[1]梁建嫦,吴锦锋,张泳欣,等.基于影像学和血清学特征构建列线图模型对PSA 4~10 ng mL患者穿刺阳性的预测价值[J].中国医学物理学杂志,2024,41(12):1494-1500.[doi:DOI:10.3969/j.issn.1005-202X.2024.12.006]
　LIANG Jianchang,WU Jinfeng,ZHANG Yongxin,et al.Predictive value of a nomogram model constructed based on imaging and serological characteristics for prostate biopsy positivity in patients with PSA levels of 4-10 ng mL[J].Chinese Journal of Medical Physics,2024,41(12):1494-1500.[doi:DOI:10.3969/j.issn.1005-202X.2024.12.006]
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基于影像学和血清学特征构建列线图模型对PSA 4~10 ng mL患者穿刺阳性的预测价值()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
41卷
期数:
2024年第12期
页码:
1494-1500
栏目:
医学影像物理
出版日期:
2024-12-17

文章信息/Info

Title:
Predictive value of a nomogram model constructed based on imaging and serological characteristics for prostate biopsy positivity in patients with PSA levels of 4-10 ng mL
文章编号:
1005-202X（2024）12-1494-07
作者:
梁建嫦1; 吴锦锋2; 张泳欣2; 5; 沈俊鑫3; 陈振杰2; 谭健2; 钟睿2; 赵卫4; 卢扬柏2; 袁润强2
1.云浮市中医院检验科， 广东 云浮 527300； 2.中山市人民医院泌尿外科， 广东 中山 528403； 3.广东医科大学第一临床医学院，广东 湛江524023； 4.南方医科大学公共卫生学院， 广东 广州 510515； 5.中山市人民医院影像中心， 广东 中山 528403
Author(s):
LIANG Jianchang1;  WU Jinfeng2;  ZHANG Yongxin2;  5;  SHEN Junxin3;  CHEN Zhenjie2;  TAN Jian2;  ZHONG Rui2;  ZHAO Wei4;  LU Yangbai2;  YUAN Runqiang2
1. Department of Clinical Laboratory, Yunfu Hospital of TCM, Yunfu 527300, China 2.Department of Urology, Zhongshan City Peoples Hospital, Zhongshan 528403, China 3. The First Clinical Medical College, Guangdong Medical University, Zhanjiang 524023, China 4. School of Public Health, Southern Medical University, Guangzhou 510515, China 5. Imaging Center,Zhongshan City Peoples Hospital, Zhongshan 528403, China
关键词:
前列腺癌; 列线图模型; 前列腺特异性抗原; 预测模型; 影像学; 血清学
Keywords:
Keywords: prostate cancer nomogram model prostate specific antigen predictive model imaging serology
分类号:
R318；R737.25
DOI:
DOI:10.3969/j.issn.1005-202X.2024.12.006
文献标志码:
A
摘要:
目的：探讨基于影像学联合前列腺特异性抗原（PSA）及其相关参数构建的列线图模型对PSA 4~10 ng/mL患者穿刺阳性的预测价值。方法：回顾性分析2018年1月至2023年12月191例在中山市人民医院和/或云浮市中医院行血清学PSA及相关指标检测并接受经直肠超声穿刺前列腺首次活检的患者的临床血清学和影像学资料，应用多因素Logistic回归分析前列腺癌相关独立风险因素，构建PSA 4~10 ng/mL患者的列线图模型，使用受试者工作特征曲线、校准曲线和决策曲线对模型进行评估。结果：多因素Logistic回归分析结果显示游离PSA、前列腺体积、移行带体积、PSA密度及前列腺影像报告和数据系统（PI-RADS v2.1）为前列腺癌的独立风险因素。基于这些显著变量构建的融合模型表现最佳，AUC为0.750（95%CI：0.678~0.821），敏感性为72.7%，特异性为77.2%，准确性为74.9%。校准曲线显示该模型预测的前列腺癌概率与病理结果有良好的一致性；决策曲线分析进一步证明该模型具有较高的临床应用价值。结论：构建的列线图及预测模型在术前能较好地预测PSA 4~10 ng/mL患者前列腺癌的风险，为临床医师提供直观的预估工具，有助于根据前列腺癌发生的风险调整治疗计划，从而优化患者的生存结果。
Abstract:
Abstract: Objective To investigate the predictive value of a nomogram model constructed based on imaging combined with prostate-specific antigen (PSA) and its related parameters for biopsy in patients with PSA levels of 4-10 ng/mL. Methods The serological and imaging data of 191 patients who were detected for PSA and related indicators and underwent the first biopsy of prostate by transrectal ultrasound at Zhongshan City Peoples Hospital and/or Yunfu Hospital of TCM from January 2018 to December 2023 were analyzed retrospectively. Multivariate Logistic regression identified independent risk factors for prostate cancer, and a nomogram model was developed for patients with PSA levels of 4-10 ng/mL. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results The multivariate Logistic regression analysis showed that free PSA, prostate volume, transition zone volume, PSA density, and the prostate imaging-reporting and data system (PI-RADS v2.1) score were independent risk factors for prostate cancer. The model incorporating these significant variables demonstrated the best performance, with an area under the curve (AUC) of 0.750 (95% CI: 0.678-0.821), sensitivity of 72.7%, specificity of 77.2%, and accuracy of 74.9%. The calibration curve indicated good agreement between the predicted probability and the actual probability of prostate cancer and the decision curve analysis further confirmed that the model had high clinical utility. Conclusion The constructed nomogram prediction model can effectively estimate the preoperative risk of prostate cancer in patients with PSA levels of 4-10 ng/mL, providing clinicians with an intuitive tool to adjust treatment plans based on the assessed risk, thereby optimizing patient outcomes.

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备注/Memo

备注/Memo:
【收稿日期】2024-10-26 【基金项目】国家重点研发计划（2018YFC1602206）；广东省基础与应用基础研究基金（2022A1515220032）；广东省医学科学技术研究基金（B2023195）；中山市科技计划项目（2020B1073）；中山市人民医院重大科研基金（BG20228249）；中山市人民医院优秀青年项目（SG2023106）；中山市第三批社会公益与基础研究项目（2023B3006） 【作者简介】梁建嫦，副主任技师，研究方向：免疫学检验，E-mail: m202413672507034@163.com 【通信作者】袁润强，博士，主任医师，研究方向：泌尿系肿瘤，E-mail: yuanrunqiang@yeah.net
更新日期/Last Update: 2024-12-20