5 results on '"Bauchau, Vincent"'
Search Results
2. Application of Probabilistic Multiple-Bias Analyses to a Cohort- and a Case-Control Study on the Association between Pandemrix™and Narcolepsy
- Author
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Bollaerts, Kaatje, primary, Shinde, Vivek, additional, Dos Santos, Gaël, additional, Ferreira, Germano, additional, Bauchau, Vincent, additional, Cohet, Catherine, additional, and Verstraeten, Thomas, additional
- Published
- 2016
- Full Text
- View/download PDF
3. Application of Probabilistic Multiple-Bias Analyses to a Cohort- and a Case-Control Study on the Association between Pandemrix™and Narcolepsy.
- Author
-
Bollaerts, Kaatje, Shinde, Vivek, Dos Santos, Gaël, Ferreira, Germano, Bauchau, Vincent, Cohet, Catherine, and Verstraeten, Thomas
- Subjects
NARCOLEPSY ,H1N1 influenza ,EVIDENCE-based medicine ,PUBLIC health ,VACCINATION ,THERAPEUTICS - Abstract
Background: An increase in narcolepsy cases was observed in Finland and Sweden towards the end of the 2009 H1N1 influenza pandemic. Preliminary observational studies suggested a temporal link with the pandemic influenza vaccine Pandemrix™, leading to a number of additional studies across Europe. Given the public health urgency, these studies used readily available retrospective data from various sources. The potential for bias in such settings was generally acknowledged. Although generally advocated by key opinion leaders and international health authorities, no systematic quantitative assessment of the potential joint impact of biases was undertaken in any of these studies. Methods: We applied bias-level multiple-bias analyses to two of the published narcolepsy studies: a pediatric cohort study from Finland and a case-control study from France. In particular, we developed Monte Carlo simulation models to evaluate a potential cascade of biases, including confounding by age, by indication and by natural H1N1 infection, selection bias, disease- and exposure misclassification. All bias parameters were evidence-based to the extent possible. Results: Given the assumptions used for confounding, selection bias and misclassification, the Finnish rate ratio of 13.78 (95% CI: 5.72–28.11) reduced to a median value of 6.06 (2.5
th - 97.5th percentile: 2.49–15.1) and the French odds ratio of 5.43 (95% CI: 2.6–10.08) to 1.85 (2.5th —97.5th percentile: 0.85–4.08). Conclusion: We illustrate multiple-bias analyses using two studies on the Pandemrix™ -narcolepsy association and advocate their use to better understand the robustness of study findings. Based on our multiple-bias models, the observed Pandemrix™ -narcolepsy association consistently persists in the Finnish study. For the French study, the results of our multiple-bias models were inconclusive. [ABSTRACT FROM AUTHOR]- Published
- 2016
- Full Text
- View/download PDF
4. Estimation of vaccination coverage from electronic healthcare records; methods performance evaluation – A contribution of the ADVANCE-project
- Author
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Ana Llorente García, Miriam C. J. M. Sturkenboom, Consuelo Huerta, Toon Braeye, Elisa Martin Merino, Kaatje Bollaerts, Hanne-Dorthe Emborg, Vincent Bauchau, Garcia, Ana Llorente, Emborg, Hanne-Dorthe, BRAEYE, Toon, Huerta, Consuelo, Merino, Elisa Martin, BOLLAERTS, Kaatje, Sturkenboon, Miriam, and Bauchau, Vincent
- Subjects
Vaccination Coverage ,Computer science ,Pathology and Laboratory Medicine ,Biochemistry ,01 natural sciences ,Geographical Locations ,010104 statistics & probability ,Database and Informatics Methods ,0302 clinical medicine ,Statistics ,Health care ,Medicine and Health Sciences ,Electronic Health Records ,Public and Occupational Health ,030212 general & internal medicine ,Papillomaviridae ,Mammals ,Pertussis Vaccine ,Vaccines ,Multidisciplinary ,Agricultural and Biological Sciences(all) ,Simulation and Modeling ,Vaccination ,Eukaryota ,Vaccination and Immunization ,3. Good health ,Europe ,Infectious Diseases ,Medical Microbiology ,Vaccination coverage ,Viral Pathogens ,Vertebrates ,Physical Sciences ,Viruses ,Apes ,Medicine ,Pathogens ,Research Article ,Primates ,Infectious Disease Control ,Papillomaviruses ,Science ,Immunology ,Research and Analysis Methods ,Microbiology ,Risk Assessment ,03 medical and health sciences ,Journal Article ,Animals ,Humans ,0101 mathematics ,Microbial Pathogens ,business.industry ,Biochemistry, Genetics and Molecular Biology(all) ,Organisms ,Biology and Life Sciences ,Human Papillomavirus ,Probability Theory ,Probability Distribution ,Amniotes ,People and Places ,Preventive Medicine ,business ,DNA viruses ,Mathematics ,Genetics and Molecular Biology(all) - Abstract
