Department of Urology and Hubei Key Laboratory of Kidney Disease Pathogenesis and Intervention, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, No.141, Tianjin Road, Huangshi, Hubei, 435000, People's Republic of China.
Int Urol Nephrol. 2019 Oct;51(10):1743-1753. doi: 10.1007/s11255-019-02224-z. Epub 2019 Jul 9.
This study aimed to develop and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in patients with prostate cancer.
Clinical data of patients with mPCa between 2010 and 2014 were retrieved retrospectively, and randomized into training (2/3) and validation sets (1/3). Nomograms were built with potential risk factors based on COX regression analysis. Accuracy was validated using the discrimination and calibration curve for the training and validation groups, respectively.
6659 mPCa patients were collected and enrolled, including 4440 in the training set and 2219 in the validation set. Multivariate analysis showed that age, marital status, PSA, biopsy Gleason score, T stage, and bone metastasis were independent risk factors for both OS and CSS. The concordance index (C-index) of OS was 0.735 (95% CI 0.722-0.748) for the internal validation and 0.735 (95% CI 0.717-0.753) for the external validation. For CSS, it was 0.734 (95% CI 0.721-0.747) and 0.742 (95% CI 0.723-0.761), respectively. The nomograms for predicting OS and CSS displayed better discrimination power in both training and validation sets. Moreover, a favorable consistency between the predicted and actual survival probabilities was demonstrated using calibration curves.
The nomograms showed good performances for predicting OS and CSS in patients with prostate cancer. It might be a convenient individualized predictive tool for prognosis in clinical practice.
本研究旨在开发和验证列线图,以预测前列腺癌患者的总生存期(OS)和癌症特异性生存期(CSS)。
回顾性检索了 2010 年至 2014 年间 mPCa 患者的临床数据,并将其随机分为训练集(2/3)和验证集(1/3)。基于 COX 回归分析,使用潜在风险因素构建列线图。分别使用训练组和验证组的判别和校准曲线验证准确性。
共收集并纳入了 6659 例 mPCa 患者,其中 4440 例在训练集中,2219 例在验证集中。多变量分析显示,年龄、婚姻状况、PSA、活检 Gleason 评分、T 分期和骨转移是 OS 和 CSS 的独立危险因素。OS 的一致性指数(C-index)在内部验证中为 0.735(95%CI 0.722-0.748),外部验证中为 0.735(95%CI 0.717-0.753)。CSS 分别为 0.734(95%CI 0.721-0.747)和 0.742(95%CI 0.723-0.761)。在训练和验证组中,预测 OS 和 CSS 的列线图均显示出更好的判别能力。此外,校准曲线表明,预测和实际生存概率之间存在良好的一致性。
列线图在预测前列腺癌患者的 OS 和 CSS 方面表现出良好的性能。它可能是临床实践中一种方便的个体化预后预测工具。