Although a survival benefit was observed in patients with metastatic renal cell carcinoma (mRCC) who underwent cytoreductive nephrectomy (CN), there is a lack of effective tools for predicting which individuals are likely to benefit from surgical intervention. Herein, we developed a predictive model using data from the Surveillance, Epidemiology, and End Results (SEER) database. Patients diagnosed with mRCC were screened from the SEER database (2010-2020), supplemented by patients from East Asia. Patients were categorized into surgical and non-surgical groups, with propensity score matching conducted to balance baseline characteristics. Logistic regression analysis was performed to identify independent factors associated with benefits and a nomogram was constructed based on these factors. This study included 11,044 cases from the SEER database and 50 cases from an external validation cohort. CN was identified as an independent protective factor for OS. A nomogram was established, and it performed well in the training and validation sets. The calibration curves and DCA confirmed that the nomogram model could precisely predict the probability of surgical benefit. We used the nomogram to classify surgical patients into benefit and non-benefit groups. Then, we found that OS was significantly higher in the benefit group than in the non-benefit group. The external validation cohort observed the same result (P=0.035). While CN offers potential benefits for patients with mRCC, its applicability varies across the patient population. Our study constructed a nomogram that quantitatively assesses the likelihood of surgical benefit in mRCC patients, facilitating more tailored therapeutic decision-making.

中文翻译：

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基于监测、流行病学和最终结果数据库，开发列线图模型来识别转移性肾细胞癌细胞减灭术的合适候选者

尽管在接受细胞减灭性肾切除术 (CN) 的转移性肾细胞癌 (mRCC) 患者中观察到生存获益，但缺乏有效的工具来预测哪些个体可能从手术干预中受益。在此，我们使用监测、流行病学和最终结果 (SEER) 数据库中的数据开发了一个预测模型。诊断为转移性肾细胞癌的患者是从 SEER 数据库（2010-2020 年）中筛选出来的，并补充了来自东亚的患者。患者被分为手术组和非手术组，并进行倾向评分匹配以平衡基线特征。进行逻辑回归分析以确定与效益相关的独立因素，并根据这些因素构建列线图。这项研究包括来自 SEER 数据库的 11,044 例病例和来自外部验证队列的 50 例病例。 CN 被确定为 OS 的独立保护因素。列线图已经建立，并且在训练和验证集中表现良好。校准曲线和 DCA 证实列线图模型可以精确预测手术获益的概率。我们使用列线图将手术患者分为受益组和非受益组。然后，我们发现受益组的 OS 显着高于非受益组。外部验证队列观察到相同的结果（P=0.035）。虽然 CN 为转移性肾细胞癌患者提供了潜在的益处，但其适用性因患者群体而异。我们的研究构建了一个列线图，可以定量评估 mRCC 患者手术获益的可能性，从而促进更有针对性的治疗决策。