Introduction The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public private collaboration aiming to develop and test a system for rapid benefit-risk (B/ R) monitoring of vaccines, using existing electronic healthcare record (eHR) databases in Europe. Part of the data in such sources is missing due to incomplete follow-up hampering the accurate estimation of vaccination coverage. We compared different methods for coverage estimation from eHR databases; naïve period prevalence, complete case period prevalence, period prevalence adjusted for follow-up time, Kaplan-Meier (KM) analysis and (adjusted) inverse probability weighing (IPW). Methods We created simulation scenarios with different proportions of completeness of follow-up. Both completeness independent and dependent from vaccination date and status were considered. The root mean squared error (RMSE) and relative difference between the estimated and true coverage were used to assess the performance of the different methods for each of the scenarios. We included data examples on the vaccination coverage of human papilloma virus and pertussis component containing vaccines from the Spanish BIFAP databaseResults Under completeness independent from vaccination date or status, several methods provided estimates with bias close to zero. However, when dependence between completeness of follow-up and vaccination date or status was present, all methods generated biased estimates. The IPW/CDF methods were generally the least biased. Preference for a specific method should be based on the type of censoring and type of dependence between completeness of follow-up and vaccination. Additional insights into these aspects, might be gained by applying several methods. The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under ADVANCE grant agreement no. 115557, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. Co-author V.B received a salary from GSK during the period in which this study was performed. The study sponsors had no role in study design, in the collection, analysis and interpretation of data, in the writing of the report, or in the decision to submit the report for publication. The specific roles of these authors are articulated in the ‘author contributions’ section
- Published
- 2019
5. Application of Probabilistic Multiple-Bias Analyses to a Cohort- and a Case-Control Study on the Association between Pandemrix™ and Narcolepsy.
- Author
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Bollaerts K, Shinde V, Dos Santos G, Ferreira G, Bauchau V, Cohet C, and Verstraeten T
- Subjects
- Adolescent, Adult, Case-Control Studies, Child, Child, Preschool, Female, Finland epidemiology, France epidemiology, Humans, Influenza Vaccines administration & dosage, Influenza, Human epidemiology, Male, Narcolepsy chemically induced, Sweden epidemiology, Influenza A Virus, H1N1 Subtype, Influenza Vaccines adverse effects, Influenza, Human prevention & control, Narcolepsy epidemiology, Pandemics
- Abstract
Background: An increase in narcolepsy cases was observed in Finland and Sweden towards the end of the 2009 H1N1 influenza pandemic. Preliminary observational studies suggested a temporal link with the pandemic influenza vaccine Pandemrix™, leading to a number of additional studies across Europe. Given the public health urgency, these studies used readily available retrospective data from various sources. The potential for bias in such settings was generally acknowledged. Although generally advocated by key opinion leaders and international health authorities, no systematic quantitative assessment of the potential joint impact of biases was undertaken in any of these studies., Methods: We applied bias-level multiple-bias analyses to two of the published narcolepsy studies: a pediatric cohort study from Finland and a case-control study from France. In particular, we developed Monte Carlo simulation models to evaluate a potential cascade of biases, including confounding by age, by indication and by natural H1N1 infection, selection bias, disease- and exposure misclassification. All bias parameters were evidence-based to the extent possible., Results: Given the assumptions used for confounding, selection bias and misclassification, the Finnish rate ratio of 13.78 (95% CI: 5.72-28.11) reduced to a median value of 6.06 (2.5th- 97.5th percentile: 2.49-15.1) and the French odds ratio of 5.43 (95% CI: 2.6-10.08) to 1.85 (2.5th-97.5th percentile: 0.85-4.08)., Conclusion: We illustrate multiple-bias analyses using two studies on the Pandemrix™-narcolepsy association and advocate their use to better understand the robustness of study findings. Based on our multiple-bias models, the observed Pandemrix™-narcolepsy association consistently persists in the Finnish study. For the French study, the results of our multiple-bias models were inconclusive.
- Published
- 2016
- Full Text
- View/download PDF
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