Evidence map›Paper›PMID 23420298›Full record

ArticleJournal of bone and mineral metabolism2013

Development and validation of osteoporosis risk-assessment model for Korean postmenopausal women.

Sun Min Oh, Byung-Ho Nam, Yumie Rhee, Seong-Hwan Moon, Deog Young Kim, Dae Ryong Kang, Hyeon Chang Kim

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Journal of bone and mineral metabolism, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
2.3field-weighted citation impact, top 14% 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

20 citing papers in PubMed, 3 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for osteoporosis or low bone density.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2015
    Pooled it
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  12. Performance of Osteoporosis Self-Assessment Tool (OST) in Predicting Osteoporosis-A Review.International journal of environmental research and public health · 2018
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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

7 authors at 3 institutions in 2 countries.

Sun Min OhDepartment of Preventive Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea.
Byung-Ho Nam
Yumie Rhee
Seong-Hwan Moon
Deog Young Kim
Dae Ryong Kang
Hyeon Chang Kim
Yonsei University · KRNational Cancer Center · KRNorthwestern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, dual-energy X-ray absorptiometry (DXA) is the gold standard for detecting osteoporosis, but is not recommended for general population screening. Therefore, this study aims to develop an osteoporosis risk-assessment model to identify high-risk individuals among Korean postmenopausal women. Data from 1,209 and 1,046 postmenopausal women who participated in the 2009 and 2010 Korean National Health and Nutrition Examination Survey, respectively, were used for development and validation of an osteoporosis risk-assessment model. Osteoporosis was defined as T score less than or equal to -2.5 at either the femoral neck or lumbar spine. Performance of the candidate models and the Osteoporosis Self assessment Tool for Asians (OSTA) were compared with respect to sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). To compare the developed Korean Osteoporosis Risk-Assessment Model (KORAM) with OSTA, a net reclassification improvement was further calculated. In the development dataset, the prevalence of osteoporosis was 33.9 %. KORAM, consisting of age, weight, and hormone therapy, had a sensitivity of 91.2 %, a specificity of 50.6 %, and an AUC of 0.709 with a specific cut-off score of -9. Comparable results were shown in the validation dataset: sensitivity 84.8 %, specificity 51.6 %, and AUC 0.682. Additionally, risk categorization with KORAM showed improved reclassification over that of OSTA from 7.4 to 41.7 %. KORAM can be easily used as a pre-screening tool to identify candidates for DXA tests. Further studies investigating cost-effectiveness and replicability in other datasets are required to establish the clinical utility of KORAM.

Indexed as

Models, BiologicalRisk AssessmentAgedBone DensityFemaleHumansMiddle AgedOsteoporosis, PostmenopausalPractice Guidelines as TopicRegression AnalysisReproducibility of ResultsRepublic of KoreaRisk Factors

Identifiers

PMID23420298
OpenAlexW2038630032

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.