Suppr超能文献

基于网络的列线图构建与验证:用于前列腺腺癌伴骨转移的检测和预后评估。

Construction and validation of web-based nomograms for detecting and prognosticating in prostate adenocarcinoma with bone metastasis.

机构信息

Center for Bone, Joint and Sports Medicine, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510630, China.

Guangdong Provincial Key Laboratory of Pharmaceutical Bioactive Substances, Guangdong Pharmaceutical University, Guangzhou, 510006, China.

出版信息

Sci Rep. 2022 Nov 3;12(1):18623. doi: 10.1038/s41598-022-23275-w.

Abstract

Bone metastasis (BM) is one of the most common sites of metastasis in prostate adenocarcinoma (PA). PA with BM can significantly diminish patients' quality of life and result in a poor prognosis. The objective of this study was to establish two web-based nomograms to estimate the risk and prognosis of BM in PA patients. From the Surveillance, Epidemiology, and End Results (SEER) database, data on 308,332 patients diagnosed with PA were retrieved retrospectively. Logistic and Cox regression, respectively, were used to determine independent risk and prognostic factors. Then, We constructed two web-based nomograms and the results were validated by receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA) , and the Kaplan-Meier analyses. The independent risk factors for BM in PA patients included race, PSA, ISUP, T stage, N stage, brain, liver, lung metastasis, surgery, radiation and chemotherapy. The independent prognostic predictors for overall survival (OS) were age, marital status, PSA, ISUP and liver metastasis. Both nomograms could effectively predict risk and prognosis of BM in PA patients according to the results of ROC curves, calibration, and DCA in the training and validation sets. And the Kaplan-Meier analysis illustrated that the prognostic nomogram could significantly distinguish the population with different survival risks. We successfully constructed the two web-based nomograms for predicting the incidence of BM and the prognosis of PA patients with BM, which may assist clinicians in optimizing the establishment of individualized treatment programs and enhancing patients' prognoses.

摘要

骨转移(BM)是前列腺腺癌(PA)最常见的转移部位之一。患有 BM 的 PA 患者的生活质量会显著下降,预后较差。本研究旨在建立两个基于网络的列线图,以估计 PA 患者发生 BM 的风险和预后。我们从监测、流行病学和最终结果(SEER)数据库中回顾性检索了 308332 例诊断为 PA 的患者数据。分别使用逻辑回归和 Cox 回归来确定独立的风险和预后因素。然后,我们构建了两个基于网络的列线图,并通过接收者操作特征(ROC)曲线、校准曲线、决策曲线分析(DCA)和 Kaplan-Meier 分析对结果进行验证。PA 患者发生 BM 的独立风险因素包括种族、PSA、ISUP、T 分期、N 分期、脑转移、肝转移、肺转移、手术、放疗和化疗。总生存(OS)的独立预后预测因素包括年龄、婚姻状况、PSA、ISUP 和肝转移。两个列线图在训练集和验证集中均通过 ROC 曲线、校准和 DCA 的结果有效地预测了 PA 患者发生 BM 的风险和预后。Kaplan-Meier 分析表明,预后列线图可以显著区分具有不同生存风险的人群。我们成功构建了两个用于预测 PA 患者 BM 发生率和 BM 预后的基于网络的列线图,这可能有助于临床医生优化个体化治疗方案的制定,提高患者的预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7877/9633700/99eb28569f74/41598_2022_23275_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验