Ian Douglas
- London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK
| | | | | | - Consuelo Huerta
- Agencia Española de Medicamentos y Productos Sanitarios (AEMPS), Medicines for Human Use Department, Division of Pharmacoepidemiology and Pharmacovigilance, Madrid, Spain
| | - Francisco de Abajo
- Clinical Pharmacology Unit, University Hospital Príncipe de Asturias, Department of Biomedical Sciences, University of Alcala, Alcalá de Henares, Spain
| | | | | | - Mark C H de Groot
- Utrecht University, Faculty of Science, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht, The Netherlands
| | | | - Robert Reynolds
- Epidemiology, Pfizer Research and Development, New York, NY, USA
| | - Liam Smeeth
- London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK
| | - Olaf Klungel
- Utrecht University, Faculty of Science, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht, The Netherlands
| | - Ana Ruigómez
- Fundación Centro Español de Investigación Farmacoepidemiológica (CEIFE), Madrid, Spain
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Ferrer P, Amelio J, Ballarín E, Sabaté M, Vidal X, Rottenkolber M, Schmiedl S, Laporte JR, Ibáñez L. Systematic Review and Meta-Analysis: Macrolides- and Amoxicillin/Clavulanate-induced Acute Liver Injury. Basic Clin Pharmacol Toxicol 2016; 119:3-9. [PMID: 26707367 DOI: 10.1111/bcpt.12550] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2015] [Accepted: 12/12/2015] [Indexed: 12/12/2022]
Abstract
Antibacterials are frequently associated with idiosyncratic drug-induced liver injury (DILI). The objective of this study was to estimate the risk of macrolides and amoxicillin/clavulanate (AMC) on DILI. We conducted a systematic review (SR) and meta-analysis (MA) with studies retrieved from PubMed, Cochrane Library Plus, Web of Knowledge, clinicaltrials.gov, Livertox and Toxline (1980-2014). We searched for macrolides, AMC and MeSH and synonym terms for DILI. We included all study designs except case reports/series, all population ages and studies with a placebo/non-user comparator. We summarized the evidence with a random-effects MA. Quality of the studies was appraised with a checklist developed for SR of adverse effects. Heterogeneity and publication bias were assessed with different exploratory tools. We finally included 10 (two randomized clinical trials, six case-control, one cohort and one case-population studies) and 9 (case-population excluded) articles in the SR and MA, respectively. The overall summary relative risk of DILI for macrolides was 2.85 [95% confidence interval (CI) 1.81-4.47], p < 0.0001, I(2) = 57%. Three studies were perceived to be missing in the area of low statistical significance. Year of study and selected exposure window partly explained the variability between studies. For AMC, the risk of DILI was 9.38 (95% CI 0.65-135.41) p = 0.3, I2 = 95%. In conclusion, although spontaneous reports and case series have long established an association between macrolides and AMC with acute liver injury, these SR and MA have assessed the magnitude of this association. The low incidence of DILI and the therapeutic place of these antibiotics might tilt the balance in favour of their benefits.
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Affiliation(s)
- Pili Ferrer
- Foundation Catalan Institute of Pharmacology, Barcelona, Spain
| | | | - Elena Ballarín
- Foundation Catalan Institute of Pharmacology, Barcelona, Spain.,Department of Clinical Pharmacology, University Hospital Vall d'Hebron, Barcelona, Spain.,Department of Pharmacology, Toxicology and Therapeutics, Autonomous University of Barcelona, Barcelona, Spain
| | - Mònica Sabaté
- Foundation Catalan Institute of Pharmacology, Barcelona, Spain.,Department of Clinical Pharmacology, University Hospital Vall d'Hebron, Barcelona, Spain.,Department of Pharmacology, Toxicology and Therapeutics, Autonomous University of Barcelona, Barcelona, Spain
| | - Xavi Vidal
- Foundation Catalan Institute of Pharmacology, Barcelona, Spain.,Department of Clinical Pharmacology, University Hospital Vall d'Hebron, Barcelona, Spain.,Department of Pharmacology, Toxicology and Therapeutics, Autonomous University of Barcelona, Barcelona, Spain
| | - Marietta Rottenkolber
- Institute for Medical Information Sciences, Biometry and Epidemiology, Ludwig-Maximilians Universitaet-Muenchen, Munich, Germany
| | - Sven Schmiedl
- Philipp Klee-Institute for Clinical Pharmacology, Helios Klinik Wuppertal, Wuppertal, Germany.,Department of Clinical Pharmacology, School of Medicine, Faculty of Health, Witten-Herdecke University, Witten, Germany
| | - Joan-Ramon Laporte
- Foundation Catalan Institute of Pharmacology, Barcelona, Spain.,Department of Clinical Pharmacology, University Hospital Vall d'Hebron, Barcelona, Spain.,Department of Pharmacology, Toxicology and Therapeutics, Autonomous University of Barcelona, Barcelona, Spain
| | - Luisa Ibáñez
