Evidence map›Paper›PMID 38503995›Full record

ArticleArchives of osteoporosis2024

Age-dependent FRAX-based assessment and intervention thresholds for therapeutic decision making in osteoporosis in the Malaysian population.

Jeyakantha Ratnasingam, Mariyam Niyaz, Shanmugam Mariyappan, Terence Ong, Siew Pheng Chan, Fen Lee Hew, Swan Sim Yeap, Shanty Velaiutham, Subashini C Thambiah, Sarath Lekamwasam

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of osteoporosis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Race-specific FRAX models are evidence-based and support equitable care: a response to the ASBMR Task Force report on Clinical Algorithms for Fracture Risk.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
    Article
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

10 authors.

Jeyakantha RatnasingamDepartment of Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia. jeyakantha_r@hotmail.com.
Mariyam NiyazDepartment of Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia.
Shanmugam MariyappanDepartment of Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia.
Terence OngDepartment of Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia.
Siew Pheng ChanDepartment of Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia.
Fen Lee HewPuchong Specialist Clinic, Puchong, Malaysia.
Swan Sim YeapPuchong Specialist Clinic, Puchong, Malaysia.
Shanty VelaiuthamHospital Pulau Pinang, George Town, Malaysia.
Subashini C ThambiahUniversiti Putra Malaysia, Seri Kembangan, Malaysia.
Sarath LekamwasamFaculty of Medicine, University of Ruhuna, Matara, Sri Lanka.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fracture risk stratification is crucial in countries with limited access to bone density measurement. 24.8% women were in the high-risk category while 30.4% were in the low-risk category. In the intermediate risk group, after recalculation of fracture risk with bone density, 38.3% required treatment. In more than half, treatment decisions can be made without bone density. PURPOSE: We aimed to examine the role of age-dependent intervention thresholds (ITs) applied to the Fracture Risk Assessment (FRAX) tool in therapeutic decision making for osteoporosis in the Malaysian population.

methodsData were collated from 1380 treatment-naïve postmenopausal women aged 40-85 years who underwent bone mineral density (BMD) measurements for clinical reasons. Age-dependent ITs, for both major osteoporotic fracture (MOF) and hip fracture (HF), were calculated considering a woman with a BMI of 25 kg/m

resultsThe ITs of MOF and HF ranged from 0.7 to 18% and 0.2 to 8%, between 40 and 85years. The LATs of MOF ranged from 0.3 to 11%, while those of HF ranged from 0.1 to 5.2%. The UATs of MOF and HF were 0.8 to 21.6% and 0.2 to 9.6%, respectively. In this study, 24.8% women were in the high-risk category while 30.4% were in the low-risk category. Of the 44.8% (n=618) in the intermediate risk group, after recalculation of fracture risk with BMD input, 38.3% (237/618) were above the ITs while the rest (n=381, 61.7%) were below the ITs. Judged by the Youden Index, 11.5% MOF probability which was associated with a sensitivity of 0.62 and specificity of 0.83 and 4.0% HF probability associated with a sensitivity of 0.63 and a specificity 0.82 were found to be the most appropriate fixed ITs in this analysis.

conclusionLess than half of the study population (44.8%) required BMD for osteoporosis management when age-specific assessment thresholds were applied. Therefore, in more than half, therapeutic decisions can be made without BMD based on these assessment thresholds.

Indexed as

Hip FracturesOsteoporosisOsteoporotic FracturesAdultAgedAged, 80 and overBone DensityDecision MakingFemaleHumansMaleMiddle AgedRisk AssessmentRisk FactorsBone mineral densityFRAXIntervention thresholdsLower assessment thresholdsMalaysiaOsteoporosisUpper assessment thresholds

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.