Suppr超能文献

列线图预测原发性肢体平滑肌肉瘤患者的癌症特异性和总体生存。

Nomograms Predict Cancer-Specific and Overall Survival of Patients With Primary Limb Leiomyosarcoma.

机构信息

Department of Orthopaedic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou, 310009, P. R. China.

Division of Reproductive Medicine & Infertility, The Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou, 310009, P. R. China.

出版信息

J Orthop Res. 2019 Jul;37(7):1649-1657. doi: 10.1002/jor.24298. Epub 2019 May 9.

Abstract

To date, there have been no data to predict the survival of patients with leiomyosarcoma from soft limb tissue because of the rarity of this disease. Nomograms have been widely applied in clinical oncology to precisely predict the survival of individual patients. This was a retrospective study to construct and validate nomograms to predict the cancer-specific survival (CSS) and overall survival (OS) of patients with primary limb leiomyosarcoma (PL-LMS). A total of 1,208 patients with LMS from limb soft tissue were collected from the Surveillance, Epidemiology, and End Results database from 1975 to 2015. We identified independent prognostic factors using univariate and multivariate Cox analyses. These prognostic factors were then included in the nomograms to predict 3- and 5-year CSS and OS rates. Finally, we validated the nomograms internally and externally. A total of 1208 patients were collected and divided into validation (N = 604) and training (N = 604) groups. Age, race, grade, tumor size, stage, and surgical types were demonstrated as independent prognostic factors for CSS and OS (all p < 0.05) and further used to construct the nomograms. The concordance index (C-index) for CSS was 0.857 for internal validation and 0.727 for external validation. The C-index for OS and CSS both demonstrated that the nomogram prediction agreed perfectly with actual survival. We developed nomograms to predict CSS and OS in PL-LMS patients and can benefit from using them to identify patients' mortality risk and make more precise assessments regarding survival. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1649-1657, 2019.

摘要

截至目前,由于这种疾病的罕见性,还没有数据可以预测软组织肢体平滑肌肉瘤患者的生存情况。列线图已广泛应用于临床肿瘤学,以精确预测个体患者的生存情况。本研究回顾性地构建和验证了列线图,以预测原发性肢体平滑肌肉瘤(PL-LMS)患者的癌症特异性生存(CSS)和总生存(OS)。从 1975 年至 2015 年,我们从监测、流行病学和最终结果数据库中收集了 1208 例来自肢体软组织的 LMS 患者。我们使用单变量和多变量 Cox 分析确定独立的预后因素。然后,这些预后因素被纳入列线图中,以预测 3 年和 5 年 CSS 和 OS 率。最后,我们对列线图进行了内部和外部验证。共收集 1208 例患者,分为验证(N=604)和训练(N=604)组。年龄、种族、分级、肿瘤大小、分期和手术类型被证明是 CSS 和 OS 的独立预后因素(均 P<0.05),并进一步用于构建列线图。CSS 的一致性指数(C-index)内部验证为 0.857,外部验证为 0.727。OS 和 CSS 的 C-index 均表明,列线图预测与实际生存完全一致。我们开发了用于预测 PL-LMS 患者 CSS 和 OS 的列线图,可以帮助我们识别患者的死亡风险,并对生存情况做出更精确的评估。2019 年骨科研究协会。由 Wiley 期刊出版公司出版。J Orthop Res 37:1649-1657, 2019.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验