DOI: 10.5061/dryad.tdz08kq30
title: Global burden of non-tuberculous mycobacteria in the cystic fibrosis population: A systematic review and meta-analysis

description: Background: People living with cystic fibrosis have an increased
 risk of lung infection with non-tuberculous mycobacteria (NTM), which is
 reportedly increasing. We conducted a systematic review of the literature
 to estimate the burden (prevalence and incidence) of non-tuberculous
 mycobacteria in the cystic fibrosis population. 
 Methods: Electronic databases, registries, and grey literature
 sources were searched for cohort and cross-sectional studies reporting
 epidemiological measures (incidence and prevalence) of NTM infection or
 NTM pulmonary disease (NTM-PD) in cystic fibrosis. The last search was
 conducted in September 2021; we included reports since database creation
 and registry reports published since 2010. The methodological quality of
 studies was appraised with the Joanna Briggs Institute tool. A
 random-effects meta-analysis was conducted to summarize the prevalence of
 NTM infection, and the remaining results are presented in a narrative
 synthesis.  Results: Ninety-five studies were included in this
 review. All 95 studies reported on NTM infection, and 14 of these also
 reported on NTM-PD. The pooled estimate for the point prevalence of NTM
 infection was 7.9% (CI 95%, 5.1–12.0%). In meta-regression, sample size
 and geographical location of the study modified the estimate. Longitudinal
 analysis of registry reports showed an increasing trend in NTM infection
 prevalence between 2010 and 2019.  Conclusions: The
 overall prevalence of NTM infection in CF is 7.9% and is increasing over
 time based on international registry reports. Future studies should report
 screening frequency, microbial identification methods, and incidence rates
 of progression from NTM infection to pulmonary disease.
description: <strong>Review
 question</strong> We designed our review question based on
 population, condition, outcome (epidemiological measure) and study design,
 as recommended by current guidelines. Briefly, we screened for
 cross-sectional or cohort studies reported in English including people
 with CF (population) and evaluating NTM infection or NTM-PD (condition).
 NTM infection was defined as isolation of any NTM on at least one occasion
 per patient; the criteria for NTM-PD were specified in each study.
 Reporting of at least one epidemiologic measure among incidence rate,
 incidence proportion, point prevalence, or period prevalence was required
 for inclusion. The full criteria are described in Supplementary Table 1.
 The review protocol was registered to the International
 Prospective Register of Systematic Reviews, PROSPERO (CRD42020200418) in July 2020. In October 2020,
 before the abstract screening, we updated the grey literature sources and
 screening procedures.
 <strong>Literature
 search</strong> EMBASE and MEDLINE were searched in September
 2020 using the criteria specified in Supplementary Methods 1; an updated
 search was conducted in September 2021. We manually reviewed the
 conference proceedings from relevant research meetings between 2010 and
 2020 (North American Cystic Fibrosis, European Cystic Fibrosis Society,
 American Thoracic Society, and the Infectious Diseases Society of America
 conferences). Also, we performed forward and backward searches for highly
 cited references in Web of Science (listed in Supplementary Table 2) using
 Google Scholar and Web of Science. Finally, the United States of America
 (CF Foundation), Canadian (CF Canada), European (European CF Society),
 Australian, and Brazilian registry reports published between 2010 and 2021
 were included. <strong>Screening and data
 extraction</strong> All records were retrieved and exported
 in Research Information Systems format. Initial manual deduplication evaluated
 Author, Title, and Year of publication. Then, we performed automated
 deduplication using the SRA De-Duplicator software and Covidence.
 Screening of reports and full-text manuscripts, data extraction, and risk
 of bias assessment was conducted independently by two reviewers (M.P. and
 M.A.); discrepancies were solved by consensus or by a third reviewer
 (B.Q.). Epidemiological measures of interest reported in each study were
 included for analysis. Abstract screening evaluated language, study type,
 the inclusion of CF population, and reporting of any measures of interest.
 Full-text screening evaluated all eligibility criteria defined in
 Supplementary Table 1. For unretrievable reports, we requested access to
 unpublished full manuscripts from authors via email on at least two
 separate occasions. The Joana Briggs Institute tool was used to assess
 methodological and reporting quality. Overall low risk of bias was defined
 as low risk in the assessments of the sampling frame, sample size,
 population description, and statistical methods. High risk was determined
 by a high-risk assessment in any of the following: sampling frame,
 sampling scheme, sampling size, population description, identification
 methods, or statistical calculation. Data extraction was based on a
 pre-specified data dictionary piloted with 10 studies (Supplementary Table
 2). For period prevalence, point prevalence, and incidence proportion, we
 extracted proportions, the number of cases, and the sample size. We did
 not impute any missing data. In studies with unclear years of data
 collection, we assumed that data was obtained from the year before
 publication. The body of evidence was not evaluated for certainty given
 the lack of adapted tools for single-proportion
 measures. <strong>Data
 analysis</strong> Data were analyzed with the meta and metafor
 packages in R studio and R version 4.1.1. Risk of bias plots were produced
 with the robvis and ggplot2 packages, and tables with the flextable
 package. We pre-specified the use of random-effects models based on
 expected heterogeneity by study region and dates. To model proportion
 data, we used generalized linear models with LOGIT transformation. Point
 and annual prevalence of NTM infection were summarized together in the
 meta-analysis because they contain comparable time frames of evaluation (a
 year or less). The remaining epidemiologic measures including period
 prevalence of NTM infection, incidence of NTM infection, prevalence (point
 or period) of NTM-PD, and incidence of NTM-PD are reported in supplementary tables and text
 only. Period prevalence of NTM infection and NTM-PD were not pooled due to
 varying time intervals among studies, while the rest of the epidemiologic
 measures had a small number of studies. To avoid the overrepresentation of
 registry reports in the meta-analysis, we included only the most recent
 report per registry with both numerator and denominator available to
 calculate prevalence. Secondary data analyses of registry data were also
 excluded from meta‑analysis to reduce redundancy with the registry
 reports. Heterogeneity was assessed with the I2 index and 95% confidence
 interval, with a significance level established at p &lt; 0.10.
 Publication bias was explored graphically using sample size as a predictor
 of bias in the funnel plot. We pre-specified subgroup analyses by study
 design, age category (pediatric vs adult), year of data collection (before
 2000, 2001 to 2009, and 2010–2019), geographical region (grouped as North America,
 Europe, and others), and the most common individual NTM species reported
 in CF (<em>Mycobacterium</em>
 <em>abscessus</em> complex (MABs)
 and <em>Mycobacterium</em> <em>avium</em> complex
 (MAC)). The prespecified meta-regression model was optimized by maximum
 likelihood and used the same transformation as the meta-analysis (LOGIT).
 We evaluated the goodness of fit in the model using Akaike’s information
 criteria by stepwise inclusion of pre-specified coefficients. Exploratory
 (unspecified) analyses include a longitudinal trend of prevalence in
 registries and subgroup analyses by region for MAC and MABs. Sensitivity
 analyses included three meta-analyses of NTM infection point (and annual)
 prevalence. The first excluded a study that screened patients only in the
 presence of increased symptoms, the second included only registry data,
 and the third excluded studies that did not use standardized culture media
 for identification of NTM. Reporting is based on the recommendations of
 the Joanna Briggs Institute and the Preferred Reporting Items for
 Systematic Reviews and Meta-Analyses (PRISMA)
 checklist.
description: Requires R version 4.1 or higher and a spreadsheet program (MS
 Excel) to explore the collected datasets. The R studio IDE was used to
 conduct R analyses and document procedures. The list of packages (with
 versions) necessary to reproduce the results is specified inside the
 scripts.