BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access Protocol 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 Annelies Wilder-Smith,1 Yinghui Wei,2 Thalia Velho Barreto de Araújo,3 Maria VanKerkhove,4 Celina Maria Turchi Martelli,5 Marília Dalva Turchi,6 Mauro Teixeira,7 Adriana Tami,8 João Souza,9 Patricia Sousa,10 Antoni Soriano-Arandes,11 Carmen Soria-Segarra,12 Nuria Sanchez Clemente,13 Kerstin Daniela Rosenberger,14 Ludovic Reveiz,15 Arnaldo Prata-Barbosa,16 Léo Pomar,17 Luiza Emylce Pelá Rosado,18 Freddy Perez,19 Saulo D. Passos,20 Mauricio Nogueira,21 Trevor P. Noel,22 Antônio Moura da Silva,23 To cite: Wilder-Smith A, Wei Y, Maria Elisabeth Moreira,24 Ivonne Morales,14 Maria Consuelo Miranda Montoya,25 by copyright. Araújo TVB, et al. Understanding Demócrito de Barros Miranda-Filho,26 Lauren Maxwell,27,28 the relation between Zika virus infection during pregnancy Calum N. L. Macpherson,22 Nicola Low, 29 Zhiyi Lan,30 Angelle Desiree LaBeaud,31 and adverse fetal, infant and Marion Koopmans,32 Caron Kim,33 Esaú João,34 Thomas Jaenisch,14 child outcomes: a protocol Cristina Barroso Hofer,35 Paul Gustafson,36 Patrick Gérardin, 37,38 for a systematic review and individual participant data meta- Jucelia S. Ganz,39 Ana Carolina Fialho Dias,7 Vanessa Elias,40 Geraldo Duarte,41 analysis of longitudinal studies Thomas Paul Alfons Debray,42 María Luisa Cafferata,43 Pierre Buekens,44 of pregnant women and their Nathalie Broutet,45 Elizabeth B. Brickley,46 Patrícia Brasil,47 Fátima Brant,7 infants and children. BMJ Open 2019;9:e026092. doi:10.1136/ Sarah Bethencourt,48 Andrea Benedetti,49 Vivian Lida Avelino-Silva,50 bmjopen-2018-026092 Ricardo Arraes de Alencar Ximenes,51 Antonio Alves da Cunha,52 Jackeline Alger,53 ►► Prepublication history and Zika Virus Individual Participant Data Consortium additional material for this paper are available online. To view please visit the journal (http://​ dx.​doi.​org/​10.​1136/​bmjopen-​ Abstract and develop and validate a risk prediction model to 2018-​026092). Introduction Zika virus (ZIKV) infection during pregnancy identify the pregnancies at the highest risk of CZS or is a known cause of microcephaly and other congenital adverse developmental outcomes. The variable accuracy Received 17 August 2018 and developmental anomalies. In the absence of a ZIKV of diagnostic assays and differences in exposure and Revised 11 February 2019 vaccine or prophylactics, principal investigators (PIs) outcome definitions means that included studies will Accepted 9 May 2019 and international leaders in ZIKV research have formed have a higher level of systematic variability, a component the ZIKV Individual Participant Data (IPD) Consortium of measurement error, than an IPD-MA of studies of an to identify, collect and synthesise IPD from longitudinal established pathogen. We will use expert testimony, © Author(s) (or their studies of pregnant women that measure ZIKV infection existing internal and external diagnostic accuracy employer(s)) 2019. Re-use during pregnancy and fetal, infant or child outcomes. validation studies and laboratory external quality permitted under CC BY. Methods and analysis We will identify eligible studies assessments to inform the distribution of measurement Published by BMJ. through the ZIKV IPD Consortium membership and a error in our models. We will apply both Bayesian and For numbered affiliations see frequentist methods to directly account for these and other systematic review and invite study PIs to participate in end of article. the IPD meta-analysis (IPD-MA). We will use the combined sources of uncertainty. Correspondence to dataset to estimate the relative and absolute risk of Ethics and dissemination The IPD-MA was deemed Dr Lauren Maxwell; congenital Zika syndrome (CZS), including microcephaly exempt from ethical review. We will convene a group of ​maxwelll@​who.​int, and late symptomatic congenital infections; identify and patient advocates to evaluate the ethical implications and ​lauren.​maxwell.u​ s@​gmail.c​ om explore sources of heterogeneity in those estimates utility of the risk stratification tool. Findings from these Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 1 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access analyses will be shared via national and international conferences and through publication in open access, peer-reviewed journals. Strengths and limitations of this study Trial registration number PROSPERO International prospective register ►► This is one of the first applications of an individual participant data of systematic reviews (CRD42017068915). meta-analysis (IPD-MA) to address public health concerns in the context of an emerging pathogen. Lessons learnt from this IPD-MA may facilitate the formation of research collaborations to inform the Introduction public health response to future epidemics. Zika virus (ZIKV) infection during pregnancy is an ►► By using a diversity of populations to develop and validate the risk acknowledged cause of microcephaly and other forms of prediction tool that identifies pregnancies at the highest risk of con- fetal brain defects and disability.1 2 ZIKV is an arbovirus in genital Zika syndrome, the IPD-MA provides a real opportunity to help inform how clinicians and laboratory scientists communicate the genus Flavivirus that is usually transmitted through the Zika virus (ZIKV) results to pregnant women and their families. female Aedes aegypti mosquito. Aedes aegypti is also the main ►► There is a high degree of variability in the accuracy of diagnostic vector for dengue (DENV), urban yellow fever (YF) and assays for ZIKV, coinfection and outcome ascertainment. Addressing chikungunya viruses. The Asian strain of ZIKV has been this variability will be a challenge and ultimately a limitation of the shown to replicate in the placenta and fetal brain;3 ZIKV accuracy of IPD-MA results. transmitted from mother to fetus during pregnancy may ►► There is no gold standard diagnostic assay to detect ZIKV infection have a detrimental effect on fetal brain development.4–6 during pregnancy and few studies have been able to measure fetal Microcephaly, generally defined as a 2–3 SD reduc- infection. The statistical methods traditionally used to account for tion from the mean head circumference,7 8 is caused by measurement error in IPD-MA need to be adapted to account for the infections during pregnancy, maternal diet, drug abuse, myriad, correlated sources of uncertainty that arise in the synthesis genetic factors or environmental exposures.9 10 Micro- of participant-level data from studies that arise in the context of an emerging pathogen. cephaly (congenital or acquired) may be associated with developmental delays: intellectual, hearing and visual impairment and epilepsy.11 The causal relation between ZIKV and a spectrum of fetal anomalies that includes and related neurological complications represented a microcephaly, now known as congenital Zika syndrome Public Health Emergency of International Concern on (CZS),12 has been supported through several case-con- 1 February 2016.27 trol;13 14cohort15 16 and surveillance studies;17 animal and ZIKV presents myriad challenges from an epidemi- by copyright. cell studies18 and through two systematic reviews of the ological, virological, diagnostic and outbreak control evidence for causality that considered all study designs.1 2 perspective. Diagnosing ZIKV infection is complicated by The relation between ZIKV infection during pregnancy the absence of symptoms in most cases or the presence of and miscarriage (pregnancy loss <20 weeks gestation) non-specific symptoms; cross-reactivity with DENV;28 29the and fetal loss (pregnancy loss ≥20 weeks gestation) is still short window for diagnosing acute infection and the lack of under investigation. point-of-care diagnostics.30 Recent research suggests that Prior to the 2013–2016 epidemic waves, ZIKV infection the relation between ZIKV infection during pregnancy was known clinically as a mild illness characterised by and fetopathology may vary by virus genotype or lineage; symptoms shared with other arboviruses, including macu- primary versus secondary infection31 and DENV-immune lopapular rash, headache, fever, non-purulent conjuncti- status and genotype in the presence of coinfection.29 32 33 vitis and/or joint and muscle pain.19 During the 2015–2016 The unequal spatial distribution of microcephaly cases ZIKV outbreak in Brazil, which extended to a number has been discussed extensively.34–36 These differences may of other Latin American countries, there was a sharp be related to population-level differences in baseline risk increase in reports of microcephaly and other neonatal of adverse fetal outcomes (clinically important heteroge- neurological conditions and in Guillain-Barré syndrome neity), differences in study design (eg, inclusion criteria; (GBS),20–22 an autoimmune neurological disorder. Subse- measurement of important cofactors) or to measurement quent analysis of