Evidence map›Paper›PMID 36404865›Full record

ArticleJournal of diabetes and metabolic disorders2022

Evaluation of the performance of osteoporosis/fracture screening models to identify high-risk women for osteoporosis: Bushehr elderly health (BEH) program.

Mahnaz Pejman Sani, Noushin Fahimfar, Nekoo Panahi, Mohammad Ali Mansournia, Mahnaz Sanjari, Kazem Khalagi, Mohammad Javad Mansourzadeh, Iraj Nabipour, Gita Shafiee, Afshin Ostovar and 1 more

Abstract read
In one paragraph

Article in Journal of diabetes and metabolic disorders, 2022. 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. 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

11 authors.

Mahnaz Pejman SaniOsteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Noushin FahimfarOsteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Nekoo PanahiMetabolic Disorders Research Center, Endocrinology and Metabolism Molecular Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad Ali MansourniaSchool of public health, department of epidemiology and biostatistics, Tehran university of medical science, Tehran, Iran.
Mahnaz SanjariOsteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Kazem KhalagiOsteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad Javad MansourzadehOsteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Iraj NabipourThe Persian Gulf Marine Biotechnology Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran.
Gita ShafieeChronic Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Afshin OstovarOsteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Bagher LarijaniEndocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to evaluate the performance of valid risk assessment models developed for osteoporosis/ fracture screening to identify women in need of bone density measurement in a population of Iranian elderly women. Methods: This study was performed using the data of Bushehr Elderly Health (BEH) program, a population-based cohort study of elderly population aged ≥ 60 years. Seven osteoporosis risk assessment tools, including Osteoporosis Risk Assessment Instrument (ORAI), Malaysian Osteoporosis Screening Tool (MOST), Osteoporosis Prescreening Risk Assessment (OPERA), Osteoporosis Prescreening Model for Iranian Postmenopausal women (OPMIP), Osteoporosis Index of Risk (OSIRIS), and Osteoporosis Self-Assessment Tool for Asians (OSTA), as well as Fracture Risk Assessment Tool (FRAX) were included in the study. By using osteoporosis definition based on BMD results, the performance measurement criteria of diagnostic tests such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Youden index for each model were calculated and the models were compared. Results: A total of 1237 female participants with the mean age of 69.1 ± 6.3 years were included. Overall, 733 (59%) participants had osteoporosis, and about 80% had no history of fracture. The sensitivity of the seven models ranged from 16.7% (OSIRIS) to 100% (ORAI and MOST) at their recommended cut-off points. Moreover,their specificity ranged from 0.0% (ORAI and MOST) to 78.9% (OSTA). The FRAX and OPERA had the optimal performance with the Youden index of 0.237 and 0.226, respectively. Moreover, after combining these models, the sensitivity of them increased to 85.4%. Conclusion: We found that the FRAX (model with 11 simple variables) and OPERA (model with 5 simple variables) had the best performance. By combining the models, the performance of each was improved. Further studies are needed to adopt the model and to find the best cut-off point in the Iranian postmenopausal women.

Indexed as

FractureOsteoporosisPost-menopausal womenRisk assessmentScreening

Identifiers

PMID36404865
PMCPMC9672243

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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.