Evidence map›Paper›PMID 35855348›Full record

ReviewAging and disease2022

Prediction Models for Osteoporotic Fractures Risk: A Systematic Review and Critical Appraisal.

Xuemei Sun, Yancong Chen, Yinyan Gao, Zixuan Zhang, Lang Qin, Jinlu Song, Huan Wang, Irene Xy Wu

Abstract readReview
In one paragraph

Review in Aging and disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
–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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Observational
  4. The development and validation of a prediction model for imminent vertebral osteoporotic fracture in postmenopausal women.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
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  10. Predictive capacity of fracture risk assessment tools: overview of systematic reviews.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025
    Review
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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

8 authors.

Xuemei Sun1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.
Yancong Chen1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.
Yinyan Gao1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.
Zixuan Zhang1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.
Lang Qin1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.
Jinlu Song1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.
Huan Wang1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.
Irene Xy Wu1Department of Epidemiology and Biostatistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoporotic fractures (OF) are a global public health problem currently. Many risk prediction models for OF have been developed, but their performance and methodological quality are unclear. We conducted this systematic review to summarize and critically appraise the OF risk prediction models. Three databases were searched until April 2021. Studies developing or validating multivariable models for OF risk prediction were considered eligible. Used the prediction model risk of bias assessment tool to appraise the risk of bias and applicability of included models. All results were narratively summarized and described. A total of 68 studies describing 70 newly developed prediction models and 138 external validations were included. Most models were explicitly developed (n=31, 44%) and validated (n=76, 55%) only for female. Only 22 developed models (31%) were externally validated. The most validated tool was Fracture Risk Assessment Tool. Overall, only a few models showed outstanding (n=3, 1%) or excellent (n=32, 15%) prediction discrimination. Calibration of developed models (n=25, 36%) or external validation models (n=33, 24%) were rarely assessed. No model was rated as low risk of bias, mostly because of an insufficient number of cases and inappropriate assessment of calibration. There are a certain number of OF risk prediction models. However, few models have been thoroughly internally validated or externally validated (with calibration being unassessed for most of the models), and all models showed methodological shortcomings. Instead of developing completely new models, future research is suggested to validate, improve, and analyze the impact of existing models.

Indexed as

critical appraisalosteoporotic fracturesprediction modelsystematic review

Identifiers

PMID35855348
PMCPMC9286920

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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.