medical records collected during and error, defined as the difference between the observed and after the 2013–2014 ZIKV outbreak in French Polynesia actual level of a given variable. Laboratory confirmation identified several ZIKV-linked pregnancies that had not of ZIKV infection and coinfection differs by diagnostic been recorded earlier because they ended in elective algorithms (eg, definition of positive and negative ZIKV abortion or stillbirth. The reanalysis of medical records diagnostic assay results); factors that affect the regularity indicated that the prevalence of both microcephaly of testing (eg, provision of incentives, distance from and GBS had increased in the wake of the outbreak in testing centre, differences across protocols); popula- French Polynesia.23 24 The Pan American Health Organi- tion-specific distribution of related coinfections; differing zation (PAHO) issued a ZIKV Epidemiological Alert for levels of training of laboratory staff and the accessibility Member States on 7 May 2015,25 the Brazilian Ministry of of materials and technology (eg, ultrasound, immuno- Health (MOH) declared a national public health emer- assays, reliability panels), among other factors. In addi- gency due to the time and cluster of microcephaly cases tion to documented difficulties in accurately measuring identified in Northeastern Brazil on 12 November 201526 infant head circumference, measurement standards and the WHO declared that the clusters of microcephaly for identifying microcephaly differ across populations 2 Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access and standards themselves may not appropriately classify are currently being investigated, seem to have reduced reduced or enlarged head circumference.37 38 the numbers of ZIKV infections during the 2017/2018 Our limited understanding of the absolute risk of epidemic cycle. While many studies have followed infants adverse fetal, infant and child outcomes in ZIKV-infected to the end of their first year, certain developmental mile- mothers led to calls from several governments suggesting stones can only be assessed after age 249 or when a child that women avoid becoming pregnant for as long as reaches school age. Leveraging limited data from studies 2 years.39 40 ZIKV disproportionately affects low-income with extended follow-up of ZIKV-infected and non-in- populations residing in areas with poor living condi- fected women will be essential for estimating the risk of tions.41 The impetus placed on women to delay pregnancy more subtle, long-term effects of ZIKV infection during as a ZIKV control measure is complicated by the limited pregnancy. By combining data from individual studies, access to contraception and safe abortion in many of the the proposed IPD-MA will improve the precision of risk countries and regions with the highest burden of ZIKV-re- estimates. lated microcephaly.42 43 Identifying the risk factors for CZS is a global health priority and central for prioritising Identify and quantify the relative importance of effect measure resource allocation for vector control and effective and modifiers targeted family planning interventions and for improving The benefits of using IPD rather than AD to assess effect risk counselling for ZIKV-infected pregnant women or women planning a pregnancy in endemic areas. measure modification and interaction are myriad.50 In a one-stage analysis with IPD, subject level data are meta-an- Rationale for the individual participant data meta-analysis of alysed using the exact binomial distribution; in a two-stage longitudinal studies of pregnant women analysis of IPD or AD, study-level outcome measures Individual participant data meta-analysis (IPD-MA) is are combined assuming asymptomatic normality.51 In a the quantitative synthesis of participant-level data from one-stage analysis of IPD, study-level and individual-level included studies, while appropriately accounting for the sources of heterogeneity can be assessed concurrently clustering of information at the study level. The proposed and IPD are better able to identify heterogeneity in the IPD-MA will combine deidentified, participant-level cohort context of rare events or small studies.50 52 Individual data from different populations of pregnant women to studies are often powered to detect the overall effect of identify and quantify the relative importance of different the exposure rather than subgroup effects. Due to vari- by copyright. predictors of CZS. Individual participant data (IPD) ations in the characteristics of the affected populations have a number of analytic benefits over aggregate data and in the potential confounders and effect modifiers meta-analysis (AD-MA), a form of knowledge synthesis that measured by different studies, it is unlikely that individual combines study-level measures of effect.44 45 IPD facilitate studies will be powered to definitively quantify the impor- the assessment of effect measure modification, the devel- tance of different sources of heterogeneity in the relation opment and validation of risk prediction models, and the between ZIKV infection during pregnancy and adverse application of a unified analytic approach. In addition to fetal, infant or child outcomes. using the same statistical model across studies, with IPD we can apply the same or similar exclusion criteria, diag- Clinical risk prediction to inform decision-making and resource nostic algorithms, methods for addressing missing data allocation and confounding and conduct the same types of sensi- While there are a number of vaccine trials underway,53 tivity analyses needed to explore unexplained within- and the development of a ZIKV vaccine is complicated by between-study heterogeneity. the necessity of testing the vaccine in pregnant women; assessing whether the vaccine is associated with devel- Increased precision of estimates opment of GBS; the difficulties inherent in developing Timely, accurate and reliable predictions are predicated an arbovirus vaccine;46 54–56 findings from in vivo studies on well-designed studies that minimise the risk of bias, that indicate cross-reactivity between ZIKV and DENV adequate sample size and the inclusion of a diversity of populations. Adequate sample size is crucial for precise or West Nile virus is related to antibody-dependent estimation of the risk of CZS within important subgroups enhancement of ZIKV infection;55 57 58 and by the poten- (eg, women infected during the first trimester; preg- tial use of prevention of infection as a vaccine efficacy nant women with previous or concurrent DENV, CHIKV endpoint.59 In this context, identifying the pregnancies and STORCH (syphilis, toxoplasmosis, rubella, cyto- at the highest risk of adverse neonatal and later devel- megalovirus and herpes) pathogen exposure). Vector opmental outcomes is critical for effective resource control measures, including pesticides, public education allocation and prevention strategies. We will use partic- campaigns, the use of drones to detect standing water ipant-level data to develop and externally validate clin- and the introduction of sterilised male vectors to reduce ical risk prediction models to facilitate the identification Aedes aegypti populations, have been implemented in the of pregnancies that are most likely to result in ZIKV-re- wake of the 2015/2016 ZIKV epidemics.46–48 Fortunately, lated adverse fetal or infant outcomes and longer-term these measures, in combination with other factors that developmental delays. Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 3 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access Standardisation and cross-national partnerships to inform the expert panel and made available on the WHO website in public health response to emerging pathogens March 2016 (http://www.​who.