Nov 21, 2023
Burden of RSV in Italian adults: Protocol for a systematic review and meta-analysis
- 1IRCCS Ospedale Policlinico San Martino;
- 2Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
Protocol Citation: Alexander Domnich, Giovanna Elisa Calabrò 2023. Burden of RSV in Italian adults: Protocol for a systematic review and meta-analysis. protocols.io https://dx.doi.org/10.17504/protocols.io.5qpvo32odv4o/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: November 21, 2023
Last Modified: November 21, 2023
Protocol Integer ID: 91240
Abstract
Globally, respiratory syncytial virus (RSV) is a leading cause of respiratory infections and is responsible for a significant socioeconomic burden in all age groups, including adults. To date, no review systematically appraised the burden of RSV in Italian adults. Understanding country-specific burden of disease is a key driver for policy decisions on the introduction of new vaccines. In fact, two vaccines have been recently authorized to prevent lower respiratory tract disease caused by RSV in adults. In this protocol for a systematic review, we aim to collect and analyze data on the clinical burden of RSV in Italian adults with the goal of informing and supporting National and local decision makers on the planification and implementation of future vaccination strategies.
Attachments
Introduction
Introduction
Together with seasonal influenza, respiratory syncytial virus (RSV) is a
leading cause of respiratory infections and is responsible for a significant
socioeconomic burden in all age groups, especially at the extremes of age [McLaughlin,
2022; Rafferty, 2022]. Indeed, a recent modelling study [Osei-Yeboah, 2023] has
estimated that on average, a total of 158,229 RSV-associated hospitalizations among
European adults occur annually and 92% of these concern older adults aged ≥ 65
years. Contrary to young children, in the last 20 years mortality attributable
to RSV increased in both working-age and older adults [Du, 2023].
Several systematic reviews [Shi, 2020; Tin Tin Htar, 2020; Nguyen-Van-Tam,
2022; Shi, 2022; Maggi, 2022; Li, 2023] have investigated global epidemiology
and burden of RSV in (older) adults. These reviews have confirmed significant
RSV attack rates, hospitalization, mortality and case-fatality rates [Shi,
2020; Tin Tin Htar, 2020; Nguyen-Van-Tam, 2022; Shi, 2022; Maggi, 2022; Li,
2023], which seem similar to seasonal influenza [Maggi, 2022], and noted a
substantial case under-ascertainment [Li, 2023]. Moreover, there was a large
between-country variation in burden estimates [Tin Tin Htar, 2020], which is
driven by numerous factors, from climatic conditions [Haynes, 2013] to case
definitions and efficiency of the surveillance system in place [Staadegaard,
2021]. Notably, the available systematic reviews [Shi, 2020; Tin Tin Htar,
2020; Nguyen-Van-Tam, 2022; Shi, 2022; Maggi, 2022; Li, 2023] have identified
only up to six primary studies conducted in Italy.
Two vaccines have been recently authorized to prevent lower respiratory
tract disease (LRTD) caused by RSV in adults aged ≥ 60 years [Kotton, 2023].
This age indication will be likely extended to younger adults in the upcoming
years. In the United States (US), a single dose of RSV vaccine is recommended
to adults ≥ 60 years, as a part of shared clinical decision-making between
patient and healthcare provider [CDC, 2023]. In the United Kingdom (UK), RSV
vaccination is recommended for older adults aged ≥ 75 years, being the most
cost-effective option [United Kingdom Department of Health & Social Care,
2023]. By contrast, as of November 2023, no recommendations have been issued in
Italy.
Understanding country-specific burden of disease (BoD) is a key driver
for policy decisions on the introduction of new vaccines [Levine, 1997]. A
systematic appraisal of the burden of RSV enables policy makers, health
professionals and other relevant stakeholders to make informed decisions
regarding the recently available vaccines. In this regard, systematic reviews
on the frequency of different BoD indicators are important in the description
of the spatiotemporal distribution and the variation between population
subgroups potentially targeted by the novel preventive measures [Munn 2018;
Barker, 2021]. Country-specific BoD indicators are also essential for all types
of pharmacoeconomic models.
In Italy, a recent systematic review [Boccalini, 2023] has assessed RSV
BoD in pediatric outpatients. By including six studies, the authors found that
18–41% of children with respiratory infections were positive for RSV.
Conversely, no review systematically appraised the burden of RSV in Italian
adults. Indeed, RSV epidemiology is highly age-dependent, which hinders
transferability of pediatric estimates to other target population groups.
Furthermore, as we mentioned earlier, the available global reviews on (older)
adults [Shi, 2020; Tin Tin Htar, 2020; Nguyen-Van-Tam, 2022; Shi, 2022; Maggi,
2022; Li, 2023] were able to identify only a limited number of Italian studies.
In this systematic review, we aim to comprehensively collect and analyze
available data on the BoD of RSV in Italian adults in both primary care and
hospital settings with the ultimate goal of informing and supporting National
and local decision makers on the planification and implementation of
vaccination strategies.
