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      Understanding the relation between Zika virus infection during pregnancy and adverse fetal, infant and child outcomes: a protocol for a systematic review and individual participant data meta-analysis of longitudinal studies of pregnant women and their infants and children

      protocol
      1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 14 , 25 , 26 , 27 , 28 , 22 , 29 , 30 , 31 , 32 , 33 , 34 , 14 , 35 , 36 , 37 , 38 , 39 , 7 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 7 , 48 , 49 , 50 , 51 , 52 , 53 , Zika Virus Individual Participant Data Consortium
      BMJ Open
      BMJ Publishing Group
      individual participant data meta-analysisis, prognosis, congenital Zika syndrome, Zika Virus, Microcephaly, risk prediction model

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          Abstract

          Introduction

          Zika virus (ZIKV) infection during pregnancy is a known cause of microcephaly and other congenital and developmental anomalies. In the absence of a ZIKV vaccine or prophylactics, principal investigators (PIs) and international leaders in ZIKV research have formed the ZIKV Individual Participant Data (IPD) Consortium to identify, collect and synthesise IPD from longitudinal studies of pregnant women that measure ZIKV infection during pregnancy and fetal, infant or child outcomes.

          Methods and analysis

          We will identify eligible studies through the ZIKV IPD Consortium membership and a systematic review and invite study PIs to participate in the IPD meta-analysis (IPD-MA). We will use the combined dataset to estimate the relative and absolute risk of congenital Zika syndrome (CZS), including microcephaly and late symptomatic congenital infections; identify and explore sources of heterogeneity in those estimates and develop and validate a risk prediction model to identify the pregnancies at the highest risk of CZS or adverse developmental outcomes. The variable accuracy of diagnostic assays and differences in exposure and outcome definitions means that included studies will have a higher level of systematic variability, a component of measurement error, than an IPD-MA of studies of an established pathogen. We will use expert testimony, existing internal and external diagnostic accuracy validation studies and laboratory external quality assessments to inform the distribution of measurement error in our models. We will apply both Bayesian and frequentist methods to directly account for these and other sources of uncertainty.

          Ethics and dissemination

          The IPD-MA was deemed exempt from ethical review. We will convene a group of patient advocates to evaluate the ethical implications and utility of the risk stratification tool. Findings from these analyses will be shared via national and international conferences and through publication in open access, peer-reviewed journals.

          Trial registration number

          PROSPERO International prospective register of systematic reviews (CRD42017068915).

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          Most cited references57

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials

            The CONSORT statement is used worldwide to improve the reporting of randomised controlled trials. Kenneth Schulz and colleagues describe the latest version, CONSORT 2010, which updates the reporting guideline based on new methodological evidence and accumulating experience. To encourage dissemination of the CONSORT 2010 Statement, this article is freely accessible on bmj.com and will also be published in the Lancet, Obstetrics and Gynecology, PLoS Medicine, Annals of Internal Medicine, Open Medicine, Journal of Clinical Epidemiology, BMC Medicine, and Trials.
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              Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data.

