Evidence map›Paper›PMID 40823712›Full record

ArticleJournal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research2026

Longitudinal associations between changes in bone mechanical strength and fracture risk estimated by μFRAC.

Annabel R Bugbird, Danielle E Whittier, Lauren A Burt, Steven K Boyd

Abstract read
In one paragraph

Article in Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Annabel R BugbirdMcCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada.
Danielle E WhittierMcCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada.
Lauren A BurtMcCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada.
Steven K BoydMcCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada.

Funding

EPIDEMIOLOGY OF AGE-RELATED BONE LOSS, &FRACTURESR01AR027065 · NIAMS · MAYO CLINIC ROCHESTER · PI AMIN, SHREYASEE, KHOSLA, SUNDEEP · 1986 to 2020
$14.9M
The Gut Microbiome and Bone MicroarchitectureR01AR061445 · NIAMS · HEBREW REHABILITATION CENTER FOR AGED · PI KIEL, DOUGLAS P. · 2012 to 2021
$8.9M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
Bob and Nola Rintoul Chair in Bone and Joint ResearchCIHR 178098NHLBI NIH HHS HHSN268201500001CNHLBI NIH HHS HHSN268201500001INHLBI NIH HHS N01 HC025195NIAMS NIH HHS R01 AR027065NIAMS NIH HHS R01 AR061445
6 · The paper itself

Abstract

Monitoring bone health for osteoporosis is typically based on measuring areal BMD. However, widely used fracture risk prediction tools are primarily driven by clinical risk factors and show limited sensitivity to underlying bone changes over time. This study evaluated the ability of the new Microarchitecture Fracture Risk Assessment Calculator ($\mu $FRAC) to detect longitudinal changes in fracture risk in relation to bone quality. Our study cohort included 601 participants (70.2% female) from a longitudinal population study. HR-pQCT scans of the distal radius and tibia were acquired at 2 visits, 3-10 years apart. The $\mu $FRAC 5-year risk of major osteoporotic fracture was calculated at both time points. Participants were divided into quartiles based on the absolute change in tibia bone strength between study visits to assess the model's sensitivity to changes in bone fragility. Differences between quartiles were assessed using a Mann-Whitney U test and the standardized response mean (SRM). Additionally, changes in fracture risk by decade, were analyzed to investigate age- and sex-specific trends in fracture risk. The average age of participants was 53.8 $\pm $ 15.4 years, with an average follow-up of 6.8 $\pm $ 1.8 years. The greatest absolute annualized changes in $\mu $FRAC risk occurred in individuals with the largest differences in bone strength (SRM = 0.73-0.78), while the least change was observed in individuals with minimal changes (SRM = 0.07-0.21). Age- and sex-specific trends aligned with previously established patterns of bone aging, showing the greatest annualized changes in fracture risk in menopausal females (40-60 years) and older adults (70+ years). We demonstrated $\mu $FRAC is sensitive to changes in fracture risk driven by declines in bone quality in aging adults. These results suggest $\mu $FRAC is well suited for tracking fracture prediction longitudinally and has potential to monitor osteoporosis disease progression and treatment response.

Indexed as

Absorptiometry, PhotonBone and BonesBone DensityFractures, BoneOsteoporotic FracturesAdultAgedBiomechanical PhenomenaFemaleHumansLongitudinal StudiesMaleMiddle AgedRisk FactorsTibiachange in fracture riskfracture risk assessmenthigh-resolution peripheral quantitative computed tomographyosteoporosisμFRAC

Identifiers

PMID40823712
PMCPMC12865857

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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.