转移性肾癌亚型的预后评估与预测模型研究 |
投稿时间:2024-10-22 修订日期:2024-11-13 点此下载全文 |
引用本文:何万滨,张云峰,杨志军,张文博,周逢海.转移性肾癌亚型的预后评估与预测模型研究[J].医学研究杂志,2025,54(4):122-129 |
DOI:
10.11969/j.issn.1673-548X.2025.04.022 |
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基金项目:甘肃省自然科学基金资助项目(22JR5RA650);甘肃省人民医院院内基金资助项目(23GSSYD-12) |
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中文摘要:目的 本研究旨在利用监测、流行病学和最终结果(Surveillance, Epidemiology, and End Results, SEER)数据库,探讨转移性肾细胞癌(metastatic renal cell carcinoma,mRCC)不同亚型对预后的影响,并建立相应的预测模型。方法 本研究从SEER数据库中提取了2010~2015年确诊为mRCC的2595例患者的临床资料,涵盖年龄、性别、种族、肿瘤直径及转移部位等信息。患者被分为肾透明细胞癌(clear cell renal cell carcinoma,ccRCC)组和非透明细胞癌(non-ccRCC)组。首先,对两组进行Kaplan-Meier生存分析,然后进一步进行单因素和多因素COX回归分析。根据单因素分析结果,确定影响预后的共同因素。结合多因素分析结果,分别为ccRCC组和non-ccRCC组建立预后预测列线图,并对模型的效能进行评估。结果 ccRCC组和non-ccRCC组的中位总生存期(overall survival, OS)分别为18个月和11个月。单因素分析表明,年龄、T分期、骨转移、肝转移以及阳性淋巴结对数概率(log odds of positive lymph nodes,LODDS)是mRCC患者不同亚型的共同预后因素。此外,ccRCC组中还发现性别、肿瘤分化程度、是否接受放疗或化疗、婚姻状况、肿瘤直径、N分期、肺转移及脑转移与预后相关。ccRCC组的OS列线图模型具有良好的预测效能,而non-ccRCC组的模型效能较差,可能与该组样本量较小有关。结论 mRCC不同亚型的预后因素既具有同质性也存在异质性。本研究建立的预后预测模型可为临床医生提供个体化治疗决策支持,从而有望改善患者的预后。 |
中文关键词:转移性肾癌 肾透明细胞癌 EEE数据库 预后 预测模型 肾癌亚型 |
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Prognostic Impact of Different Subtypes of Metastatic Renal Cancer and the Establishment of Predictive Models. |
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Abstract:Objective This study aimed to investigate the prognostic impact of different subtypes of metastatic renal cell carcinoma (mRCC) and establish corresponding predictive models using the Surveillance, Epidemiology, and End Results (SEER) database. Methods Clinical data of 2595 patients diagnosed with mRCC from 2010 to 2015 were extracted from the SEER database, including age, gender, race, tumor size, and metastatic sites. Patients were divided into clear cell renal cell carcinoma (ccRCC) group and non-clear cell renal cell carcinoma (non-ccRCC) group. Firstly, Kaplan-Meier survival analysis was performed for both groups, followed by univariate and multivariate COX regression analysis. Based on the results of univariate analysis, common factors affecting prognosis were determined. Combining the results of multivariate analysis, prognostic nomograms were established for ccRCC group and non-ccRCC group respectively, and the performance of the models was evaluated. Results The median overall survival (OS) of ccRCC group and non-ccRCC group were 18months and 11months respectively. Univariate analysis indicated that age, T stage, bone metastasis, liver metastasis, and log odds of positive lymph nodes (LODDS) were common prognostic factors for different subtypes of mRCC patients. In addition, gender, tumor differentiation degree, whether receiving radiotherapy or chemotherapy, marital status, tumor size, N stage, lung metastasis and brain metastasis were also found to be associated with prognosis in ccRCC group. The OS nomogram model for ccRCC group had good predictive performance while the model for non-ccRCC group had poor performance, which might be related to the small sample size in this group. Conclusion Prognostic factors for different subtypes of mRCC are both homogeneous and heterogeneous. The prognostic prediction model established in this study can provide individualized treatment decision support for clinicians, thereby potentially improving patient prognosis. |
keywords:Metastatic renal cancer Clear cell renal cell carcinoma SEER database Prognosis Predictive models Renal cancer subtypes |
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