[1]王永祥,赵兴华,许长宝,等.初诊前列腺癌骨转移的危险因素分析及预测模型建立[J].医学信息,2023,36(11):16-20.[doi:10.3969/j.issn.1006-1959.2023.11.003]
　WANG Yong-xiang,ZHAO Xing-hua,XU Chang-bao,et al.Risk Factors Analysis and Prediction Model Establishment of Bone Metastasis in Newly Diagnosed Prostate Cancer[J].Journal of Medical Information,2023,36(11):16-20.[doi:10.3969/j.issn.1006-1959.2023.11.003]
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初诊前列腺癌骨转移的危险因素分析及预测模型建立()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年11期
页码:
16-20
栏目:
临床信息学
出版日期:
2023-06-01

文章信息/Info

Title:
Risk Factors Analysis and Prediction Model Establishment of Bone Metastasis in Newly Diagnosed Prostate Cancer
文章编号:
1006-1959（2023）11-0016-05
作者:
王永祥; 赵兴华; 许长宝; 等
（郑州大学第二附属医院泌尿外科，河南 郑州 450000）
Author(s):
WANG Yong-xiang; ZHAO Xing-hua; XU Chang-bao; et al.
(Department of Urology Surgery,the Second Affiliated Hospital of Zhengzhou University,Zhengzhou 450000,Henan,China)
关键词:
前列腺癌; 骨转移; 列线图; 预测模型
Keywords:
Prostate cancer; Bone metastasis; Nomogram; Prediction model
分类号:
R69；R737.1
DOI:
10.3969/j.issn.1006-1959.2023.11.003
文献标志码:
A
摘要:
目的 探讨初诊前列腺癌骨转移的危险因素，构建个性化预测前列腺癌发生骨转移概率的列线图模型。方法 回顾性分析2014年9月-2022年9月就诊于郑州大学第二附属医院泌尿外科298例初诊前列腺癌的临床病理资料，根据骨扫描结果分为未骨转移组（162例）和骨转移组（136例），采用单因素和多因素Logistic回归分析筛选前列腺癌骨转移的独立危险因素，联合独立危险因素构建列线图预测模型，绘制列线图模型的校准曲线以及受试者工作特征曲线（ROC）评估模型的预测效能。结果 骨转移组血清总前列腺特异性抗原（tPSA）、Gleason评分（GS）、临床肿瘤分期（cTx）、前列腺特异性抗原密度（PSAD）、血清磷水平（sP）、碱性磷酸酶（ALP）、和系统免疫炎症指数（SII）高于未骨转移组，差异有统计学意义（P＜0.05）；Logistic分析显示tPSA、GS、cTx、ALP以及SII是前列腺癌发生骨转移的独立危险因素（OR＞1，P＜0.05）。构建了预测前列腺癌发生骨转移风险的列线图，校准曲线和理想曲线比较贴近，预测模型的ROC曲线下面积（AUC）为0.923。结论 tPSA、GS、cTx、ALP以及SII是前列腺癌发生骨转移的独立危险因素，本次构建的列线图模型对前列腺癌发生骨转移有较高的预测价值。
Abstract:
Objective To explore the risk factors of bone metastasis in newly diagnosed prostate cancer, and to construct a personalized nomogram model for predicting the probability of bone metastasis in prostate cancer.Methods The clinicopathological data of 298 patients with newly diagnosed prostate cancer in the Department of Urology, the Second Affiliated Hospital of Zhengzhou University from September 2014 to September 2022 were retrospectively analyzed. According to the results of bone scan, they were divided into non-bone metastasis group (162 patients) and bone metastasis group (136 patients). Univariate and multivariate Logistic regression analysis was used to screen the independent risk factors of bone metastasis of prostate cancer. The nomogram prediction model was constructed by combining independent risk factors, and the calibration curve of the nomogram model and the receiver operating characteristic curve (ROC) were drawn to evaluate the predictive efficacy of the model.Results The serum total prostate specific antigen (tPSA), Gleason score (GS), clinical tumor stage (cTx), prostate specific antigen density (PSAD), serum phosphorus level (sP), alkaline phosphatase (ALP) and systemic immune inflammation index (SII) in the bone metastasis group were higher than those in the non-bone metastasis group, and the differences were statistically significant (P<0.05). Logistic analysis showed that tPSA, GS, cTx, ALP and SII were independent risk factors for bone metastasis of prostate cancer (OR>1, P<0.05). A nomogram was constructed to predict the risk of bone metastasis in prostate cancer. The calibration curve was close to the ideal curve, and the area under the ROC curve (AUC) of the prediction model was 0.923.Conclusion tPSA, GS, cTx, ALP and SII are independent risk factors for bone metastasis of prostate cancer. The nomogram model constructed in this study has a high predictive value for bone metastasis of prostate cancer.

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更新日期/Last Update: 1900-01-01