​int/​csr/​resources/​publi- Formation of the ZIKV IPD Consortium cations/​zika/​laboratory-​testing/​en/). The IPD-MA will The ZIKV IPD Consortium is a global collaboration need to account for the between-study and within-study designed to streamline the international response to differences in diagnostic assays and testing algorithms. ZIKV. To facilitate cross-country analyses and a coor- dinated response to ZIKV, representatives from WHO, PAHO, the US Centers for Disease Control and Preven- Objectives of the IPD-MA tion (CDC), the National Institutes of Health (NIH), 1. Estimate the absolute and relative risks of fetal in- the National Institute of Allergy and Infectious Diseases fection; miscarriage (<20 weeks gestation), fetal loss (NIAID), Institut national de la santé et de la recherche (≥20 weeks gestation), microcephaly and other man- médicale (INSERM), Institut Pasteur, and the networks ifestations of CZS and later developmental delays for of Fundação Oswaldo Cruz (Fiocruz), Grupo de Pesquisa women who do and do not experience ZIKV infection da Epidemia da Microcefalia (MERG)/ZikaPlan, ZIKAlli- during pregnancy. ance, ZIKAction, the Consortium for the Standardization 2. Identify factors that modify women’s risk of adverse of Influenza Seroepidemiology (CONSISE) and Interna- ZIKV-related fetal, infant and child outcomes and in- tional Severe Acute Respiratory and Emerging Infection fants’ risk of infection (eg, gestational age at time of Consortium (ISARIC) have developed a standardised infection, clinical or subclinical illness, concurrent or protocol for cohorts of pregnant women and their infants prior arbovirus exposure, other congenital infections exposed to ZIKV to facilitate the proposed IPD-MA; and other posited effect measure modifiers). identified existing or planned cohorts and prospectively 3. Use information on the relative importance of differ- introduced cohort principal investigators (PI)s and MOH ent effect measure modifiers identified in Objective 2 officials to the methodological and public health benefits to decompose the total effect of ZIKV infection during related to IPD-MA in the context of Zika. Many of the pregnancy on adverse fetal, infant and child outcomes longitudinal studies and surveillance systems identified into (1) the direct effect of ZIKV; (2) the indirect effect to date through the review of country-level registries, of ZIKV as mediated by the effect measure modifier of existing literature reviews and ZIKV IPD Consortium interest (eg, DENV, CHIKV or STORCH pathogens) by copyright. membership have agreed to contribute deidentified, and (3) the effect of the interaction between ZIKV and participant level data to the analysis. A complete list of the mediator of interest. the studies and surveillance systems who have agreed to 4. Develop and validate a risk prediction tool to identi- contribute data to the ZIKV IPD Consortium led IPD-MA fy pregnant women at a high risk of an adverse ZIKV- is included in online supplementary table 1. related outcome and to inform couples planning a pregnancy, healthcare providers and/or resource mo- Standardised protocols for cohorts of pregnant women and their bilisation (eg, vector control strategies; antenatal care; infants open access to contraception). A multiplicity of mechanisms for exposure and outcome ascertainment as well as differences in the measurement of important cofactors are known challenges for the Methods and analysis meta-analysis of data from individual research studies. To This protocol has been drafted in accordance with the minimise the potential for heterogeneity caused by differ- PRISMA-P Statement (online supplementary table 2).61 ences in study inclusion criteria and the measurement of The proposed systematic review and meta-analysis will ZIKV, infant outcomes and important cofactors, WHO/ follow the PRISMA-IPD guidelines for the systematic PAHO, Institut Pasteur, Fiocruz, CONSISE and ISARIC review of non-randomised studies.62 convened an international meeting of ZIKV researchers and MOH officials in June 2016 to develop standardised Step 1. Study identification protocols and data collection instruments for cohort Eligibility criteria studies of pregnant women and newborns and other Eligible studies will use a longitudinal design where ZIKV-related studies.60 Standardisation of protocols and ZIKV infection is measured in pregnant women prior data collection instruments was intended to minimise to outcome ascertainment. Eligible studies may include differences in case ascertainment and data collection cohort studies, case-cohort studies, randomised control methods to facilitate data synthesis and the identifica- trials or active surveillance systems, regardless of publi- tion of sources of heterogeneity in the relation between cation status. Studies may enrol symptomatic and/or congenital Zika infection and adverse fetal, infant and asymptomatic women prior to or following a confirmed child outcomes. The protocols were made available on pregnancy. Included studies and active surveillance WHO website in October 2016 (http://www.​ who.​ int/​ systems will test women for ZIKV infection during preg- reproductivehealth/​ zika/​en). The standardised proto- nancy, follow women until the end of pregnancy and cols do not include detailed guidance on laboratory assess for CZS or related fetal, infant or child outcomes methods, but testing algorithms were developed by an (see table 1). We will exclude studies with fewer than 10 4 Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 Table 1 Participant-level variables of interest Maternal ZIKV infection (diagnosis: confirmed, probable, unlikely; primary, secondary, naïve; viral load) Exposure Fetal or placental ZIKV infection (diagnosis: confirmed, probable, unlikely; primary, secondary, naïve; viral load)* Primary outcomes Miscarriage (<20 weeks gestation) Fetal loss (≥20 weeks gestation) Microcephaly (diagnosis: severe microcephaly, microcephaly, normocephaly, macrocephaly; Z-score) CZS (diagnosis: confirmed, probable, unlikely) Secondary fetal outcomes† Induced abortion with microcephaly (diagnosis: confirmed, probable, unlikely) Early fetal death (20–27 weeks gestation) Late fetal death (≥28 weeks gestation) Late fetal death (≥28 weeks gestation) with microcephaly Placental insufficiency (diagnosis: confirmed, probable, unlikely)‡ Intrauterine growth restriction Secondary infant outcomes† Postnatal microcephaly (diagnosis: severe microcephaly, microcephaly, normocephaly, macrocephaly; Z-score) Gestational age at birth Birth weight (diagnosis: normal birth weight; low birth weight; very low birth weight; extremely low birth weight; Z-score) Craniofacial disproportion Neuroimaging abnormalities (intracranial calcification, lissencephaly, hydranencephaly, porencephaly, ventriculomegaly, posterior fossa abnormalities, Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 cerebellar hypoplasia, corpus callosal and vermian dysgenesis; focal cortical dysplasia) Postnatal intraventricular haemorrhage Motor abnormalities (hypotonia, hypertonia, hyperreflexia, spasticity, clonus, extrapyramidal symptoms)§ Seizures, epilepsy§ Ocular abnormalities (blindness, other)§ Congenital deafness or hearing loss§ Congenital contractures (arthrogryposis, unilateral or bilateral clubfoot) Other non-neurological congenital abnormalities Secondary outcomes detected Cortical auditory processing after the infant period¶ Neurodevelopment (expressive and receptive language, fine and gross motor skills, attention and executive function, memory and learning, socioemotional development, overall neurodevelopmental score) Vision (Cardiff test) Posited confounders Demographic factors (age, education, marital status, racial/ethnic group; BMI) Socioeconomic factors Maternal smoking, illicit drug and alcohol use Maternal prescription drug use, vaccination Maternal experience of violence during pregnancy; infant or child exposure to intimate partner violence127 Workplace or environmental exposures to teratogenic substances (eg, maternal exposure to lead, mercury) Continued Open access 5 by copyright. BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected 6 Open access Table 1 Continued Potential effect measure Genetic anomalies, metabolic disorders, perinatal brain injury modifiers Gestational age, term at birth Timing of infection during pregnancy Clinical/subclinical illness Viral genotype and load Concurrent or prior flavivirus or alphavirus infection Maternal history of YF or JE vaccination Maternal immunosuppressive conditions, disorders, comorbidities (eg, chronic hypertension, diabetes) or pregnancy-related conditions (eg, pre-eclampsia, gestational diabetes) Intrauterine exposure to STORCH pathogens Maternal malnutrition Presence and severity of maternal and infant clinical symptoms *Fetal ZIKV infection will be considered as both an exposure and an outcome; definition of fetal infection will be based on clinical and radiological criteria defined by an expert panel. †Both with and without microcephaly. ‡As estimated by antenatal consequences of placental insufficiency, including fetal growth restriction, oligohydramnios, non-reassuring fetal heart rate tracing or small for gestational age at birth as markers of placental insufficiency. §May also be detected after the infant period. ¶As measured by the Bayley Scale;128 Ages and Stages;129 INTERGROWTH-21st Neurodevelopmental Assessment.49 BMI, body mass index; CZS, congenital Zika syndrome; JE, Japanese encephalitis; STORCH, syphilis, toxoplasmosis, rubella, cytomegalovirus and herpes; YF, yellow fever virus; ZIKV, Zika virus Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 by copyright. BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access participants and limit included surveillance systems to and laboratory procedures; assay and specimen type; those that capture country or territory-level active surveil- criteria used to define ZIKV infection and timing of infec- lance data (ie, individual hospital active surveillance data tion and exposure, cofactor and outcome ascertainment will not be included). Before sharing participant-level for all eligible studies. We will ask study PIs for