Dataset Information

Abdominal aortic calcification, bone mineral density and fractures: a systematic review and meta-analysis protocol.

ABSTRACT:

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.

SUBMITTER: Rodriguez AJ

PROVIDER: S-EPMC6500258 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Abdominal aortic calcification, bone mineral density and fractures: a systematic review and meta-analysis protocol.

Rodríguez Alexander J AJ Leow Kevin K Szulc Pawel P Scott David D Ebeling Peter P Sim Marc M Wong Germaine G Lim Wai H WH Schousboe John T JT Kiel Douglas P DP Prince Richard L RL R Lewis Joshua J

BMJ open 20190402 4

<h4>Introduction</h4>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) ...[more]

PMID: 30944137

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Project description:BackgroundLateral spine images for vertebral fracture assessment can be easily obtained on modern bone density machines. Abdominal aortic calcification (AAC) can be scored on these images by trained imaging specialists to assess cardiovascular disease risk. However, this process is laborious and requires careful training.MethodsTraining and testing of model performance of the convolutional neural network (CNN) algorithm for automated AAC-24 scoring utilised 5012 lateral spine images (2 manufacturers, 4 models of bone density machines), with trained imaging specialist AAC scores. Validation occurred in a registry-based cohort study of 8565 older men and women with images captured as part of routine clinical practice for fracture risk assessment. Cox proportional hazards models were used to estimate the association between machine-learning AAC (ML-AAC-24) scores with future incident Major Adverse Cardiovascular Events (MACE) that including death, hospitalised acute myocardial infarction or ischemic cerebrovascular disease ascertained from linked healthcare data.FindingsThe average intraclass correlation coefficient between imaging specialist and ML-AAC-24 scores for 5012 images was 0.84 (95% CI 0.83, 0.84) with classification accuracy of 80% for established AAC groups. During a mean follow-up 4 years in the registry-based cohort, MACE outcomes were reported in 1177 people (13.7%). With increasing ML-AAC-24 scores there was an increasing proportion of people with MACE (low 7.9%, moderate 14.5%, high 21.2%), as well as individual MACE components (all p-trend <0.001). After multivariable adjustment, moderate and high ML-AAC-24 groups remained significantly associated with MACE (HR 1.54, 95% CI 1.31-1.80 & HR 2.06, 95% CI 1.75-2.42, respectively), compared to those with low ML-AAC-24.InterpretationThe ML-AAC-24 scores had substantial levels of agreement with trained imaging specialists, and was associated with a substantial gradient of risk for cardiovascular events in a real-world setting. This approach could be readily implemented into these clinical settings to improve identification of people at high CVD risk.FundingThe study was supported by a National Health and Medical Research Council of Australia Ideas grant and the Rady Innovation Fund, Rady Faculty of Health Sciences, University of Manitoba.

Project description:BackgroundOsteoporosis is diagnosed by the measurement of bone mineral density, which is a highly heritable and multifactorial trait. We aimed to identify genetic loci that are associated with bone mineral density.MethodsIn this genome-wide association study, we identified the most promising of 314 075 single nucleotide polymorphisms (SNPs) in 2094 women in a UK study. We then tested these SNPs for replication in 6463 people from three other cohorts in western Europe. We also investigated allelic expression in lymphoblast cell lines. We tested the association between the replicated SNPs and osteoporotic fractures with data from two studies.FindingsWe identified genome-wide evidence for an association between bone mineral density and two SNPs (p<5x10(-8)). The SNPs were rs4355801, on chromosome 8, near to the TNFRSF11B (osteoprotegerin) gene, and rs3736228, on chromosome 11 in the LRP5 (lipoprotein-receptor-related protein) gene. A non-synonymous SNP in the LRP5 gene was associated with decreased bone mineral density (rs3736228, p=6.3x10(-12) for lumbar spine and p=1.9x10(-4) for femoral neck) and an increased risk of both osteoporotic fractures (odds ratio [OR] 1.3, 95% CI 1.09-1.52, p=0.002) and osteoporosis (OR 1.3, 1.08-1.63, p=0.008). Three SNPs near the TNFRSF11B gene were associated with decreased bone mineral density (top SNP, rs4355801: p=7.6x10(-10) for lumbar spine and p=3.3x10(-8) for femoral neck) and increased risk of osteoporosis (OR 1.2, 95% CI 1.01-1.42, p=0.038). For carriers of the risk allele at rs4355801, expression of TNFRSF11B in lymphoblast cell lines was halved (p=3.0x10(-6)). 1883 (22%) of 8557 people were at least heterozygous for these risk alleles, and these alleles had a cumulative association with bone mineral density (trend p=2.3x10(-17)). The presence of both risk alleles increased the risk of osteoporotic fractures (OR 1.3, 1.08-1.63, p=0.006) and this effect was independent of bone mineral density.InterpretationTwo gene variants of key biological proteins increase the risk of osteoporosis and osteoporotic fracture. The combined effect of these risk alleles on fractures is similar to that of most well-replicated environmental risk factors, and they are present in more than one in five white people, suggesting a potential role in screening.

Dataset Information

Abdominal aortic calcification, bone mineral density and fractures: a systematic review and meta-analysis protocol.

Introduction

Methods

Ethics and dissemination

Prospero registration number

Publications

Abdominal aortic calcification, bone mineral density and fractures: a systematic review and meta-analysis protocol.

Similar Datasets

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