Evidence map›Paper›PMID 40100219›Full record

ArticleJAMA network open2025

Identifying Younger Postmenopausal Women With Osteoporosis Using USPSTF-Recommended Osteoporosis Risk Assessment Tools.

Henry W Zheng, Alex A T Bui, Kristine E Ensrud, Nicole C Wright, JoAnn E Manson, Nelson B Watts, Karen C Johnson, Aladdin H Shadyab, Carolyn J Crandall

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. TLS-VBQ: a novel MRI-based bone quality score for opportunistic osteoporosis screening in spinal surgery candidates.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. 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

9 authors.

Henry W ZhengMedical and Imaging Informatics, UCLA (University of California, Los Angeles), Los Angeles.
Alex A T BuiDepartments of Radiological Sciences, Bioengineering and Bioinformatics, David Geffen School of Medicine at UCLA, Los Angeles.
Kristine E EnsrudDivision of Epidemiology and Community Health, Department of Medicine, University of Minnesota, Minneapolis.
Nicole C WrightDepartment of Epidemiology, School of Public Health, University of Alabama at Birmingham.
JoAnn E MansonDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Nelson B WattsBone Health and Osteoporosis Services, Bon Secours Mercy Health, Cincinnati, Ohio.
Karen C JohnsonDepartment of Preventive Medicine, University of Tennessee Health Science Center, Memphis.
Aladdin H ShadyabHerbert Wertheim School of Public Health and Human Longevity Science and Division of Geriatrics, Gerontology, and Palliative Care, Department of Medicine, University of California, San Diego, La Jolla.
Carolyn J CrandallDepartment of Medicine, David Geffen School of Medicine at UCLA, Los Angeles.

Funding

Predicting who will fracture: Exploration of machine learning in the observational Women's Health Initiative Study dataset.R21AR078905 · NIAMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUI, ALEX, CRANDALL, CAROLYN JANET · 2022 to 2023
$310k
NIAMS NIH HHS R21 AR078905
6 · The paper itself

Abstract

Importance: For younger postmenopausal women, clinical guidelines recommend using osteoporosis risk prediction tools to identify candidates with low bone mineral density (BMD). However, the performance of these tools is not well quantified. Objective: To examine the performance of Osteoporosis Risk Assessment Instrument (ORAI) and Osteoporosis Index of Risk (OSIRIS), compared with Osteoporosis Self-Assessment Tool (OST), in identifying the presence of osteoporotic BMD in younger postmenopausal women. Design, Setting, and Participants: This cross-sectional study used data from the Women's Health Initiative Bone Density Substudy, which was conducted at 3 clinical centers in Tucson and Phoenix, Arizona; Pittsburgh, Pennsylvania; and Birmingham, Alabama. Participants were healthy postmenopausal women aged 50 to 64 years with BMD measurements evaluated using the 3 risk prediction tools: OSIRIS, ORAI, and OST. Risk factors and other participant characteristics were compared across osteoporosis status. Data were collected from October 1993 to December 1998 and analyzed between September 23, 2023, and April 10, 2024. Exposures: The primary exposures were OSIRIS, ORAI, and OST risk scores. Main Outcomes and Measures: Primary outcome was osteoporosis defined by BMD T score of -2.5 or lower at 1 or more of 3 anatomical locations: femoral neck, total hip, and/or lumbar spine. The tools were evaluated via area under the receiver operating characteristic curve (AUC) at published score cutoffs and at alternate cutoffs. Results: Among 6067 included participants (mean [SD] age at baseline, 57.7 [4.1] years), the prevalence of osteoporosis was 14.1% (n = 857) at any 1 of 3 anatomical sites. AUC for identifying osteoporosis at any site was 0.633 (95% CI, 0.633-0.634) for OSIRIS, 0.663 (95% CI, 0.663-0.664) for ORAI, and 0.654 (95% CI, 0.654-0.655) for OST. Conclusions and Relevance: In this cross-sectional study, 3 guideline-recommended osteoporosis risk assessment tools had fair to moderate discrimination in identifying osteoporosis defined by lowest BMD at any 1 of 3 skeletal sites. Screening is essential to reducing individual and societal burden of osteoporosis and related fractures, and this study showed a gap in identifying younger postmenopausal women using common clinical risk factors.

Indexed as

Osteoporosis, PostmenopausalBone DensityCross-Sectional StudiesFemaleHumansMiddle AgedRisk AssessmentRisk Factors

Identifiers

PMID40100219
PMCPMC11920839

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.