Alexander J. Rodríguez
Marc Sim, Edith Cowan UniversityFollow
Wai H. Lim
John T. Schousboe
Douglas P. Kiel
Richard L. Prince
Joshua R. Lewis, Edith Cowan UniversityFollow
Marc Sim Orcid: https://orcid.org/0000-0001-5166-0605
BMJ Publishing Group Ltd
School of Medical and Health Sciences
Funding information available at https://doi.org/10.1136/bmjopen-2018-026232
NHMRC Number : 1107474
INTRODUCTION: Abdominal aortic calcification (AAC) is associated with low bone mass and increased fracture risk. Two previous meta-analyses have investigated the association between AAC and fracture. However, these meta-analyses only identified articles until December 2016, undertook limited searches and did not explore potential sources of between-study heterogeneity. We aim to undertake a sensitive and comprehensive assessment of the relationship between AAC, bone mineral density (BMD) as well as prevalent and incident fractures.
METHODS: We will search MEDLINE, EMBASE, Web of Science core collection and Google Scholar (top 200 articles sorted by relevance) from their inception to 1 June 2018. Reference lists of included studies and previous systematic reviews will be hand searched for additional eligible studies. Retrospective and prospective cohort studies (cross-sectional, case-control and longitudinal) reporting the association between AAC, BMD and fracture at any site will be included. At least two investigators will independently: (A) evaluate study eligibility and extract data, with a third investigator to adjudicate when discrepancies occur, (B) assess study quality by the Newcastle-Ottawa Scale for each cohort/study. The meta-analysis will be reported in adherence to the Meta-analysis of Observational Studies in Epidemiology criteria. AAC will be grouped as either: (1) AAC present or absent, (2) AAC categorised as 'low' (referent-lowest reported group) versus 'high' (all other groups) or (3) dose-response when AAC was assessed in ≥3 groups. Where primary event data were reported in individual studies, pooled risk differences and risk ratios with 95% CI will be calculated, from which, a summary estimate will be determined using DerSimonian-Laird random effects models. For the AAC and BMD pooled analyses, estimates will be expressed as standardised mean difference with 95% CI. We will examine the likelihood of publication bias and where possible, investigate potential reasons for between-study heterogeneity using subgroup analyses and meta-regression.
ETHICS AND DISSEMINATION: The study will be submitted to a peer- reviewed journal and disseminated via research presentations.
PROSPERO REGISTRATION NUMBER: CRD42018088019.
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