Evidence map›Paper›PMID 41561052›Full record

ArticleFrontiers in endocrinology2025

Bone turnover markers (β-CTX, PINP, ALP) in osteoporosis: correlation with bone loss and fracture risk stratification.

Shiqiang Wu, Liangming Wang, Xiaolu Zhang, Liquan Cai, Qingfeng Ke, Jie Xu

Abstract read
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Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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0cells of the map it votes in
10citing 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

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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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

6 authors.

Shiqiang WuDepartment of Orthopedic, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Liangming WangDepartment of Orthopedic, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Xiaolu ZhangDepartment of Orthopedic, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Liquan CaiDepartment of Orthopedic, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Qingfeng KeDepartment of Orthopedic, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Jie XuShengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the correlation of β-C-terminal telopeptide of type I collagen (β-CTX), procollagen type I N-terminal propeptide (PINP), alkaline phosphatase (ALP) with bone mineral density (BMD) in patients with osteoporosis and evaluate their predictive value for secondary fracture risk. Methods: A total of 180 osteoporosis patients and 80 healthy controls were enrolled. The osteoporosis group was stratified into fracture and non-fracture cohorts. Correlation of β-CTX, PINP, ALP with BMD at lumbar spine (L1-4) and femoral neck was assessed using Pearson correlation coefficient. Binary logistic regression model was employed to analyze the risk factors associated with secondary fractures in patients with osteoporosis and receiver-operator characteristic (ROC) curve was used for assessing the predictive utility. Results: Osteoporosis patients exhibited significantly higher β-CTX, PINP, and ALP levels compared to controls (all Conclusion: Elevated β-CTX, PINP, and ALP levels correlate with reduced BMD and independently predict secondary fracture risk in osteoporosis patients. Integrating these biomarkers with BMD enhances fracture risk stratification, supporting their inclusion in clinical risk assessment tool.

Indexed as

Alkaline PhosphataseBiomarkersBone RemodelingCollagen Type IOsteoporosisOsteoporotic FracturesPeptide FragmentsPeptidesProcollagenAgedBone DensityCase-Control StudiesFemaleHumansMaleMiddle AgedAlkaline PhosphataseBiomarkersCollagen Type Icollagen type I trimeric cross-linked peptidePeptide FragmentsPeptidesProcollagenprocollagen Type I N-terminal peptidealkaline phosphatasebone turnover markersfractureosteoporosisprocollagen type I N-terminal propeptide (PINP)β-C-terminal telopeptide of type I collagen (β-CTX)

Identifiers

PMID41561052
PMCPMC12812736

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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.