- Foundation Catalan Institute of Pharmacology, Barcelona, Spain.,Department of Clinical Pharmacology, University Hospital Vall d'Hebron, Barcelona, Spain.,Department of Pharmacology, Toxicology and Therapeutics, Autonomous University of Barcelona, Barcelona, Spain
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17
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Brauer R, Ruigómez A, Klungel O, Reynolds R, Feudjo Tepie M, Smeeth L, Douglas I. The risk of acute liver injury among users of antibiotic medications: a comparison of case-only studies. Pharmacoepidemiol Drug Saf 2015; 25 Suppl 1:39-46. [PMID: 26248609 PMCID: PMC4916501 DOI: 10.1002/pds.3846] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Revised: 07/06/2015] [Accepted: 07/07/2015] [Indexed: 11/12/2022]
Abstract
PURPOSE The aims of this study were two-fold: (i) to investigate the effect of exposure to antibiotic agents on the risk of acute liver injury using a self-controlled case series and case-crossover study and (ii) to compare the results between the case-only studies. METHODS For the self-controlled case series study relative incidence ratios (IRR) were calculated by dividing the rate of acute liver injury experienced during patients' periods of exposure to antibiotics to patients' rate of events during non-exposed time using conditional Poisson regression. For the case-crossover analysis we calculated Odds Ratios (OR) using conditional logistic regression by comparing exposure during 14- and 30-day risk windows with exposure during control moments. RESULTS Using the self-controlled case series approach, the IRR was highest during the first 7 days after receipt of a prescription (10.01, 95% CI 6.59-15.18). Omitting post-exposure washout periods lowered the IRR to 7.2. The highest estimate in the case-crossover analysis was found when two 30-day control periods 1 year prior to the 30-day ALI risk period were retained in the analysis: OR = 6.5 (95% CI, 3.95-10.71). The lowest estimate was found when exposure in the 14-day risk period was compared to exposure in four consecutive 14-day control periods immediately prior to the risk period (OR = 3.05, 95% CI, 2.06-4.53). CONCLUSION An increased relative risk of acute liver injury was consistently observed using both self-controlled case series and case-crossover designs. Case-only designs can be used as a viable alternative study design to study the risk of acute liver injury, albeit with some limitations.
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Affiliation(s)
- Ruth Brauer
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Ana Ruigómez
- Fundación Centro Español de Investigación Farmacoepidemiológica, (CEIFE), Madrid, Spain
| | - Olaf Klungel
- Faculty of Science, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, The Netherlands
| | - Robert Reynolds
- Epidemiology, Pfizer Research and Development, New York, USA
| | | | - Liam Smeeth
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Ian Douglas
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
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Raschi E, De Ponti F. Drug- and herb-induced liver injury: Progress, current challenges and emerging signals of post-marketing risk. World J Hepatol 2015; 7:1761-1771. [PMID: 26167249 PMCID: PMC4491905 DOI: 10.4254/wjh.v7.i13.1761] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Revised: 05/21/2015] [Accepted: 06/18/2015] [Indexed: 02/06/2023] Open
Abstract
Drug-induced liver injury (DILI) and herb-induced liver injury is a hot topic for clinicians, academia, drug companies and regulators, as shown by the steadily increasing number of publications in the past 15 years. This review will first provide clues for clinicians to suspect idiosyncratic (unpredictable) DILI and succeed in diagnosis. Causality assessment remains challenging and requires careful medical history as well as awareness of multifaceted aspects, especially for herbs. Drug discontinuation and therapy reconciliation remain the mainstay in patent's management to minimize occurrence of acute liver failure. The second section will address novel agents associated with liver injury in 2014 (referred to as "signals"), especially in terms of clinical, research and drug development implications. Insights will be provided into recent trends by highlighting the contribution of different post-marketing data, especially registries and spontaneous reporting systems. This literature scrutiny suggests: (1) the importance of post-marketing databases as tools of clinical evidence to detect signals of DILI risk; and (2) the need for joining efforts in improving predictivity of pre-clinical assays, continuing post-marketing surveillance and design ad hoc post-authorization safety studies. In this context, ongoing European/United States research consortia and novel pharmaco-epidemiological tools (e.g., specialist prescription event monitoring) will support innovation in this field. Direct oral anticoagulants and herbal/dietary supplements appear as key research priorities.