clarifica- data, research studies will be asked to provide documen- tion if there are outstanding questions or disagreements tation of ethics review. regarding study-level data. Information sources Step 2. Collection, review and synthesis of deidentified, ZIKV IPD Consortium participant-level data We anticipate that most eligible studies will have been We will contact the PIs and authors of studies that meet identified through the efforts of the ZIKV IPD Consor- our inclusion criteria to request deidentified, partici- tium. The Consortium is an international initiative that pant-level data on select variables and the associated is meant to include the PIs from all planned, ongoing or surveys and data dictionaries or codebooks. If study data completed ZIKV longitudinal studies at the time of this have been imputed, we will request both the original and review. We have searched clinical trials and ZIKV-related imputed data so that we can apply consistent imputation databases63 (online supplementary table 3) to identify methods across studies and review the imputed dataset existing or planned longitudinal studies. We have circu- for validation purposes. To reduce the burden on indi- lated the list of ongoing or planned ZIKV-related longi- vidual studies and ensure clear documentation of all steps tudinal studies of pregnant women to MOH Officials in in the creation of the synthesised dataset, we will use the countries with autochthone ZIKV transmission and to study codebooks or data dictionaries to develop study-spe- PIs of ZIKV cohorts and asked them to update the list as cific code in the statistical language used by the study data necessary. manager that selects only the study variables required for the proposed analyses and removes information that Systematic review could be used to identify individual participants. The We will perform a systematic search of biomedical data- study’s data manager will apply the code to the original bases for published longitudinal studies and protocols. dataset. The deidentified, participant-level data will be The search strategy is based on Medical Subject Headings transferred from the study site to Emory University, which (MeSH) and text-based search terms for ZIKV, pregnant will serve as the WHO data synthesis partner centre, using by copyright. women, infants and children. The search strategy was secure file transfer protocol and will be protected on a developed in collaboration with an information scien- secure server with standard encryption and by the Emory tist and adapted for the following electronic databases: University firewall. Data synthesis-related decisions will Embase (Medline), Embase (Ovid) and SCOPUS (see be reviewed by a ZIKV IPD Consortium membership and online supplementary text 1 for the search strategy for will be recorded using Jupyter Notebook.65 Researchers Embase (Medline and Ovid). We also will search the who are unable or unwilling to provide their participant additional databases listed in online supplementary table data after at least four attempts at contact by the project 3 and review the reference lists of published systematic team over a period of 6 months will be excluded from reviews and the list of studies produced by a living system- the IPD-MA and we will report the reason for their exclu- atic review of ZIKV studies conducted by the University of sion. When IPD are not available for a given study, we will Bern64 to identify additional studies. After removing dupli- extract study-level effect estimates from any publications cates from the list of identified studies, two reviewers will to compare study-level estimates from all eligible studies, independently screen the title and abstracts of included whether or not they provide data for the IPD-MA. studies to identify longitudinal studies or active surveil- lance systems that measure ZIKV infection during preg- Variables of interest nancy and subsequent fetal, infant or child outcomes. Despite efforts to develop protocols that can be applied Disagreements about study inclusion will be resolved by across studies, there will be significant cross-study hetero- consensus. geneity in how congenital Zika infection, cofactors and outcomes are measured and reported. Exposure, Collection of study-level data outcome variables and posited confounders and effect We will contact the PIs of eligible studies identified measure modifiers are listed in table 1. Where possible, through either the ZIKV IPD Consortium or the elec- ZIKV and other infections (eg, DENV, CHIKV, STORCH tronic searches to invite them to take part in the IPD-MA pathogens) will be modelled as time-varying, rather than and ask them to provide a copy of their study protocol. We time-fixed covariates. Given that the case definitions for will develop and pilot an electronic data extraction form microcephaly have changed over time (and may change to record study-level characteristics for all eligible studies, during the course of included studies), we will allow for regardless of whether study PIs agree to participate in the coding of variables with different definitions (ie, WHO the IPD-MA. Two reviewers will independently review fetal growth chart,66 Fenton scale,67 INTERGROWTH protocols and study-related publications to extract data 21st Project49). We will ask studies for data on the contin- on study design; study population; enrolment, follow-up uous measures used to make diagnoses (eg, viral load; Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 7 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access head circumference) rather than just the diagnoses that includes experts on the evaluation of laboratory themselves (eg, maternal ZIKV infection, microcephaly). assays and external quality assessment (EQA); obstet- Using continuous variables will allow us to test the sensi- rics and perinatal epidemiology will provide a detailed tivity of results to the application of different cutoffs and description of the role of selection, confounding and the reference standards used to generate Z-scores. Defi- measurement-related biases within studies. nitions for miscarriage, fetal loss and other pregnancy outcomes vary across countries. We will explore the sensi- Step 3. Statistical analyses tivity of project findings to different outcome definitions. Objectives 1 and 2 Estimate the absolute and relative risks of adverse ZIKV-related Assessing the integrity of deidentified, participant-level data fetal, infant and child outcomes; identify and quantify relative We will review the distribution of variables to identify importance of sources of heterogeneity potential outliers and to assess the proportion missing Estimating the absolute risk of CZS by the gestational within each study. We will discuss the distribution of key age of the fetus at the time of infection is as important as variables with the study data manager to identify and it is difficult. Early in the outbreak, cohort studies limited address any inconsistencies. If there has been a publica- enrolment to symptomatic pregnant women. While an tion related to a given longitudinal study, we will attempt estimated 50%–70% of infections are subclinical, when to replicate table 1 presented in the publication and will symptoms are detected they generally appear 3–14 days resolve any inconsistencies with the data manager. after infection.71 For asymptomatic infections, the gesta- Synthesis of participant-level data tional age of infection is interval censored because it is Given that these longitudinal studies and active surveil- defined by the last negative and first positive tests for ZIKV. lance systems are part of the global research response to Rather than using the midpoint between the last negative an emerging pathogen, there is a high degree of variability and first positive ZIKV test, which is known to be biased, we in the data that have been collected across studies and the will impute the trimester or week that asymptomatic infec- algorithms that have been applied to define ZIKV expo- tions occurred using methods that are routinely applied sure, symptoms, components of CZS and so on. Where in studies with interval censored covariates in the field of possible, we will ask studies for the individual factors (ie, perinatal research.72 73 In table 2, we present sample defi- fever, rash) that were used to define certain parameters nitions for the absolute risk of fetal and infant outcomes. by copyright. (ie, clinical infection) to ensure cross-study consistency These definitions will be reviewed prior to analysis and in composite markers. Similarly, we will combine the data publication and we will assess the sensitivity of our results inputs for exposure, cofactor and outcome classification to the definition applied. Later developmental outcomes algorithms to reduce cross-study differences in the classi- (eg, neurodevelopment, cortical auditory processing), fication of important factors. listed in table 1 as secondary outcomes, will follow a