Suppr超能文献

构建并验证预测鼻腔鼻窦黏膜黑色素瘤患者总生存的列线图。

Development and validation of a nomogram for predicting overall survival in patients with sinonasal mucosal melanoma.

机构信息

Department of Otolaryngology-Head and Neck Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No.1, Shuaifuyuan, Wangfujing, Dongcheng District, 100730, Beijing, China.

出版信息

BMC Cancer. 2024 Feb 7;24(1):184. doi: 10.1186/s12885-024-11888-5.

Abstract

BACKGROUND

Sinonasal mucosal melanoma (SNMM) is a relatively rare malignant tumour with a poor prognosis. This study was designed to identify prognostic factors and establish a nomogram model to predict the overall survival (OS) of patients with SNMM.

METHODS

A total of 459 patients with SNMM were selected from the Surveillance, Epidemiology, and End Results (SEER) database as the training cohort. Univariate and multivariate Cox regression analyses were used to screen for independent factors associated with patient prognosis and develop the nomogram model. In addition, external validation was performed to evaluate the effectiveness of the nomogram with a cohort of 34 patients with SNMM from Peking Union Medical College Hospital.

RESULTS

The median OS in the cohort from the SEER database was 28 months. The 1-year, 3-year and 5-year OS rates were 69.8%, 40.4%, and 30.0%, respectively. Multivariate Cox regression analysis indicated that age, T stage, N stage, surgery and radiotherapy were independent variables associated with OS. The areas under the receiver operating characteristic curves (AUCs) of the nomograms for predicting 1-, 3- and 5-year OS were 0.78, 0.71 and 0.71, respectively, in the training cohort. In the validation cohort, the area under the curve (AUC) of the nomogram for predicting 1-, 3- and 5-year OS were 0.90, 0.75 and 0.78, respectively. Patients were classified into low- and high-risk groups based on the total score of the nomogram. Patients in the low-risk group had a significantly better survival prognosis than patients in the high-risk group in both the training cohort (P < 0.0001) and the validation cohort (P = 0.0016).

CONCLUSION

We established and validated a novel nomogram model to predict the OS of SNMM patients stratified by age, T stage, N stage, surgery and radiotherapy. This predictive tool is of potential importance in the realms of patient counselling and clinical decision-making.

摘要

背景

鼻腔鼻窦黑色素瘤(SNMM)是一种预后较差的罕见恶性肿瘤。本研究旨在确定预后因素并建立诺莫图模型来预测 SNMM 患者的总生存率(OS)。

方法

从监测、流行病学和最终结果(SEER)数据库中选择了 459 名 SNMM 患者作为训练队列。使用单因素和多因素 Cox 回归分析筛选与患者预后相关的独立因素,并建立诺莫图模型。此外,还使用来自北京协和医学院医院的 34 名 SNMM 患者队列进行外部验证,以评估诺莫图的有效性。

结果

SEER 数据库队列的中位 OS 为 28 个月。1 年、3 年和 5 年 OS 率分别为 69.8%、40.4%和 30.0%。多因素 Cox 回归分析表明,年龄、T 分期、N 分期、手术和放疗是与 OS 相关的独立变量。预测 1 年、3 年和 5 年 OS 的诺莫图的受试者工作特征曲线(ROC)下面积(AUC)在训练队列中分别为 0.78、0.71 和 0.71。在验证队列中,预测 1 年、3 年和 5 年 OS 的诺莫图的 AUC 分别为 0.90、0.75 和 0.78。根据诺莫图的总分,患者被分为低危和高危组。在训练队列(P<0.0001)和验证队列(P=0.0016)中,低危组患者的生存预后明显优于高危组患者。

结论

我们建立并验证了一种新的诺莫图模型,用于预测 SNMM 患者的 OS,该模型根据年龄、T 分期、N 分期、手术和放疗进行分层。该预测工具在患者咨询和临床决策方面具有潜在的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5396/10851497/6b87bc410a61/12885_2024_11888_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