              We consider random effects meta-analysis where the outcome variable is the occurrence of some event of interest. The data structures handled are where one has one or more groups in each study, and in each group either the number of subjects with and without the event, or the number of events and the total duration of follow-up is available. Traditionally, the meta-analysis follows the summary measures approach based on the estimates of the outcome measure(s) and the corresponding standard error(s). This approach assumes an approximate normal within-study likelihood and treats the standard errors as known. This approach has several potential disadvantages, such as not accounting for the standard errors being estimated, not accounting for correlation between the estimate and the standard error, the use of an (arbitrary) continuity correction in case of zero events, and the normal approximation being bad in studies with few events. We show that these problems can be overcome in most cases occurring in practice by replacing the approximate normal within-study likelihood by the appropriate exact likelihood. This leads to a generalized linear mixed model that can be fitted in standard statistical software. For instance, in the case of odds ratio meta-analysis, one can use the non-central hypergeometric distribution likelihood leading to mixed-effects conditional logistic regression. For incidence rate ratio meta-analysis, it leads to random effects logistic regression with an offset variable. We also present bivariate and multivariate extensions. We present a number of examples, especially with rare events, among which an example of network meta-analysis.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2019
                18 June 2019
                : 9
                : 6
                : e026092
                Affiliations
                [1 ] departmentLee Kong Chian School of Medicine , Nanyang Technological University , Singapore, Singapore
                [2 ] departmentCentre for Mathematical Sciences , University of Plymouth , Plymouth, UK
                [3 ] departmentDepartment of Social Medicine , Universidade Federal de Pernambuco , Recife, Brazil
                [4 ] departmentHealth Emergencies Programme , Organisation mondiale de la Sante , Geneve, Switzerland
                [5 ] departmentDepartment of Collective Health, Institute Aggeu Magalhães (CPqAM) , Oswaldo Cruz Foundation , Recife, Brazil
                [6 ] departmentInstitute of Tropical Pathology and Public Health , Federal University of Goias , Goiânia, Brazil
                [7 ] departmentDepartment of Biochemistry and Immunology , Federal University of Minas Gerais , Belo Horizonte, Minas Gerais, Brazil
                [8 ] departmentDepartment of Medical Microbiology , University Medical Center Groningen , Groningen, The Netherlands
                [9 ] departmentDepartment of Social Medicine , University of São Paulo , São Paulo, Brazil
                [10 ] departmentReference Center for Neurodevelopment, Assistance, and Rehabilitation of Children , State Department of Health of Maranhão , Sao Luís, Brazil
                [11 ] departmentDepartment of Pediatrics , University Hospital Vall d’Hebron , Barcelona, Spain
                [12 ] SOSECALI C. Ltda , Guayaquil, Ecuador
                [13 ] departmentDepartment of Epidemiology , University of São Paulo , São Paulo, Brazil
                [14 ] departmentDepartment of Infectious Diseases, Section Clinical Tropical Medicine , UniversitatsKlinikum Heidelberg , Heidelberg, Germany
                [15 ] departmentEvidence and Intelligence for Action in Health , Pan American Health Organization , Washington, District of Columbia, USA
                [16 ] departmentDepartment of Pediatrics , D’Or Institute for Research & Education , Rio de Janeiro, Brazil
                [17 ] departmentDepartment of Obstetrics and Gynecology , Centre Hospitalier de l’Ouest Guyanais , Saint-Laurent du Maroni, French Guiana
                [18 ] departmentHospital Materno Infantil de Goiânia , Goiânia State Health Secretary , Goiás, Brazil
                [19 ] departmentCommunicable Diseases and Environmental Determinants of Health Department , Pan American Health Organization , Washington, District of Columbia, USA
                [20 ] departmentDepartment of Pediatrics , FMJ , São Paulo, Brazil
                [21 ] Faculdade de Medicina de Sao Jose do Rio Preto , departmentDepartment of Dermatologic Diseases , São José do Rio Preto, Brazil
                [22 ] departmentWindward Islands Research and Education Foundation , St. George’s University , True Blue Point, Grenada
                [23 ] departmentDepartment of Public Health , Universidade Federal do Maranhão – São Luís , São Luís, Brazil
