选择性盆腔淋巴结放射治疗和不良风险前列腺癌患者的死亡风险:随机后分析分析
Mutlay Sayan1, Ming-Hui Chen2, Marian Loffredo1
1Department of Radiation Oncology, Brigham and Women's Hospital and Dana Farber Cancer Institute, Boston, MA.
概括
全盆腔放射治疗 (WPRT) 可能会降低患有不利风险前列腺癌 (PC) 的年轻男性的死亡率. 长期数据显示,WPRT显著降低了65岁以下男性的全因和前列腺癌特异性死亡风险.
科学领域:
- 在瘤学瘤学.
- 辐射瘤学 辐射瘤学
- 临床试验 临床试验
背景情况:
- 当代随机试验支持针对局部,不利风险前列腺癌 (PC) 的全骨盆放射治疗 (WPRT).
- 关于WPRT对死亡率的影响的长期数据有限.
- 评估WPRT与死亡率的关联对于治疗指南至关重要.
研究的目的:
- 评估辐射治疗量与全因死亡率 (ACM) 和PC特定死亡率 (PCSM) 之间的长期关联.
- 调查WPRT对不良风险PC男性死亡率的影响.
- 为了确定年龄是否会改变WPRT对死亡率结果的影响.
主要方法:
- 一个随机临床试验,涉及350名男性,从2005年至2015年具有局部,不利风险的PC.
- 患者接受了雄激素剥夺疗法 (ADT) 和RT加多西或ADT和RT.
- 多变量回归分析评估了辐射治疗量与死亡率之间的关联,调整了共变量,并包括了年龄相互作用术语.
主要成果:
- 随访时间中位数为10.2年后,死亡人数为89人 (25.43%),其中42人死于PC.
- 在350名患者中,88名 (25.14%) 接受了WPRT.
- 在65岁以下的男性中,WPRT与明显降低ACM风险 (AHR,0.33;P = .04) 和降低PCSM风险 (AHR,0.17;P = .09) 的趋势有关.
结论:
- 全盆腔辐射疗法 (WPRT) 表明,在被诊断患有不利风险前列腺癌的年轻男性中,有可能降低死亡率.
- 观察到的WPRT对死亡的好处是特定于65岁以下的患者.
- 这些发现表明,WPRT可能是选择晚期前列腺癌的年轻患者群体的有价值的治疗策略.
相关概念视频
Actuarial Approach
384
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
384
Comparing the Survival Analysis of Two or More Groups
712
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
712
Cancer Survival Analysis
863
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
863


