Suppr超能文献

列线图预测脊柱软骨肉瘤患者总生存和癌症特异性生存的建立与验证。

Development and Validation of Nomograms Predicting Overall and Cancer-Specific Survival of Spinal Chondrosarcoma Patients.

机构信息

Department of Orthopaedics, Huashan Hospital, Fudan University, Shanghai, China.

Shanghai Medical College, Fudan University, Shanghai, China.

出版信息

Spine (Phila Pa 1976). 2018 Nov 1;43(21):E1281-E1289. doi: 10.1097/BRS.0000000000002688.

Abstract

STUDY DESIGN

Retrospective analysis.

OBJECTIVE

To develop and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS) of spinal chondrosarcoma patients.

SUMMARY OF BACKGROUND DATA

In this era of personalized medicine, data those are available to predict the survival of spinal chondrosarcoma patients are still limited due to the rarity of the disease. Nomogram, which has been widely used in clinical oncology, could conveniently and precisely predict survival outcome for individual patient.

METHODS

We retrospectively collected 450 spinal chondrosarcoma patients from the Surveillance, Epidemiology, and End Results (SEER) database between 1984 and 2013. Univariate log-rank and multivariate Cox analyses were used to identify independent prognostic factors. These prognostic factors were included in the nomograms, which predict 3- and 5-year OS and CSS rate. The nomograms were bootstrap validated internally and externally.

RESULTS

A total of 450 patients were collected and randomly assigned into the training (n = 225) and validation (n = 225) cohorts. Age, histologic subtype, grade, tumor size, stage, and surgery were identified as independent prognostic factors for OS and CSS (all P < 0.05) and were further incorporated to construct the nomograms. The concordance indices (C-indices) for internal validation of OS and CSS prediction were 0.807 and 0.821, while for external validation of OS and CSS prediction were 0.756 and 0.767. Internal and external calibration plots both revealed an excellent agreement between nomogram prediction and actual survival.

CONCLUSION

Nomograms were developed to predict OS and CSS for spinal chondrosarcoma patients. The nomograms could assist clinicians in making more accurate survival evaluation and identifying patients with high risk of mortality.

LEVEL OF EVIDENCE

摘要

研究设计

回顾性分析。

目的

建立并验证预测脊柱软骨肉瘤患者总生存(OS)和癌症特异性生存(CSS)的列线图。

背景数据概要

在个体化医学时代,由于脊柱软骨肉瘤的罕见性,可用的数据仍然有限,无法准确预测脊柱软骨肉瘤患者的生存情况。列线图已广泛应用于临床肿瘤学,可以方便、准确地预测个体患者的生存结局。

方法

我们从 1984 年至 2013 年期间的监测、流行病学和最终结果(SEER)数据库中回顾性收集了 450 例脊柱软骨肉瘤患者。单因素对数秩检验和多因素 Cox 分析用于识别独立的预后因素。这些预后因素被纳入列线图中,用于预测 3 年和 5 年的 OS 和 CSS 率。列线图通过内部和外部的自举法进行验证。

结果

共收集了 450 例患者,随机分为训练队列(n=225)和验证队列(n=225)。年龄、组织学亚型、分级、肿瘤大小、分期和手术被确定为 OS 和 CSS 的独立预后因素(均 P<0.05),并进一步纳入列线图的构建。OS 和 CSS 预测的内部验证一致性指数(C 指数)分别为 0.807 和 0.821,而 OS 和 CSS 预测的外部验证 C 指数分别为 0.756 和 0.767。内部和外部校准图均显示列线图预测与实际生存之间具有极好的一致性。

结论

我们建立了预测脊柱软骨肉瘤患者 OS 和 CSS 的列线图。这些列线图可以帮助临床医生更准确地进行生存评估,并识别出具有高死亡率风险的患者。

证据水平

4 级。

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