Evidence map›Paper›PMID 39114671›Full record

ArticleAmerican journal of translational research2024

Development and validation of a nomogram incorporating multi-parametric MRI and hematological indicators for discriminating benign from malignant central prostatic nodules: a retrospective analysis.

Chunling Xu, Yupeng Zhang, Nailong Jia, Chuizhi Huang, Qimao Fu, Yan Chen, Changkun Lin

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Article in American journal of translational research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Chunling XuDepartment of Imaging, Lianyungang First People's Hospital Lianyungang 570311, Jiangsu, China.
Yupeng ZhangDepartment of Radiology, The Second Affiliated Hospital of Hainan Medical College Haikou 570311, Hainan, China.
Nailong JiaDepartment of Radiology, The Second Affiliated Hospital of Hainan Medical College Haikou 570311, Hainan, China.
Chuizhi HuangDepartment of Radiology, The Second Affiliated Hospital of Hainan Medical College Haikou 570311, Hainan, China.
Qimao FuDepartment of Radiology, The Second Affiliated Hospital of Hainan Medical College Haikou 570311, Hainan, China.
Yan ChenDepartment of Radiology, The Second Affiliated Hospital of Hainan Medical College Haikou 570311, Hainan, China.
Changkun LinDepartment of Radiology, The Second Affiliated Hospital of Hainan Medical College Haikou 570311, Hainan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProstate cancer poses a significant risk to men's health. In this study, a model for differentiating benign and malignant nodules in the central region of the prostate was constructed by combining multi-parametric MRI and hematological lab values.

methodsThis retrospective study analyzed the data acquired from Lianyungang First People's Hospital and The Second Affiliated Hospital of Hainan Medical College from January 2018 to December 2021. We included 310 MRI-confirmed prostatic nodule patients. The data were split into a training set (260 cases) and an external validation set (50 cases), with the latter exclusively from The Second Affiliated Hospital of Hainan Medical College to test the model's generalizability. Univariate and multivariate logistic regression identified critical measurements for differentiating prostate cancer (PCa) from benign prostatic hyperplasia (BPH), which were then integrated into a nomogram model.

resultsThe key indicators determined by multivariate logistic regression analysis included apparent diffusion coefficient (ADC), standard deviation (StDev), neutrophil to lymphocyte ratio (NLR), and prostate specific antigen (PSA). The nomogram's performance, as indicated by the area under the curve (AUC), was 0.844 (95% CI: 0.811-0.938) in the training set and 0.818 (95% CI: 0.644-0.980) in the external validation set. Calibration and decision curves demonstrated that the nomogram was well-calibrated and could serve as an effective tool in clinical practice.

conclusionThe nomogram model based on ADC, StDev, NLR and PSA may be helpful to identify PCa and BPH.

Indexed as

identificationmagnetic resonance imagingnomogramProstate cancer

Identifiers

PMID39114671
PMCPMC11301461

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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.