成年人骨的原发性扩散性大B细胞淋巴瘤:一个基于SEER人口的SEER研究
Jing Li1, Xiangpeng Li, Tong Gao
1Department of Clinical Pharmacy, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Medicine
|October 29, 2024
概括
这项研究确定了原发性骨扩散性大B细胞淋巴瘤 (PB-DLBCL) 的临床特征和生存率. 开发的诺姆图准确预测患者的存活率,有助于优化这种罕见淋巴瘤的治疗.
科学领域:
- 血液学 血液学 血液学
- 在瘤学瘤学.
- 流行病学 流行病学
背景情况:
- 原发性扩散性大B细胞骨淋巴瘤 (PB-DLBCL) 是一种罕见的突节性淋巴瘤,临床特征和结局不明确.
- 了解预后因素和生存率对于管理成人PB-DLBCL患者至关重要.
研究的目的:
- 研究成年PB-DLBCL的临床表现,分期,治疗选择,预后因素和生存结果.
- 开发PB-DLBCL患者的生存结果的预测模型 (nomograms).
主要方法:
- 利用了成人PB-DLBCL患者的监测,流行病学和最终结果 (SEER) 计划 (2000-2018) 的数据.
- 采用卡普兰-梅尔对生存率和考克斯回归 (包括BESS和LASSO) 的分析,用于名ogram构造.
- 使用一致性指数,校准曲线和决策曲线分析 (DCA) 验证的诺姆图.
主要成果:
- 扩散性大B细胞淋巴瘤 (DLBCL) 占主要骨淋巴瘤的67.51%,通常影响脊椎和下肢.
- 3,5,10年和15年的总生存率分别为74.9%,70.5%,60.0%和49.9%.
- 针对OS和疾病特异性存活率 (DSS) 的诺姆图识别了关键预测因素,包括年龄,安纳伯阶段,主要地点,治疗,婚姻状况,骨损伤数量和诊断年份.
结论:
- 为PB-DLBCL开发的诺米图显示出在预测患者存活率方面具有良好的准确性和临床实用性.
- 这些预测模型可以帮助临床医生优化PB-DLBCL的成人患者的治疗策略.
- 进一步的研究可以完善对这种罕见的血液性恶性瘤的理解和管理.
相关概念视频
Cancers Originate from Somatic Mutations in a Single Cell
Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
Cancers Originate from Somatic Mutations in a Single Cell
Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...


