Evidence map›Paper›PMID 41142623›Full record

ArticleFrontiers in oncology2025

The diagnostic value of inflammatory markers in bone metastasis of prostate cancer at initial prostate biopsy.

Xinyang Chen, Yu Li, Zhiqin Chen, Gansheng Xie, Huming Yin, Gang Li

Abstract read
In one paragraph

Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xinyang Chen *Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Yu Li *Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Zhiqin ChenDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Gansheng XieDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Huming YinDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Gang LiDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Accurate prediction of bone metastasis at diagnosis is crucial for optimizing management in prostate cancer (PCa) patients. While clinical parameters like PSA and Gleason score are established predictors, their accuracy is suboptimal. Systemic inflammation, reflected in biomarkers like the high-sensitivity C-reactive protein-to-albumin ratio (HAR), fibrinogen (FIB), and hemoglobin (HB), has emerged as a key player in cancer progression, yet its integration into clinical predictive tools remains underexplored. Methods: In this retrospective study of 803 newly diagnosed PCa patients, we developed and validated two nomograms for predicting bone metastasis. A baseline clinical model was constructed using total prostate-specific antigen (TPSA) and biopsy Gleason grade groups. An enhanced comprehensive model integrated these clinical parameters with inflammatory markers (HAR, FIB, HB). Model performance was rigorously assessed through discrimination (ROC analysis, AUC), calibration (calibration curves, Hosmer-Lemeshow test), and clinical utility (Decision Curve Analysis). Internal validation was performed via bootstrapping. Results: Multivariate analysis confirmed TPSA, FIB, HB, HAR, and Gleason grade groups as independent predictors of bone metastasis. The comprehensive model demonstrated significantly superior discriminative ability, achieving an AUC of 0.874 (95% CI: 0.845-0.902) compared to 0.830 (95% CI: 0.798-0.863) for the clinical model (Delong's test, P < 0.01). This translated to a net improvement in reclassification (NRI: 8.96%) and overall predictive performance (IDI: 10.3%). The model was well-calibrated and provided a positive net benefit across a wide range of clinical threshold probabilities. Conclusion: We present a novel, internally validated nomogram that synergistically combines inflammatory and clinical markers to accurately predict bone metastasis in PCa at initial diagnosis. This practical and cost-effective tool has the potential to aid clinicians in risk stratification, guide personalized diagnostic imaging decisions, and ultimately help reduce unnecessary bone scans, particularly in resource-conscious settings. Our findings underscore the pivotal role of the systemic inflammatory response in PCa metastasis.

Indexed as

bone metastasisfibrinogenGleason scorehigh-sensitivity C-reactive protein/albumin ratioprostate biopsyprostate cancer

Identifiers

PMID41142623
PMCPMC12545053

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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.