fetus- es-at-risk approach.74 We will apply censoring to account Critical review of study quality for competing risks where necessary. We will use the Cochrane Methodological Quality Assess- We will apply mixed binomial models for binary ment of Observational Studies68 and the Q-Coh tool69 outcomes, and multinomial models for categorical to help describe the risk of bias within non-randomised outcomes, with a logit link to provide estimates for each studies and will apply the Cochrane Risk of Bias 2.0 tool measure of absolute risk by week or trimester of congen- to assess the risk of bias in randomised controlled trails.70 ital infection. Because of the differences in baseline risks Rather than using a score-based bias assessment, a panel across populations, pooling measures of absolute risk Table 2 Definitions applied to estimation of absolute risk of primary fetal and infant outcomes Outcome Numerator Denominator Miscarriage Number of miscarriages (pregnancy loss prior Total number of pregnancies to 20 weeks gestation) Early fetal death Number of pregnancies lost between Total number of pregnancies carried to 20 weeks gestation 20 and 27 weeks gestation Late fetal death Number or pregnancies lost at or following Total number of pregnancies carried to 28 weeks gestation 28 weeks gestation Microcephaly Number of microcephaly cases Total number of pregnancies carried to ≥24 weeks gestation, when microcephaly can be assessed by ultrasound in ZIKV-infected mothers,38 we will consider all pregnancies regardless of whether the pregnancy results in a live birth ZIKV, Zika virus. 8 Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access across studies may not be clinically relevant and can even are excluded from certain studies are missing at random be misleading.75 We will combine study-level estimates and will incorporate studies by setting the missing obser- of absolute risk through: (1) a one-stage meta-analysis vations and within-study correlations between outcomes (mixed binomial or multinomial model with a log link) to zero and will set the within-study variance to a very that includes study-level sources of heterogeneity and high number such that the artificial value that acts as a a separate intercept for each study to account for addi- substitute for the missing outcome will have a negligible tional cross-study differences in baseline risk and (2) a effect on the meta-analytic estimate from the multivar- forest plot of study-level estimates of absolute risk that iate model.82 Alternatively, under a Bayesian framework, does not include a summary meta-analytic estimate. we will model a joint distribution for studies providing Absolute measures of effect are considered more multiple outcomes and a univariate distribution for important for informing clinical practice than relative studies providing a single outcome without needing to measures.76 We will conduct both (1) a one-stage meta-anal- address the missing within-study correlations and vari- ysis where we estimate the relative risk of the aforemen- ance for studies with only one outcome.83 The secondary tioned outcomes of interest by congenital Zika infection outcomes that will be included in the multivariate analysis across studies and (2) a two-stage meta-analysis where are listed in table 1. we estimate the relative risk in each study and combine We will compare generalised linear mixed models study-level measures using random effects meta-analysis (GLMMs) where we use one model to analyse nested or to allow the underlying true effect to vary across studies.77 otherwise related outcomes to the standard univariate In the one-stage models, we will include study-specific approach where we apply a separate model to analyse intercepts to quantify and account for between-study vari- each outcome. Multivariate meta-analysis allows for the ation in baseline risk. We will use random slopes to allow estimation of joint probabilities across multiple outcomes the relation between certain cofactors and the risk of CZS and accounts for cross-study and within-study correla- to vary across populations. tion between related outcomes.82 84 Modelling several Combining absolute measures of effect, like the risk outcomes simultaneously improves the precision over difference, across studies may mask important differ- ences in the baseline risk.78 We will present estimates of univariate models by sharing information about hetero- the risk difference in a forest plot of study-level estimates geneity and the average effect of the treatment which may facilitate inference about the relation between different by copyright. without presenting a summary meta-analytic estimate. In both the one-stage and two-stage analyses, we will use log CZS-related outcomes82 85 86 (ie, vermian dysgenesis and binomial regression models to estimate the relative risk of ocular abnormalities). each binary outcome and will use log Poisson regression Multivariate model to combine estimates from fully and partially to estimate the relative risk if log binomial models fail to adjusted studies converge.79 80 In the two-stage models, we will assess the A number of longitudinal studies will not include the potential for non-linear relationships between continuous minimal sufficient set of confounders. Estimates from exposures (viral load) and covariates (eg, gestational age, partially adjusted studies (that are missing values for maternal age) by using the Akaike information criteria important confounders) will be combined with fully to compare restricted cubic splines with three knots to adjusted estimates in a one-stage multivariate meta-anal- exponential, quadratic and linear terms. In the one-stage ysis. The one-stage multivariate model allows us to borrow models, we will use generalised additive mixed models (GAMMs) to assess potential non-linearities as the GAMM information from partially adjusted studies with different random smoothing parameter addresses the bias/vari- sets of confounders while ensuring that we control for ance trade-off by penalising the added complexity from important confounders.82 85 non-linear terms while accounting for between-study vari- Special considerations for the meta-analysis of cohort studies with ation in non-linear effects.81 rare events Joint estimation of multiple nested or otherwise related outcomes Two-stage meta-analytic methods are based on large (multivariate meta-analysis) sample approximations and may be unsuitable in the Not all studies will have measured all primary or secondary context of CZS, which can be considered a rare event.87 88 outcomes of interest. For example, most studies will have Two-stage meta-analysis may be biased when small studies measured ventriculomegaly, but may not include values are included, the effect of an exposure is very large or the for intracranial calcification or ocular abnormalities.9 outcome is rare, all of which may affect this analysis.89 We This analysis is intended to increase the precision of esti- will highlight any instances when the two-stage meta-an- mates of the spectrum of CZS abnormalities. Studies that alytic estimates may be biased by the aforementioned do not include the measurement of a given outcome will issues and will limit our inference to one-stage anal- necessarily be excluded from univariate estimates of that yses in those cases. If we have a number of longitudinal outcome, but will be included in multivariate models that studies with zero events, we will focus our inference on estimate the joint probability of related outcomes. In the a one-stage approach to avoid reliance on large sample multivariate models, we will assume that the outcomes that approximations. Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 9 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access Assessment of study-level and participant-level heterogeneity compare the magnitude of the interaction effects across Separating within-study and between-study heterogeneity studies. The interaction between certain cofactors and is central to assessing participant-level heterogeneity and ZIKV exposure may not be consistent across studies. In to understanding the relative importance of different the first stage of the two-stage analysis, we will use the potential effect measure modifiers.50 We are only able likelihood ratio test (p<0.05) to assess the importance of to separate within-study and between-study heteroge- including interaction terms within each study. Individual neity across studies that include both levels of the effect cohort studies may not have the sample size needed to measure modifier of interest. The presence of clinical detect clinically important interactions between ZIKV and illness may be related to disease course through viral load important cofactors. We will also assess whether a certain or be a marker for the strength of the immune system’s interaction is consistent across studies, while not neces- response to infection. We will conduct a one-stage anal- sarily statistically significant within individual studies. ysis of longitudinal studies that include both symptomatic Meta-regression and subgroup analyses have limited and asymptomatic women to assess whether the risk of power to detect interactions and can only be used to CZS or of the most severe effects of congenital infection make inference about the relation between the exposure (miscarriage, fetal loss) differs for clinical and subclinical and study-level, average values of participant character- infections. Between-study heterogeneity is reflective of istics.89 92 Studies that are not willing or able to provide study-level differences, while within-study heterogeneity participant-level data may differ importantly from longi- may be indicative of clinically important differences. We tudinal studies whose data is included in the IPD-MA. will mean centre covariates included in the interaction We will apply subgroup analysis to a two-stage analysis terms at the study level to separate between-study and of effect estimates from studies included in the IPD-MA within-study heterogeneity in our one-stage meta-ana- and published estimates from studies that did not partic- lytic estimates of how prior or co-infection with alpha or ipate in the IPD-MA to assess whether study-level varia- flaviviruses or STORCH pathogens modifies the effect of tion in recruitment and enrolment criteria, exposure ZIKV infection.90 and outcome ascertainment and measurement of coin- Heterogeneity in effect estimates will arise from clini- fections and other cofactors are important sources of cally important differences between congenital infections heterogeneity in the pooled estimates. Some sources of or women (effect measure modification) and from study- heterogeneity (eg, vector density and feeding patterns; DENV serotype) may not be measured and should be by copyright. level differences in exposure and outcome ascertainment (measurement error). With IPD, we are able to jointly considered in sensitivity analyses. assess study-level and participant-level heterogeneity.52 We will incorporate participant-level interaction terms Objective 3 in a one-stage analysis that includes random intercepts Use information on the relative importance of different effect to account for unmeasured study-level factors. We will measure modifiers identified in Objective 2 to decompose the consider random slopes for certain covariates to allow for total effect of ZIKV infection during pregnancy on adverse fetal, between-study variation in covariate effects across studies. infant and child outcomes Given the difficulty in assessing the total df in mixed Some studies suggest that antibody-dependent enhance- models, we will apply bootstrapping to assess the approxi- ment related to concurrent or prior DENV infection or mate confidence intervals of the pooled interaction terms. Japanese encephalitis vaccination may modify the effect We will present the analysis of effect measure modifiers in of ZIKV infection on fetal development. Both the timing accordance with the revised STROBE guidelines.91 of exposure to DENV and DENV serotype may contribute Based on our review of research protocols for planned to regional differences in the strength of the relation or ongoing cohort studies, we expect to include data between ZIKV infection and CZS.28 32 If we find evidence from longitudinal studies with different enrolment in the literature that the effect measure modifier identi- criteria, exposure and outcome ascertainment, diag- fied in Objective 2 (eg, DENV) may affect the outcome nostic assays for prior-infections or coinfections and (eg, CZS), we will apply inverse probability of treatment measurement of important cofactors. We will include weighted-marginal structural models to decompose the measures of study-level sources of heterogeneity (eg, total effect of ZIKV on the outcome of interest into the diagnostic assay, outcome definitions) as covariates in the direct effects of ZIKV infection, the effect of ZIKV infec- one-stage regression to assess the variance explained by tion mediated by the posited effect measure modifier and these factors. We will perform a sensitivity analysis where the effect of the interaction between ZIKV and the effect we limit our inference to studies with similar inclusion measure modifier.93 94 criteria and exposure, cofactor and outcome ascertain- ment to reduce spurious cross-study heterogeneity. While Objective 4 two-stage analyses of interaction effects that fail to sepa- Develop and validate a risk prediction tool to inform decision rate between-study and within-study heterogeneity are making by pregnant women, couples planning a pregnancy and subject to ecological bias90 and our inference about the healthcare providers and/or resource mobilisation importance of interaction terms will primarily be derived We will fit one-stage logistic regression models with from one-stage analyses, we will use a two-stage analysis to random intercepts to account for differences in the 10 Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access baseline risk within each study. We will apply group Lasso O:E ratios and calibration slopes. We will apply random regression95 to identify the prognostic variables that effects meta-analysis to combine estimates of the discrim- predict progression to miscarriage, fetal loss and micro- ination and calibration of the kpredictive models. We will cephaly. Lasso regression is implemented using L1-penal- assess model calibration and discrimination and choose ised estimation. The application of group Lasso ensures the model with the best properties.99 103 We will use boot- that the algorithm selects all levels of categorical variables strap validation to evaluate model optimism and will by treating corresponding dummy variables as a group follow the TRIPOD statement guidelines for reporting instead of allowing the model to only select certain levels the final prediction models.104 of categorical variables.96 97 The L-1 penalty term allows for concurrent consideration of predictors and shrinkage, Step 4. Quantitative bias analysis which facilitates variable selection in the context of high Given the complexity and level of measurement error, we dimensional data.98 We will standardise included vari- will conduct a quantitative bias analysis under a Bayesian ables so that all variables use the same scale. We will adopt framework where we use a combination of expert cross-validation on the study level to select the optimal opinion, laboratory EQA and external and internal tuning parameter (λ) and will adopt restricted maximum assessment of the relative accuracy of diagnostic assays likelihood (REML) to estimate the variance-covariance and other methods for cofactor and outcome ascertain- matrix of the study-level random effects. ment to inform the prior distributions of bias parame- Not all studies will have the resources to implement the ters. Where possible, we will apply frequentist methods most accurate and reliable ZIKV-related diagnostic tools. for quantitative bias analysis105 as a sensitivity analysis and As part of the data synthesis, we will identify the exposure will use the GRADE criteria106 to compare the quality of and cofactor diagnostic methods that are most commonly the evidence from Bayesian and frequentist models, with applied. As a sensitivity analysis, we will use these diag- a focus on how imprecision, inconsistency, indirectness, nostic methods to develop a risk prediction model so that magnitude of effect differ in the Bayesian and frequen- the model can be applied in regular clinical practice. tist approaches to addressing the myriad sources of bias expected to affect these analyses. Development and external validation of the prediction model We will apply internal-external cross-validation where we rotate the cohort that is used for external validation to Selection bias by copyright. improve the model’s predictive ability.99 For example, Studies or surveillance systems that only recruit or given k cohort studies, we will use k-1 cohort studies to test symptomatic pregnant women or studies that only develop the prediction model and will validate model enrolled pregnant women who tested positive for ZIKV performance by applying the prediction model to a cohort infection are affected by selection bias because selection that was not used to develop the prediction model. Inter- into the study is associated with the exposure.63 This situ- nal-external cross-validation allows for the use of all avail- ation is similar to the inclusion of a single treatment arm able data for model development and validation which in a randomised controlled trial. Although data from improves model performance and generalisability.100 studies that only enrol pregnant women who test positive for ZIKV cannot directly inform estimates of the causal Evaluation of model performance effect of ZIKV, these data can inform the development We will generate receiver operating characteristic (ROC) of prediction models