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原发性乳腺淋巴瘤患者的流行病学特征和生存预测列线图的建立。

Epidemiological features of primary breast lymphoma patients and development of a nomogram to predict survival.

机构信息

Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.

Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.

出版信息

Breast. 2021 Jun;57:49-61. doi: 10.1016/j.breast.2021.03.006. Epub 2021 Mar 17.

DOI:10.1016/j.breast.2021.03.006
PMID:33774459
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8027901/
Abstract

BACKGROUND

Studies on the epidemiology and prognosis of primary breast lymphoma (PBL) are lack for low incidence. Therefore, we aimed to investigate the epidemiological characteristics of PBL and develop nomograms to predict patient survival.

METHODS

Data of patients who were diagnosed with PBL from 1975 to 2011 and incidence rate of PBL from 1975 to 2017 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Time-varying multivariable Cox regression analysis was performed to identify independent prognostic factors for overall survival (OS) and disease-specific survival (DSS). Nomograms were constructed based on the independent prognostic factors identified in multivariate Cox regression analysis.

RESULTS

A total of 1427 patients diagnosed with PBL were identified with the average age of 67.1 years. The overall incidence of PBL is 1.35/1,000,000 (adjusted to the United States standard population in 2000) from 1975 to 2017, with a significant upward trend by an annual percentage change (APC) of 2.91 (95%CI 2.29-3.94, P < 0.05). Age, sex, race, year of diagnosis, marital status, histological subtype, Ann Arbor Stage, and treatment modality were assessed as independent prognostic factors for OS and DSS by multivariable Cox regression (P < 0.05). Nomograms were constructed to predict the 1-, 3-, 5-, and 10- year OS and DSS. The concordance index (C-index) and calibration plots showed robustness and accuracy of the nomogram.

CONCLUSION

The overall incidence of PBL was steadily increasing over the past four decades. Nomograms constructed can predicting 1-, 3-, 5-, and 10-year OS and identify patients with high-risk PBL.

摘要

背景

由于原发性乳腺淋巴瘤(PBL)发病率较低,因此关于其流行病学和预后的研究较为缺乏。因此,我们旨在研究 PBL 的流行病学特征,并构建列线图以预测患者的生存情况。

方法

从 SEER 数据库中提取了 1975 年至 2011 年期间诊断为 PBL 的患者数据和 1975 年至 2017 年期间 PBL 的发病率数据。采用时变多变量 Cox 回归分析确定总生存期(OS)和疾病特异性生存期(DSS)的独立预后因素。基于多变量 Cox 回归分析中确定的独立预后因素构建列线图。

结果

共确定了 1427 例诊断为 PBL 的患者,平均年龄为 67.1 岁。1975 年至 2017 年,PBL 的总体发病率为 1.35/1,000,000(调整至 2000 年美国标准人口),呈逐年上升趋势,年变化百分比(APC)为 2.91(95%CI 2.29-3.94,P<0.05)。多变量 Cox 回归分析显示,年龄、性别、种族、诊断年份、婚姻状况、组织学亚型、Ann Arbor 分期和治疗方式是 OS 和 DSS 的独立预后因素(P<0.05)。构建了预测 1、3、5 和 10 年 OS 和 DSS 的列线图。一致性指数(C-index)和校准图表明列线图具有稳健性和准确性。

结论

在过去的四十年中,PBL 的总体发病率呈稳步上升趋势。构建的列线图可预测 1、3、5 和 10 年 OS,并识别出高危 PBL 患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/fd99fdae1361/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/de04f6c2e472/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/5b23f4436aa8/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/fcf651c92f8d/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/c1280ddd0482/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/3fc155888334/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/5b43ff5e39d2/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/438cc263fdf0/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/67744a39753f/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/c67c6cf8f8df/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/da457a86d38b/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/fd99fdae1361/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/de04f6c2e472/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/5b23f4436aa8/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/fcf651c92f8d/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/c1280ddd0482/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/3fc155888334/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/5b43ff5e39d2/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/438cc263fdf0/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/67744a39753f/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/c67c6cf8f8df/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/da457a86d38b/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1a8/8027901/fd99fdae1361/gr11.jpg

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