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Affiliation(s)
- Emanuel Raschi
- Emanuel Raschi, Fabrizio De Ponti, Pharmacology Unit, Department of Medical and Surgical Sciences, Alma Mater Studiorum, University of Bologna, I-40126 Bologna, Italy
| | - Fabrizio De Ponti
- Emanuel Raschi, Fabrizio De Ponti, Pharmacology Unit, Department of Medical and Surgical Sciences, Alma Mater Studiorum, University of Bologna, I-40126 Bologna, Italy
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Allegaert K, van den Anker JN. Adverse drug reactions in neonates and infants: a population-tailored approach is needed. Br J Clin Pharmacol 2015; 80:788-95. [PMID: 24862557 DOI: 10.1111/bcp.12430] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2014] [Accepted: 05/21/2014] [Indexed: 12/13/2022] Open
Abstract
Drug therapy is a powerful tool to improve outcome, but there is an urgent need to improve pharmacotherapy in neonates through tailored prevention and management of adverse drug reactions (ADRs). At present, infants commonly receive off-label drugs, at dosages extrapolated from those in children or adults. Besides the lack of labelling, inappropriate formulations, (poly)pharmacy, immature organ function and multiple illnesses further raise the risk for ADRs in neonates and infants. Pharmacovigilance to improve the prevention and management of ADRs needs to be tailored to neonates and infants. We illustrate this using prevention strategies for drug prescription and administration errors (e.g. formulation, bedside manipulation, access), detection through laboratory signalling or clinical outlier data (e.g. reference laboratory values, overall high morbidity), assessment through algorithm scoring (e.g. Naranjo or population specific), as well as understanding of the developmental toxicology (e.g. covariates, developmental pharmacology) to avoid re-occurrence and for development of guidelines. Such tailored strategies need collaborative initiatives to combine the knowledge and expertise of different disciplines, but hold promise to become a very effective tool to improve pharmacotherapy and reduce ADRs in infants.
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Affiliation(s)
- Karel Allegaert
- Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium.,Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Johannes N van den Anker
- Division of Pediatric Clinical Pharmacology, Children's National Medical Center, Washington, DC, USA.,Departments of Pediatrics, Pharmacology and Physiology, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.,Intensive Care, Erasmus MC, Sophia Children's Hospital, Rotterdam, The Netherlands.,Department of Paediatric Pharmacology, University Children's Hospital, Basel, Switzerland
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Osokogu OU, Fregonese F, Ferrajolo C, Verhamme K, de Bie S, 't Jong G, Catapano M, Weibel D, Kaguelidou F, Bramer WM, Hsia Y, Wong ICK, Gazarian M, Bonhoeffer J, Sturkenboom M. Pediatric drug safety signal detection: a new drug-event reference set for performance testing of data-mining methods and systems. Drug Saf 2015; 38:207-17. [PMID: 25663078 PMCID: PMC4328124 DOI: 10.1007/s40264-015-0265-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
BACKGROUND Better evidence regarding drug safety in the pediatric population might be generated from existing data sources such as spontaneous reporting systems and electronic healthcare records. The Global Research in Paediatrics (GRiP)-Network of Excellence aims to develop pediatric-specific methods that can be applied to these data sources. A reference set of positive and negative drug-event associations is required. OBJECTIVE The aim of this study was to develop a pediatric-specific reference set of positive and negative drug-event associations. METHODS Considering user patterns and expert opinion, 16 drugs that are used in individuals aged 0-18 years were selected and evaluated against 16 events, regarded as important safety outcomes. A cross-table of unique drug-event pairs was created. Each pair was classified as potential positive or negative control based on information from the drug's Summary of Product Characteristics and Micromedex. If both information sources consistently listed the event as an adverse event, the combination was reviewed as potential positive control. If both did not, the combination was evaluated as potential negative control. Further evaluation was based on published literature. RESULTS Selected drugs include ibuprofen, flucloxacillin, domperidone, methylphenidate, montelukast, quinine, and cyproterone/ethinylestradiol. Selected events include bullous eruption, aplastic anemia, ventricular arrhythmia, sudden death, acute kidney injury, psychosis, and seizure. Altogether, 256 unique combinations were reviewed, yielding 37 positive (17 with evidence from the pediatric population and 20 with evidence from adults only) and 90 negative control pairs, with the remainder being unclassifiable. CONCLUSION We propose a drug-event reference set that can be used to compare different signal detection methods in the pediatric population.
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Affiliation(s)
- Osemeke U Osokogu
- Department of Medical Informatics, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands,
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Ferrajolo C, Capuano A, Trifirò G, Moretti U, Rossi F, Santuccio C. Pediatric drug safety surveillance in Italian pharmacovigilance network: an overview of adverse drug reactions in the years 2001 – 2012. Expert Opin Drug Saf 2014; 13 Suppl 1:S9-20. [DOI: 10.1517/14740338.2014.939581] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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