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Kennedy-Shaffer L. Quasi-experimental methods for pharmacoepidemiology: difference-in-differences and synthetic control methods with case studies for vaccine evaluation. Am J Epidemiol 2024; 193:1050-1058. [PMID: 38456774 PMCID: PMC11228849 DOI: 10.1093/aje/kwae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 02/13/2024] [Accepted: 03/06/2024] [Indexed: 03/09/2024] Open
Abstract
Difference-in-differences and synthetic control methods have become common study designs for evaluating the effects of changes in policies, including health policies. They also have potential for providing real-world effectiveness and safety evidence in pharmacoepidemiology. To effectively add to the toolkit of the field, however, designs-including both their benefits and drawbacks-must be well understood. Quasi-experimental designs provide an opportunity to estimate the average treatment effect on the treated without requiring the measurement of all possible confounding factors, and to assess population-level effects. This requires, however, other key assumptions, including the parallel trends or stable weighting assumptions, a lack of other concurrent events that could alter time trends, and an absence of contamination between exposed and unexposed units. The targeted estimands are also highly specific to the settings of the study, and combining across units or time periods can be challenging. Case studies are presented for 3 vaccine evaluation studies, showcasing some of these challenges and opportunities in a specific field of pharmacoepidemiology. These methods provide feasible and valuable sources of evidence in various pharmacoepidemiologic settings and can be improved through research to identify and weigh the advantages and disadvantages in those settings. This article is part of a Special Collection on Pharmacoepidemiology.
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Affiliation(s)
- Lee Kennedy-Shaffer
- Department of Mathematics and Statistics, Vassar College, Poughkeepsie, NY 12604, United States
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Sotheran E, Lane CR, Horan K, Stevens K, Guglielmino C, Bradbury S, Kennedy K, Cooley L, McEwan B, Kahler CM, Mowlaboccus S, Speers DJ, Baird R, Freeman K, Leong L, Warner M, Williamson DA, McVernon J, Lahra M, Jennison AV, Howden BP, Andersson P. Genomic Surveillance of Invasive Meningococcal Disease During a National MenW Outbreak in Australia, 2017-2018. Open Forum Infect Dis 2024; 11:ofae249. [PMID: 38854393 PMCID: PMC11161896 DOI: 10.1093/ofid/ofae249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 04/30/2024] [Indexed: 06/11/2024] Open
Abstract
Background In Australia, invasive meningococcal disease (IMD) incidence rapidly increased between 2014 and 2017 due to rising serogroup W (MenW) and MenY infections. We aimed to better understand the genetic diversity of IMD during 2017 and 2018 using whole genome sequencing data. Methods Whole genome sequencing data from 440 Australian IMD isolates collected during 2017 and 2018 and 1737 international MenW:CC11 isolates collected in Europe, Africa, Asia, North America, and South America between 1974 and 2020 were used in phylogenetic analyses; genetic relatedness was determined from single-nucleotide polymorphisms. Results Australian isolates were as follows: 181 MenW (41%), 144 MenB (33%), 88 MenY (20%), 16 MenC (4%), 1 MenW/Y (0.2%), and 10 nongenogroupable (2%). Eighteen clonal complexes (CCs) were identified, and 3 (CC11, CC23, CC41/44) accounted for 78% of isolates (343/440). These CCs were associated with specific serogroups: CC11 (n = 199) predominated among MenW (n = 181) and MenC (n = 15), CC23 (n = 80) among MenY (n = 78), and CC41/44 (n = 64) among MenB (n = 64). MenB isolates were highly diverse, MenY were intermediately diverse, and MenW and MenC isolates demonstrated the least genetic diversity. Thirty serogroup and CC-specific genomic clusters were identified. International CC11 comparison revealed diversification of MenW in Australia. Conclusions Whole genome sequencing comprehensively characterized Australian IMD isolates, indexed their genetic variability, provided increased within-CC resolution, and elucidated the evolution of CC11 in Australia.
