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用于去势抵抗性前列腺癌和初发骨转移前列腺癌患者生存结局的新型列线图。

Novel nomograms for castration-resistant prostate cancer and survival outcome in patients with de novo bone metastatic prostate cancer.

机构信息

Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.

Department of Urology and Comprehensive Cancer Center, University of California Davis, Sacramento, CA, USA.

出版信息

BJU Int. 2018 Dec;122(6):994-1002. doi: 10.1111/bju.14398. Epub 2018 Jun 7.

DOI:10.1111/bju.14398
PMID:29772102
Abstract

OBJECTIVES

To develop nomograms predicting the incidence of castration-resistant prostate cancer (CRPC) and overall survival (OS) for de novo metastatic prostate cancer (PCa).

PATIENTS AND METHODS

Data from 449 patients with de novo metastatic PCa were retrospectively analysed. Patients were randomly divided into a training (n = 314, 70%) and a validation cohort (n = 135, 30%). Predictive factors were selected using a Cox proportional hazards model and were further used for building predictive models. The outcomes were incidence of CRPC and OS.

RESULTS

Predictive factors included: Gleason score (GS), intraductal carcinoma of the prostate (IDC-P), Eastern Cooperative Oncology Group status, and alkaline phosphatase, haemoglobin and prostate-specific antigen levels. IDC-P and GS were the strongest prognosticators for both the incidence of CRPC and OS. Nomograms for predicting CRPC and OS had an internal validated concordance index of 0.762 and 0.723, respectively. Based on the β coefficients of the final model, risk classification systems were constructed. For those with favourable, intermediate and poor prognosis, the median time to CRPC was 62.6, 28.0 and 13.0 months (P < 0.001), respectively; and the median OS was not reached, 55.0 and 33.0 months, respectively (P < 0.001).

CONCLUSIONS

We developed two novel nomograms to predict the incidence of CRPC and OS for patients with de novo metastatic PCa. These tools may assist in physician decision-making and the designing of clinical trials.

摘要

目的

开发预测初发转移性前列腺癌(PCa)发生去势抵抗性前列腺癌(CRPC)和总生存期(OS)的列线图。

患者和方法

回顾性分析了 449 例初发转移性 PCa 患者的数据。患者被随机分为训练队列(n=314,70%)和验证队列(n=135,30%)。使用 Cox 比例风险模型选择预测因素,并进一步用于构建预测模型。结局为 CRPC 发生率和 OS。

结果

预测因素包括:Gleason 评分(GS)、前列腺导管内癌(IDC-P)、东部合作肿瘤学组(ECOG)状态以及碱性磷酸酶、血红蛋白和前列腺特异性抗原水平。IDC-P 和 GS 是预测 CRPC 和 OS 的最强预后因素。预测 CRPC 和 OS 的列线图内部验证一致性指数分别为 0.762 和 0.723。根据最终模型的β系数,构建了风险分类系统。对于预后良好、中等和差的患者,CRPC 的中位时间分别为 62.6、28.0 和 13.0 个月(P<0.001);中位 OS 分别为未达到、55.0 和 33.0 个月(P<0.001)。

结论

我们开发了两种新的列线图来预测初发转移性 PCa 患者发生 CRPC 和 OS 的概率。这些工具可能有助于医生做出决策和设计临床试验。

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