Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Chongqing Key Laboratory of Pediatrics, Chongqing, China.
Front Public Health. 2022 Jul 12;10:935521. doi: 10.3389/fpubh.2022.935521. eCollection 2022.
Prostate cancer (PC) is the second leading cause of cancer death in men in the United States after lung cancer in global incidence. Elderly male patients over 65 years old account for more than 60% of PC patients, and the impact of surgical treatment on the prognosis of PC patients is controversial. Moreover, there are currently no predictive models that can predict the prognosis of elderly PC patients undergoing surgical treatment. Therefore, we aimed to construct a new nomogram to predict cancer-specific survival (CSS) in elderly PC patients undergoing surgical treatment.
Data for surgically treated PC patients aged 65 years and older were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to identify independent risk factors for elderly PC patients undergoing surgical treatment. A nomogram of elderly PC patients undergoing surgical treatment was developed based on the multivariate Cox regression model. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the predictive model. Decision curve analysis (DCA) was used to examine the potential clinical value of this model.
A total of 44,975 elderly PC patients undergoing surgery in 2010-2018 were randomly assigned to the training set ( = 31705) and validation set ( = 13270). the training set was used for nomogram development and the validation set was used for internal validation. Univariate and multivariate Cox regression model analysis showed that age, marriage, TNM stage, surgical style, chemotherapy, radiotherapy, Gleason score(GS), and prostate-specific antigen(PSA) were independent risk factors for CSS in elderly PC patients undergoing surgical treatment. The C index of the training set and validation indices are 0.911(95%CI: 0.899-0.923) and 0.913(95%CI: 0.893-0.933), respectively, indicating that the nomogram has a good discrimination ability. The AUC and the calibration curves also show good accuracy and discriminability.
To our knowledge, our nomogram is the first predictive model for elderly PC patients undergoing surgical treatment, filling the gap in current predictive models for this PC patient population. Our data comes from the SEER database, which is trustworthy and reliable. Moreover, our model has been internally validated in the validation set using the C-index,AUC and the and the calibration curve, showed that the model have good accuracy and reliability, which can help clinicians and patients make better clinical decision-making. Moreover, the DCA results show that our nomogram has a better potential clinical application value than the TNM staging system.
在全球范围内，前列腺癌（PC）是美国男性癌症死亡的第二大原因，仅次于肺癌。65 岁以上的老年男性患者占 PC 患者的 60%以上，手术治疗对 PC 患者预后的影响存在争议。此外，目前尚无预测模型可以预测接受手术治疗的老年 PC 患者的预后。因此，我们旨在构建一个新的列线图来预测接受手术治疗的老年 PC 患者的癌症特异性生存（CSS）。
从监测、流行病学和最终结果（SEER）数据库中获取 2010-2018 年间接受手术治疗的年龄在 65 岁及以上的 PC 患者数据。使用单因素和多因素 Cox 回归模型确定接受手术治疗的老年 PC 患者的独立危险因素。基于多因素 Cox 回归模型，为接受手术治疗的老年 PC 患者制定了列线图。一致性指数（C 指数）、受试者工作特征曲线下面积（AUC）和校准曲线用于测试预测模型的准确性和区分度。决策曲线分析（DCA）用于评估该模型的潜在临床价值。
2010-2018 年间共有 44975 例接受手术治疗的老年 PC 患者被随机分配到训练集（=31705）和验证集（=13270）。训练集用于列线图的开发，验证集用于内部验证。单因素和多因素 Cox 回归模型分析显示，年龄、婚姻状况、TNM 分期、手术方式、化疗、放疗、Gleason 评分（GS）和前列腺特异性抗原（PSA）是接受手术治疗的老年 PC 患者 CSS 的独立危险因素。训练集和验证集的 C 指数分别为 0.911（95%CI：0.899-0.923）和 0.913（95%CI：0.893-0.933），表明该列线图具有良好的区分能力。AUC 和校准曲线也显示了良好的准确性和区分度。
据我们所知，我们的列线图是首个用于接受手术治疗的老年 PC 患者的预测模型，填补了当前针对这一 PC 患者人群的预测模型的空白。我们的数据来自 SEER 数据库，该数据库值得信赖。此外，我们的模型已经在验证集中通过 C 指数、AUC 和校准曲线进行了内部验证，表明该模型具有良好的准确性和可靠性，有助于临床医生和患者做出更好的临床决策。此外，DCA 结果表明，与 TNM 分期系统相比，我们的列线图具有更好的潜在临床应用价值。