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Affiliation(s)
- Emily Sotheran
- Microbiological Diagnostic Unit Public Health Laboratory at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
- Department of Microbiology and Immunology at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
| | - Courtney R Lane
- Microbiological Diagnostic Unit Public Health Laboratory at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
- Department of Microbiology and Immunology at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
| | - Kristy Horan
- Microbiological Diagnostic Unit Public Health Laboratory at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
- Department of Microbiology and Immunology at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
| | - Kerrie Stevens
- Microbiological Diagnostic Unit Public Health Laboratory at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
| | - Christine Guglielmino
- Public Health Microbiology, Forensic and Scientific Services, Queensland Department of Health, Brisbane, Australia
| | - Susan Bradbury
- Department of Clinical Microbiology and Infectious Diseases, Canberra Health Services, Australian National University Medical School, Canberra, Australia
| | - Karina Kennedy
- Department of Clinical Microbiology and Infectious Diseases, Canberra Health Services, Australian National University Medical School, Canberra, Australia
| | - Louise Cooley
- Department of Microbiology and Infectious Diseases, Royal Hobart Hospital, Tasmanian School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Australia
| | - Belinda McEwan
- Department of Microbiology and Infectious Diseases, Royal Hobart Hospital, Tasmanian School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Australia
| | - Charlene M Kahler
- Marshall Centre for Infectious Diseases Research and Training, School of Biomedical Sciences, University of Western Australia, Perth, Australia
| | - Shakeel Mowlaboccus
- Marshall Centre for Infectious Diseases Research and Training, School of Biomedical Sciences, University of Western Australia, Perth, Australia
| | - David J Speers
- PathWest Laboratory Medicine, Queen Elizabeth II Medical Centre, Nedlands, Australia
| | - Robert Baird
- Royal Darwin Hospital Pathology, Darwin, Australia
| | | | | | | | - Deborah A Williamson
- Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- Department of Infectious Diseases at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
| | - Jodie McVernon
- Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- Department of Infectious Diseases at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
| | - Monica Lahra
- New South Wales Health Pathology, Microbiology Randwick, The Prince of Wales Hospital, Sydney, Australia
| | - Amy V Jennison
- Public Health Microbiology, Forensic and Scientific Services, Queensland Department of Health, Brisbane, Australia
| | - Benjamin P Howden
- Microbiological Diagnostic Unit Public Health Laboratory at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
- Department of Microbiology and Immunology at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
- Centre for Pathogen Genomics, Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
| | - Patiyan Andersson
- Microbiological Diagnostic Unit Public Health Laboratory at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
- Department of Microbiology and Immunology at The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
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Genetic Features of a Representative Panel of 110 Meningococcal B Isolates to Assess the Efficacy of Meningococcal B Vaccines. mSphere 2022; 7:e0038522. [PMID: 36129279 PMCID: PMC9599336 DOI: 10.1128/msphere.00385-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Predictions of vaccine efficacy against Neisseria meningitidis serogroup B (NmB) disease are hindered by antigenic variability, limiting the representativeness of individual NmB isolates. A qualitative human serum bactericidal assay using endogenous complements of individual subjects (enc-hSBA) enables large panels of NmB isolates to be tested. A 110-isolate panel was randomly selected from 442 invasive NmB isolates from United States cases reported to the Centers for Disease Control (CDC) from 2000 to 2008. Typing analyses confirmed the 110-isolate panel is representative of the 442 isolates. The genetic features of the 110-isolate panel were compared against over 4,200 invasive NmB isolates collected from 2000 to 2018 in the United States, Australia, Canada, and nine European countries. Clonal complexes in the 110-isolate panel are also present in each geographical region; cumulative percentages show that these account for around 81% of the clonal complexes found in NmB isolates in other panels. For the antigens (fHbp, NHBA, PorA1.4, NadA) included in the currently licensed meningococcal serogroup B (MenB) vaccines, specifically considering the presence of at least one antigen with a matched genotype, the 110-isolate panel represents approximately 89% of the NmB isolates circulating worldwide, ranging from 87% for the European isolates to 95% and 97% for NmB isolates in the United States and Australia, respectively. The 110-isolate panel includes the most prevalent clonal complexes and genetic variants of MenB vaccine antigens found in a multinational collection of invasive NmB isolates. This panel is useful for assessing the efficacy of MenB vaccines in clinical trials worldwide. IMPORTANCENeisseria meningitidis serogroup B (NmB) is a major cause of invasive meningococcal disease (IMD). Predicting the effectiveness of vaccines against NmB is difficult because NmB is an uncommon disease and because antigens targeted by meningococcal serogroup B (MenB) vaccines have highly variable genetic features and expression levels. Therefore, a large number of NmB isolates from different regions would need to be tested to comprehensively assess vaccine effectiveness. We examined a panel of 110 isolates obtained from NmB IMD cases in the United States and compared the genetic features of this panel with those of panels from different countries around the world. We found the 110-isolate panel included the most common clonal complexes and genetic variants of MenB vaccine antigens that exist in the global collections of invasive NmB isolates. This confirms the value of the NmB 110-isolate panel in understanding the effectiveness of MenB vaccines in clinical trials worldwide.
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