TY  - JOUR
AU  - Gauffin, Oskar
AU  - Brand, Judith S.
AU  - Vidlin, Sara Hedfors
AU  - Sartori, Daniele
AU  - Asikainen, Suvi
AU  - Catala, Martí
AU  - Chalabi, Etir
AU  - Dedman, Daniel
AU  - Danilović, Ana
AU  - Duarte-Salles, Talita
AU  - García Morales, Maria Teresa
AU  - Hiltunen, Saara
AU  - Jödicke, Annika M.
AU  - Lazarević, Milan
AU  - Mayer, Miguel A.
AU  - Miladinović, Jelena
AU  - Mitchell, Joseph
AU  - Pistillo, Andrea
AU  - Ramírez-Anguita, Juan Manuel
AU  - Reyes, Carlen
AU  - Rudolph, Annette
AU  - Sandberg, Lovisa
AU  - Savage, Ruth
AU  - Schuemie, Martijn
AU  - Spasić, Dimitrije
AU  - Trinh, Nhung T. H.
AU  - Veljković, Nevena V.
AU  - Vujovic, Ankica
AU  - de Wilde, Marcel
AU  - Zekarias, Alem
AU  - Rijnbeek, Peter
AU  - Ryan, Patrick
AU  - Prieto-Alhambra, Daniel
AU  - Noren, G. Niklas
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11727
AB  - Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research.
T2  - Drug Safety
T1  - Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study
DO  - 10.1007/s40264-023-01353-w
ER  - 

@article{
author = "Gauffin, Oskar and Brand, Judith S. and Vidlin, Sara Hedfors and Sartori, Daniele and Asikainen, Suvi and Catala, Martí and Chalabi, Etir and Dedman, Daniel and Danilović, Ana and Duarte-Salles, Talita and García Morales, Maria Teresa and Hiltunen, Saara and Jödicke, Annika M. and Lazarević, Milan and Mayer, Miguel A. and Miladinović, Jelena and Mitchell, Joseph and Pistillo, Andrea and Ramírez-Anguita, Juan Manuel and Reyes, Carlen and Rudolph, Annette and Sandberg, Lovisa and Savage, Ruth and Schuemie, Martijn and Spasić, Dimitrije and Trinh, Nhung T. H. and Veljković, Nevena V. and Vujovic, Ankica and de Wilde, Marcel and Zekarias, Alem and Rijnbeek, Peter and Ryan, Patrick and Prieto-Alhambra, Daniel and Noren, G. Niklas",
year = "2023",
abstract = "Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research.",
journal = "Drug Safety",
title = "Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study",
doi = "10.1007/s40264-023-01353-w"
}

Gauffin, O., Brand, J. S., Vidlin, S. H., Sartori, D., Asikainen, S., Catala, M., Chalabi, E., Dedman, D., Danilović, A., Duarte-Salles, T., García Morales, M. T., Hiltunen, S., Jödicke, A. M., Lazarević, M., Mayer, M. A., Miladinović, J., Mitchell, J., Pistillo, A., Ramírez-Anguita, J. M., Reyes, C., Rudolph, A., Sandberg, L., Savage, R., Schuemie, M., Spasić, D., Trinh, N. T. H., Veljković, N. V., Vujovic, A., de Wilde, M., Zekarias, A., Rijnbeek, P., Ryan, P., Prieto-Alhambra, D.,& Noren, G. N.. (2023). Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study. in Drug Safety.
https://doi.org/10.1007/s40264-023-01353-w

Gauffin O, Brand JS, Vidlin SH, Sartori D, Asikainen S, Catala M, Chalabi E, Dedman D, Danilović A, Duarte-Salles T, García Morales MT, Hiltunen S, Jödicke AM, Lazarević M, Mayer MA, Miladinović J, Mitchell J, Pistillo A, Ramírez-Anguita JM, Reyes C, Rudolph A, Sandberg L, Savage R, Schuemie M, Spasić D, Trinh NTH, Veljković NV, Vujovic A, de Wilde M, Zekarias A, Rijnbeek P, Ryan P, Prieto-Alhambra D, Noren GN. Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study. in Drug Safety. 2023;.
doi:10.1007/s40264-023-01353-w .

Gauffin, Oskar, Brand, Judith S., Vidlin, Sara Hedfors, Sartori, Daniele, Asikainen, Suvi, Catala, Martí, Chalabi, Etir, Dedman, Daniel, Danilović, Ana, Duarte-Salles, Talita, García Morales, Maria Teresa, Hiltunen, Saara, Jödicke, Annika M., Lazarević, Milan, Mayer, Miguel A., Miladinović, Jelena, Mitchell, Joseph, Pistillo, Andrea, Ramírez-Anguita, Juan Manuel, Reyes, Carlen, Rudolph, Annette, Sandberg, Lovisa, Savage, Ruth, Schuemie, Martijn, Spasić, Dimitrije, Trinh, Nhung T. H., Veljković, Nevena V., Vujovic, Ankica, de Wilde, Marcel, Zekarias, Alem, Rijnbeek, Peter, Ryan, Patrick, Prieto-Alhambra, Daniel, Noren, G. Niklas, "Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study" in Drug Safety (2023),
https://doi.org/10.1007/s40264-023-01353-w . .