because they contain information curves101 102 in the cohort that was not used to develop on the prognosis of ZIKV positive women. Longitudinal the prediction model to estimate the model’s true-posi- studies that restrict enrolment to ZIKV positive pregnant tive (sensitivity) versus false-positive (1-specificity) rate women may also increase the precision of relative treat- for each binary outcome. These curves will then be ment effects by providing more events within ZIKV-ex- summarised using the area under the ROC curve (AUC). posed pregnant women. Longitudinal studies have In some instances, the pregnant woman or couple plan- reported that women who perceive their infants as unaf- ning a pregnancy may prefer a more sensitive rather than fected by CZS are less likely to participate in follow-up. a more specific model. We will present a range of cut-off We will consider matching on the propensity score or values that maximise sensitivity, specificity or both sensi- the use of inverse probability of censoring weights107 tivity and specificity to facilitate decision making by preg- and prognostic score analysis108 to account for measured nant women or couples planning a pregnancy. We will determinants of differential loss to follow-up in the aeti- assess the extent to which these thresholds yield consis- ological and prognostic models, respectively. Selection tent sensitivity and specificity across different regions and bias can be induced when we inappropriately adjust for populations. We will use calibration plots to compare the a time-varying confounder affected by prior exposure observed and predicted probability of the outcome of (a confounder that also acts to mediate the relation interest within risk quintiles and summarise these plots between ZIKV infection and adverse fetal, infant or child by calculating the total ratio of observed versus expected outcomes). We will use G-computation methods to appro- events (O:E ratio) and the calibration slope. Internal-ex- priately adjust for time-dependent confounders affected ternal cross-validation of k studies will result in kAUCs, by prior exposure.109 Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 11 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access Confounding bias impute missing participant-level data in each study sepa- We will adjust for confounders that are unlikely to rately and use multivariate meta-analysis to combine data mediate the causal relation between infection during across studies that have and have not measured important pregnancy and adverse infant outcomes (table 1). We will host-level and environmental-level cofactors. estimate each participant’s likelihood of being infected during pregnancy, conditional on the study group and Publication bias important confounders, to identify possible violations of IPD-MA may have a lower risk of publication bias than the positivity assumption. In sensitivity analyses, we will AD-MA because they include data from unpublished apply propensity score matching within studies to ensure studies.114 We have tried to ensure that the ZIKV IPD that important confounders are adequately balanced Consortium includes representatives from all of the across exposure groups. Despite the prospective, collab- academic and government institutions responsible for orative development of a standardised research protocol planned or ongoing ZIKV-related longitudinal studies for ZIKV cohort studies of pregnant women, confounders of pregnant women and their infants. We expect that and effect measure modifiers may be defined differently Consortium members will identify most ZIKV longitu- across studies or not measured in certain studies. We will dinal studies and active surveillance systems of preg- develop a detailed codebook that reflects the heteroge- nant women and their infants, regardless of publication neity in confounder definitions and report on this hetero- status, and we will conduct a systematic review to identify geneity in our analyses. additional longitudinal studies and active surveillance systems. The degree of publication bias will be assessed Measurement (ie, detection, misclassification) bias visually by reviewing the asymmetry of study-level esti- Despite efforts to harmonise case definitions across mates from published and unpublished studies using studies with the prospective development of a stan- funnel plots that compare log RR to the corresponding dardised protocol for cohorts of pregnant women and studies’ sample size.117 their infants,60 the case definitions, diagnostic tools and We will convene a group of patient advocates to eval- algorithms used to ascertain ZIKV infection, cofactors and uate the ethical implications and utility of the risk strati- CZS-associated outcomes vary across studies.110 The liter- fication tool. ature on the accuracy of ZIKV-related and DENV-related assays is evolving rapidly.30 111 Prior to initiating our anal- by copyright. yses, we will synthesise the current evidence on the sensi- Discussion tivity and specificity of different assays for ZIKV diagnosis, The application of IPD-MA to an emerging pathogen for the assessment of concurrent or prior DENV infections presents an important opportunity to harness global and for estimating the time of infection, among other collaboration to inform the development of recommen- relevant factors. The WHO standardised protocol for dations for pregnant women, couples planning a preg- ZIKV-related cohorts of pregnant women includes WHO nancy and public health practitioners. While IPD-MA recommendations on the screening and assessment of offers real benefits compared with AD-MA or to the infer- neonates and infants with intrauterine ZIKV exposure;112 ence possible with individual cohort studies, the ability we will compare study-level outcome definitions with the of IPD-MA to inform public health practice is directly standardised WHO definitions. The role of heterogeneity related to the quality of the exposure, cofactor and related to case definitions and diagnostic tools will be outcome ascertainment in the original cohort studies. explored through both frequentist and Bayesian methods. Statistical methods for IPD-MA were developed in the In the frequentist approach, we will: (1) include categor- context of clinical research and randomised control trials. ical or continuous markers of sensitivity and specificity of These methods needs to be adapted to account for the diagnostic tools as study-level covariates in the one-stage myriad sources of uncertainty and bias that affect observa- analyses and (2) apply diagnostic tool specific-subgroup tional research, especially for field epidemiology studies analysis to both the one-stage and two-stage meta-analysis conducted as part of the research response to unknown of effect measures from different studies. In the Bayesian or emerging pathogens. approach, we will use a combination of expert opinion Historically, arboviruses and other neglected tropical and data from external and internal validation studies to diseases have been understudied because the burden inform the probability distributions of bias parameters.113 of disease falls on under resourced populations in the Global South.118 In the context of ZIKV, the unequal Missing data distribution of risk is coupled with inequities in access to Missing data at the study level, as when confounders are preventative measures like modern contraception and to not measured in certain studies, is a well-known chal- critical clinical and therapeutic care for infants affected lenge of IPD-MA114 115 and a likely source of residual by microcephaly and ZIKV-related neurological disor- confounding. In keeping with current recommendations ders. Each case of microcephaly is associated with a loss for addressing missingness in IPD-MA, we will apply new of 29.95 disability adjusted life years (DALYs) and treat- methods for multilevel multiple imputation to account ment costs ranging from US$91K to US$1 million.119 To for missing values.116 As a sensitivity analysis, we will put these figures into perspective, the yearly per capita 12 Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access income in Pernambuco, the Brazilian state with one of Ethics and dissemination the highest burdens of CZS, is US$3471.120 This IPD-MA protocol has been deemed exempt from There is no vaccine for ZIKV and the only treatment ethical review by the WHO Ethics Review Committee is supportive.58 There have been numerous calls for data and the Emory University Institutional Review Board. sharing121 122 and cooperation between governments Individual longitudinal studies will provide documenta- and academic institutions,54 123 and public and private tion of ethics review prior to sharing their deidentified, charities have pledged significant financial support to participant-level data. The WHO has developed guid- improve our understanding of ZIKV epidemiology and ance for data sharing in public health emergencies or in to develop a