                [24 ] departmentDepartment of Neonatology , Oswaldo Cruz Foundation (Fiocruz) , Rio de Janeiro, Brazil
                [25 ] departmentFacultad de Salud , Universidad Industrial de Santander , Bucaramanga, Colombia
                [26 ] departmentFaculty of Medical Sciences , University of Pernambuco , Recife, Brazil
                [27 ] departmentReproductive Health and Research , World Health Organization , Geneva, Switzerland
                [28 ] departmentHubert Department of Global Health , Emory University , Atlanta, Georgia, USA
                [29 ] departmentInstitute of Social and Preventive Medicine , University of Bern , Bern, Switzerland
                [30 ] departmentMcGill University Health Centre , McGill University , Montréal, Canada
                [31 ] departmentPediatric Infectious Diseases , Stanford Hospital , Palo Alto, California, USA
                [32 ] departmentDepartment of Virology , Erasmus Medical Center , Rotterdam, The Netherlands
                [33 ] departmentDepartment of Reproductive Health and Research , World Health Organization , Geneva, Switzerland
                [34 ] departmentDepartment of Infectious Diseases , Hospital Federal dos Servidores do Estado , Rio de Janeiro, Brazil
                [35 ] departmentInstituto de Puericultura e Pediatria Martagão Gesteira , Universidade Federal do Rio de Janeiro , Rio de Janeiro, Brazil
                [36 ] departmentStatistics , University of British Columbia , British Columbia, Vancouver, Canada
                [37 ] departmentINSERM CIC1410 Clinical Epidemiology , CHU La Réunion , Saint Pierre, Réunion
                [38 ] departmentUM 134 PIMIT (CNRS 9192, INSERM U1187, IRD 249, Université de la Réunion) , Universite de la Reunion , Sainte Clotilde, Réunion
                [39 ] Children’s Hospital Juvencio Matos , São Luís, Brazil
                [40 ] departmentSustainable Development and Environmental Health , Pan American Health Organization , Washington, District of Columbia, USA
                [41 ] departmentDepartment of Gynecology and Obstetrics , University of São Paulo , São Paulo, Brazil
                [42 ] departmentJulius Center for Health Sciences and Primary Care , University Medical Center Utrecht , Utrecht, The Netherlands
                [43 ] departmentMother and Children Health Research Department , Instituto de Efectividad Clinica y Sanitaria , Buenos Aires, Argentina
                [44 ] departmentSchool of Public Health and Tropical Medicine , Tulane University , New Orleans, USA
                [45 ] departmentDepartment of Reproductive Health and Research , World Health Organization , Geneva, Switzerland
                [46 ] departmentDepartment of Infectious Disease Epidemiology , London School of Hygiene and Tropical Medicine , London, UK
                [47 ] departmentInstituto de pesquisa Clínica Evandro Chagas , Fundacao Oswaldo Cruz , Rio de Janeiro, Brazil
                [48 ] departmentFacultad de Ciencias de la Salud , Universidad de Carabobo , Valencia, Carabobo, Bolivarian Republic of Venezuela
                [49 ] departmentDepartments of Medicine and of Epidemiology, Biostatistics & Occupational Health , McGill University , Montreal, Quebec, Canada
                [50 ] departmentDepartment of Infectious and Parasitic Diseases , Faculdade de Medicina da Universidade de Sao Paulo , São Paulo, Brazil
                [51 ] departmentDepartment of Tropical Medicine , Federal University of Pernambuco , Recife, Brazil
                [52 ] departmentDepartment of Pediatrics , Federal University of Rio de Janeiro , Rio de Janeiro, Brazil
                [53 ] departmentFacultad de Ciencias Médicas , Universidad Nacional Autónoma de Honduras , Tegucigalpa, Honduras
                Author notes
                [Correspondence to ] Dr Lauren Maxwell; maxwelll@ 123456who.int , lauren.maxwell.us@ 123456gmail.com
                Author information
                http://orcid.org/0000-0003-4817-8986
                http://orcid.org/0000-0002-3276-5919
                Article
                bmjopen-2018-026092
                10.1136/bmjopen-2018-026092
                6588966
                31217315
                89e4a7e0-6b45-4c96-b2ba-e2d01ed657b5
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

                History
                : 17 August 2018
                : 11 February 2019
                : 9 May 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Categories
                Epidemiology
                Protocol
                1506
                1692
                Custom metadata
                unlocked

                Medicine
                individual participant data meta-analysisis,prognosis,congenital zika syndrome,zika virus,microcephaly,risk prediction model

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