Evidence map›Paper›PMID 33758991›Full record

ArticleOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2021

Impact of population-based or targeted BMD interventions on fracture incidence.

N C Harvey, J A Kanis, E Liu, L Vandenput, M Lorentzon, C Cooper, E McCloskey, H Johansson

Abstract read
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In one paragraph

Article in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 3 countries.

N C HarveyMRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, SO16 6YD, UK. nch@mrc.soton.ac.uk.ORCID http://orcid.org/0000-0002-8194-2512
J A KanisCentre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK.
E LiuMary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
L VandenputMary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
M LorentzonMary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
C CooperMRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, SO16 6YD, UK.
E McCloskeyCentre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK.
H JohanssonCentre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK.
Australian Catholic University · AUUniversity Hospital Southampton NHS Foundation Trust · GBSahlgrenska University Hospital · SEUniversity of Sheffield · GB

Funding

Medical Research Council MC_PC_21000Medical Research Council MC_PC_21001Medical Research Council MC_PC_21003
6 · The paper itself

Abstract

In a simulated population of older women, we demonstrate that an upward shift in the population distribution of BMD by approximately 0.3SD may decrease the risk of incident fractures to the same extent as an intervention targeted to those with T-score less than -2.5.

introductionTo investigate the impact of population level or targeted alterations to BMD on the incidence of fractures.

methodsWe used a simulated cohort of 49,242 women with age and body mass index distribution from the UK, and prevalence of other clinical risk factors based on European FRAX® cohorts. Using FRAX probabilities of major osteoporotic fracture (MOF: hip, clinical vertebral, distal forearm, proximal humerus) and hip fracture, calculated with femoral neck BMD, we determined the expected number of fractures over 10 years, stratified by 10-year age band from 50 years. We then investigated the effect of (i) uplifting all individuals with T-score below -2.5 to be exactly -2.5 (high-risk strategy) and (ii) shifting the entire BMD distribution upwards (population strategy).

resultsOverall, the high-risk strategy prevented 573 MOF including 465 hip fractures. Moving the BMD T-score distribution upward by 0.27SD gave an equivalent reduction in numbers of MOF; for hip fractures prevented, this was 0.35SD. A global upward 0.25SD BMD shift prevented 524 MOF including 354 hip fractures, with corresponding figures for an increase of 0.5SD being 973 MOF prevented and 640 hip fractures prevented. The ratio of hip fracture to MOF prevented differed by the two approaches, such that for the high-risk strategy, the ratio was 0.81, and for the population strategy was 0.68 (0.25SD BMD uplift) and 0.66 (0.5SD BMD uplift). The numbers of fractures prevented by the high-risk strategy increased with age. In contrast, the age-related increase in numbers of fractures prevented with the population strategy rose with age, but peaked in the 70-79-year age band and declined thereafter.

conclusionsBoth strategies reduced the numbers of expected incident fractures, with contrasting relative impacts by age and fracture site. Whilst the current analysis used UK/European anthropometric/risk factor distributions, further analyses calibrated to the distributions in other settings globally may be readily undertaken. Overall, these findings support the investigation of both population level interventions and those targeted at high fracture risk groups.

Indexed as

Hip FracturesOsteoporotic FracturesAgedBone DensityFemaleFemur NeckHumansIncidenceMiddle AgedRisk AssessmentRisk FactorsBMDEpidemiologyFractureOsteoporosisPopulationTargeted

Identifiers

PMID33758991
OpenAlexW3139021110

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.