Methods
Reporting
standards
PRISMA (preferred reporting items for systematic reviews and
meta-analyses) statement [Page, 2021] will be adopted as a reporting standard.
Methodological guidance for systematic reviews of observational epidemiological
studies reporting prevalence and cumulative incidence data developed by the
Joanna Briggs Institute (JBI) [Zachary, 2015] will be also consulted.
Eligibility
criteria
All types of observational studies (e.g., surveillance, cross-sectional,
cohort, case-series) and published in any modality (i.e., peer-reviewed
article, preprint, conference abstract, official report and other forms of grey
literature) will be eligible. The CoCoPop (condition, context, and population)
approach [Munn, 2015] will be used to formulate the inclusion criteria. In
particular, the condition of interest will be RSV infection detected by any
laboratory technique, including reverse-transcription polymerase chain reaction
(RT-PCR), cell culture, immunofluorescence assay (IFA) and rapid antigen
detection test (RADT). Moreover, RSV-specific International Statistical Classification
of Diseases and Related Health Problems (ICD) diagnosis codes will be also
considered a good proxy for the true RSV infection. Indeed, specificity of the
RSV-specific codes is 99.6–99.8% [Pisesky, 2016; Cai, 2020].
For the context, we will consider studies conducted in Italy, in any
setting (outpatient, inpatient or mixed) and calendar period. For this latter,
it is important to distinguish between year-around studies and those conducted
during a typical RSV season, in which the probability of RSV detection is much
higher [Rozenbaum, 2023]. We will define RSV epidemic season as a period
between October and April [Hamid, 2023].
Population will consist of adults defined as individuals aged ≥ 14/18 years. When possible, we will
consider estimates for different age subgroups (e.g., working-age and older
adults) reported by single studies. Any clinical entity [e.g., influenza-like
illness (ILI), acute respiratory infection (ARI), severe ARI (SARI)] that
triggers swab collection will be eligible.
The following will be the exclusion criteria: (i) modeling,
pharmacoeconomic and similar studies with no original data; (ii) records with
insufficient data on RSV; (ii) studies on general population with no separate
data for adults; (iii) multi-country studies with no separate information for
Italy; (iv) redundant publications.
Study
endpoints
RSV attack rate (cumulative incidence) will be defined as the occurrence
of laboratory-confirmed RSV detections in a population (symptomatic/medically
attended, asymptomatic or both) in a specific period (e.g., RSV season). RSV
prevalence (overall, by subtype and genotype) will be defined as proportion of
RSV detections to the total number of subjects tested. Prevalence of
co-detections will be described as number of samples tested positive for both
RSV and any other respiratory pathogen to the total number of samples tested
positive for RSV. Case complication rate will be defined as proportion of
subjects tested positive for RSV and who developed at least one complication,
such as pneumonia, exacerbation of chronic obstructive pulmonary disease,
asthma, or congestive heart failure. As for drug use indicators, we will consider
frequency of drug prescriptions among subjects who was diagnosed with RSV. For
what concerns inpatient outcomes, crude hospitalization (per 100,000), case
hospitalization (i.e., proportion of RSV-positive individuals who were hospitalized)
rates, length of stay, frequency of admission to intensive care units will be
of interest. Analogously, crude, in-hospital, 30-day mortality and
case-fatality rates will be eligible. For these indicators, we will consider
only RSV-specific codes for RSV pneumonia (ICD-9-CM: 480.1; ICD-10-CM: J12.1),
acute bronchiolitis due to RSV (ICD-9-CM: 466.11; ICD-10-CM: J21.0), acute
bronchitis due to RSV (ICD-10-CM: J20.5), and RSV as the cause of diseases
classified elsewhere (ICD-9-CM: 079.6; ICD-10-CM: B97.4).
When possible, all study endpoints will be described overall, by age
group (working-age and older adults) and RSV season. Additional not
prespecified endpoints will be also eligible for exploratory purposes.
Search
strategy
The automatic search will be performed in the
following: PubMed/Medline, Biological Abstracts, Global Health through Ovid and
Scopus. In order to increase sensitivity, the number of selection criteria will
be minimized to the condition and population of interest and no filters or
other restrictions (e.g., language or publication year) will be applied. The
search following script, which will be adapted to each citation database, will
be used: (“Respiratory Syncytial Viruses”[MeSH Terms] OR "Respiratory
Syncytial Virus, Human"[MeSH Terms] OR “Respiratory Syncytial Virus
Infections” [MeSH Terms] OR “respiratory syncytial” OR “RSV”) AND (“Adult”
[MeSH Terms] OR “Aging”[MeSH Terms] OR “Men”[MeSH Terms] OR “Women”[MeSH Terms]
OR “Retirement”[MeSH Terms] OR “Long-term care”[MeSH Terms] OR “Nursing
care”[MeSH Terms] OR “Palliative care”[MeSH Terms] OR pension* OR retire* OR
adult* OR aged OR elderly OR senior* OR geriatric* OR nursing home*) AND
(“Italy”[MeSH Terms] OR Italy OR Italian*).