vaccine or small molecule prophylaxis to the context of emerging pathogens.125 Sharing deiden- decrease the risk of infection. In the wake of the Ebola tified data for IPD-MA is generally considered exempt epidemic, the global response to ZIKV has been charac- from ethical review if the objectives of the IPD-MA are terised by unprecedented levels of international cooper- in keeping with the objectives of the original studies.126 ation. In the absence of a ZIKV vaccine or prophylaxis, Individual research studies and consortia will secure addi- international leaders in ZIKV research have formed the tional ethics review and/or legal guidance on the sharing ZIKV IPD Consortium to identify, collect and synthesise of deidentified, subject-level data as needed. The results IPD from longitudinal studies of pregnant women that of this analysis will be published under the ZIKV IPD measure ZIKV infection during pregnancy and fetal, Consortium name and will include a list of the names of infant and child outcomes. These data will be used to key investigators from each study that contributed data quantify the absolute risk of ZIKV-related pregnancy for that analysis and researchers who contributed to the complications with the goal of aiding women and their analysis or writing at the end of the publication. Findings families in making difficult reproductive decisions and from the proposed analysis will be shared via national and with helping public health systems prevent and quantify international conferences; existing platforms for dissem- the burden of congenital Zika infection. ination of ZIKV-related research (eg, The Global Health Network) and through publication in open access, Challenges of developing and conducting an individual peer-reviewed journals. participant data-meta-analysis in the context of an emerging Author affiliations pathogen 1 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, by copyright. Ideally, researchers prespecify confounders, effect Singapore measure modifiers and plans for subgroup or sensi- 2 Centre for Mathematical Sciences, University of Plymouth, Plymouth, UK 3 tivity analyses in their research protocol. In the context Department of Social Medicine, Universidade Federal de Pernambuco, Recife, Brazil of Zika, our understanding of the virus is changing so 4 Health Emergencies Programme, Organisation mondiale de la Sante, Geneve, rapidly that analysis plans may change significantly Switzerland despite our best efforts to review the latest evidence on 5 Department of Collective Health, Institute Aggeu Magalhães (CPqAM), Oswaldo transmission, immunological response, diagnostic assays, Cruz Foundation, Recife, Brazil 6 vector biology and basic ZIKV epidemiology. Our ability Institute of Tropical Pathology and Public Health, Federal University of Goias, Goiânia, Brazil to appropriately account for measurement error will play 7 Department of Biochemistry and Immunology, Federal University of Minas Gerais, a critical role in the accuracy of estimates for the risk of Belo Horizonte, Minas Gerais, Brazil CZS and other adverse fetal, infant and child outcomes. 8 Department of Medical Microbiology, University Medical Center Groningen, This is one of the first instances where an IPD-MA has Groningen, The Netherlands 9 been used to address public health concerns in the Department of Social Medicine, University of São Paulo, São Paulo, Brazil 10 Reference Center for Neurodevelopment, Assistance, and Rehabilitation of context of an emerging pathogen. We expect that best Children, State Department of Health of Maranhão, Sao Luís, Brazil practices and lessons learnt from this IPD-MA can be 11 Department of Pediatrics, University Hospital Vall d’Hebron, Barcelona, Spain used to facilitate the formation of research collabora- 12 SOSECALI C. Ltda, Guayaquil, Ecuador 13 tions to streamline the public health response to future Department of Epidemiology, University of São Paulo, São Paulo, Brazil 14 epidemics. Department of Infectious Diseases, Section Clinical Tropical Medicine, UniversitatsKlinikum Heidelberg, Heidelberg, Germany 15 Evidence and Intelligence for Action in Health, Pan American Health Organization, Patient and public involvement Washington, District of Columbia, USA 16 In keeping with guidelines for public involvement in Department of Pediatrics, D’Or Institute for Research & Education, Rio de Janeiro, research,124 knowledge users (ie, women of reproduc- Brazil 17 Department of Obstetrics and Gynecology, Centre Hospitalier de l’Ouest Guyanais, tive age and their families, clinicians) will be consulted Saint-Laurent du Maroni, French Guiana at each stage of this research. The research question and 18 Hospital Materno Infantil de Goiânia, Goiânia State Health Secretary, Goiás, Brazil protocol were designed with feedback from clinicians who 19 Communicable Diseases and Environmental Determinants of Health Department, treat pregnant women in ZIKV-endemic areas and infants Pan American Health Organization, Washington, District of Columbia, USA 20 Department of Pediatrics, FMJ, São Paulo, Brazil and children affected by CZS. Focus groups that include 21 Faculdade de Medicina de Sao Jose do Rio Preto, Department of Dermatologic women of reproductive age in ZIKV-endemic areas will be Diseases, São José do Rio Preto, Brazil used to evaluate the ethical implications and utility of the 22 Windward Islands Research and Education Foundation, St. George’s University, risk stratification tool in three countries. True Blue Point, Grenada Wilder-Smith A, et al. BMJ Open 2019;9:e026092. doi:10.1136/bmjopen-2018-026092 13 BMJ Open: first published as 10.1136/bmjopen-2018-026092 on 18 June 2019. Downloaded from http://bmjopen.bmj.com/ on July 12, 2022 at Univesity Autonomous of Barcelona. Protected Open access 23 Department of Public Health, Universidade Federal do Maranhão – São Luís, São Marcia Mussi-Pinhata; Christina Nelson; Karin Nielsen; Denise M. Oliani; Renata Luís, Brazil Rabello; Marizelia Ribeiro; Barry Rockx; Laura C. Rodrigues; Silvia Salgado; Katia 24 Silveira; Elena Sulleiro; Van Tong; Diana Valencia; Wayner Vieira de Souza; Luis Department of Neonatology, Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil Angel Villar Centeno; Andrea Zin. 25 Facultad de Salud, Universidad Industrial de Santander, Bucaramanga, Colombia Contributors NB, CBH, TJ, NL, LM, JS and LR contributed to the initial conception 26 Faculty of Medical Sciences, University of Pernambuco, Recife, Brazil of the study. AB, TD, PG, NL, LM and YW made substantial contributions to the 27 Reproductive Health and Research, World Health Organization, Geneva, statistical methodology proposed for the IPD-MA. LM wrote the first draft of the Switzerland protocol. AW-S, YW, TVBA, MV, CMTM, MDT, MT, AT, PS, JPS, AS-A, CSS, AMS, NSC, 28 Hubert Department of Global Health, Emory University, Atlanta, Georgia, USA KDR, LR, APB, LP, LEPR, FP, SP, MN, TN, MEM, IM, MCMM, DBMF, LM, CM, NL, ZL, 29 Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland ADL, MK, CK, EJ, TJ, CH, PG, PG, JG, ACFD, VE, GD, TPAD, MLC, PB, NB, EB, PB, FB, 30 McGill University Health Centre, McGill University, Montréal, Canada SB, AB, VAS, RAAX, AAC and JA provided substantial revisions to the protocol. All 31 Pediatric Infectious Diseases, Stanford Hospital, Palo Alto, California, USA authors approved the final version of the protocol. 32 Department of Virology, Erasmus Medical Center, Rotterdam, The Netherlands Funding The development of the IPD-MA protocol was supported by a Wellcome 33 Department of Reproductive Health and Research, World Health Organization, Trust grant to the WHO Department of Reproductive Health and Research Human Geneva, Switzerland Reproduction Programme, grant number 206532/Z/17/Z. 34 Department of Infectious Diseases, Hospital Federal dos Servidores do Estado, Rio Competing interests None declared. de Janeiro, Brazil 35 Instituto de Puericultura e Pediatria Martagão Gesteira, Universidade Federal do Patient consent for publication Not required. Rio de Janeiro, Rio de Janeiro, Brazil Provenance and peer review Not commissioned; externally peer reviewed. 36 Statistics, University of British Columbia, British Columbia, Vancouver, Canada 37 Open access This is an open access article distributed in accordance with the INSERM CIC1410 Clinical Epidemiology, CHU La Réunion, Saint Pierre, Réunion 38 Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits UM 134 PIMIT (CNRS 9192, INSERM U1187, IRD 249, Université de la Réunion), others to copy, redistribute, remix, transform and build upon this work for any Universite de la Reunion, Sainte Clotilde, Réunion 39 purpose, provided the original work is properly cited, a link to the licence is given, Children’s Hospital Juvencio Matos, São Luís, Brazil and indication of whether changes were made. See: https://​creativecommons.​org/​ 40 Sustainable Development and Environmental Health, Pan American Health licenses/​by/​4.​0/. 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