We will then perform a manual search through several
two modalities. First, the reference lists of the available systematic reviews
will be checked. Second, a backward cross-reference checking of the included
studies will be carried out. Third, a forward citation search by using Google
Scholar (https://scholar.google.com/) will be performed, as this search engine
is better suited for identifying grey literature sources [Haddaway, 2015].
Fourth, periodic reports of the Italian surveillance reports on influenza and
other respiratory viruses (https://respivirnet.iss.it) will be examined.
Finally, we will screen abstract books and proceedings of some relevant
conferences, including ECCMID (European Society of Clinical Microbiology and
Infectious Diseases), ESWI (European Scientific Working Group on Influenza) and
ReSViNET.
Study
selection
Results of the automatic search will be merged into a
single spreadsheet and duplicates will be removed in a semi-automatic modality.
The resulting list of unique records will undergo the process of screening by
assessing titles and/or abstracts and clearly irrelevant citations will be
discarded. Full texts of potentially pertinent publications records will be
then downloaded and assessed for the eligibility criteria described earlier. Selection will be finalized by performing
the manual search, as described above. The entire process of study selection will
be performed by two reviewers, each working independently, and eventual
disagreements will be solved by consensus.
Data
extraction and coding
The following data will be extracted into a
spreadsheet: (i) full citation record; (ii) location (region); (iii) period;
(iv) design; (v) setting; (vi) population; (vii) sample size; (viii) funding
source; (ix) definition of the clinical entity that triggered swab collection;
(x) methods used for RSV case ascertainment; (xi) numerators and denominators
used to compute the endpoints of interest described above. On the basis of
period, studies will be dichotomized on whether they overlapped with the
COVID-19 pandemic, which had a significant impact on circulation of RSV and
many other respiratory viruses. In particular, the northern hemisphere winter
season 2020/21 was characterized by the absence of very limited circulation of
RSV [Hamid, 2023; Boccalini, 2023; Gomez, 2021]. Estimates for that season will
be extracted and reported, but not included in the quantitative synthesis.
Starting from the 2021/22 season, RSV returned to the epidemiological scene
[Hamid, 2023] and therefore estimates from 2021/22 will be fully considered.
Multi-season studies that reported separate seasonal estimates will be
considered as distinct estimates [Bergeri, 2022]. On the basis of sample size,
studies will be median split. Regions will be categorized into three macro-areas
of North (Aosta Valley, Liguria, Lombardy, Piedmont, Emilia-Romagna,
Friuli-Venezia Giulia, Trentino-South Tyrol, and Veneto), Center (Lazio,
Marche, Tuscany, and Umbria), and South (Abruzzo, Apulia, Basilicata, Calabria,
Campania, Molise, Sicily, and Sardinia).
Missing data on relevant numerators and/or
denominators will be handled as follows. First, the corresponding author will
be contacted by email for clarification. In case of no reply, these data will
be imputed from the available percentages and/or by extracting data from
figures using WebPlotDigitizer v.4.6 (https://automeris.io/WebPlotDigitizer).
Data will be extracted by AD and then validated by GEC.
Critical
appraisal
The JBI checklist for prevalence/incidence studies
[Zachary, 2015] will be used to assess quality of the included studies.
Critical appraisal will be performed independently by two reviewers and
eventual conflicts will be solved by consensus.
Data
synthesis
Tabulated data will be first appraised qualitatively and
by visualizing forest plots. For quantitative synthesis, a proportional
meta-analysis will be undertaken according to the available recommendations
[Zachary, 2015; Barker, 2021]. As heterogeneity is expected to be high, random-effects
models with double arcsine transformation to stabilize variances will be used.
Pooled estimates will be expressed as proportions with both 95% Clopper-Pearson
exact confidence intervals (CIs) and 95% prediction intervals (PIs).
Heterogeneity will be quantified by means of the I2statistic. Notably, high I2 values do not necessarily mean
that data are inconsistent since true heterogeneity is expected in prevalence
estimates due to spatiotemporal differences [Barker, 2021]. As recommended,
publication bias will be not formally assessed (i.e., by funnel plots or
statistical tests), since there is no consensus about what a positive result in
a meta-analysis of proportions is [Barker, 2021].
To investigate the sources of heterogeneity across
studies, both subgroup and meta-regression analyses will be performed. In
particular, the subgroup analysis will be performed by age group (working-age
and older adults), setting (outpatient, inpatient and mixed) and study period
in relation to the COVID-19 pandemic (before and after the 2020/21 season). The
meta-regression modeling will be then conducted to examine the influence of
study characteristics on the RSV-related endpoints. This latter will be
performed only when at least 10 estimates are available [The Cochrane
Collaboration, 2011].
Meta-analysis will be performed in R (R Foundation for
Statistical Computing; Vienna, Austria) package “Meta” v. 6.5-0.
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