癌症患者手术后死亡的原因:基于人口的队列研究
Yutai Hao1, Chengcai Liang1, Yifang Zhang1,2,3
1State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
International journal of surgery (London, England)
|September 10, 2025
概括
非癌症死亡现在超过癌症死亡在大多数固体瘤手术后,强调需要更好地管理癌症幸存者的心血管和传染性风险.
科学领域:
- 在瘤学瘤学.
- 公共卫生 公共卫生
- 外科手术的结果
背景情况:
- 由于外科手术的进步和术后护理,改善了癌症存活率.
- 缺乏对手术治疗癌症患者的长期死亡率趋势和竞争风险的系统分析.
- 需要数据来为有关术后死亡率的幸存者护理策略提供信息.
研究的目的:
- 在21种固体癌症中量化术后死亡原因的时间模式.
- 确定导致死亡率的主导非癌症风险因素.
- 通过了解死亡率趋势,为生存护理策略提供信息.
主要方法:
- 使用SEER数据库 (1992-2021) 进行回顾性,基于人口的队列研究.
- 分析了3,424,671名患有21种固体癌症的患者 (2,371,058例手术).
- 应用竞争性风险模型来评估因索引癌症,非索引癌症和非癌症原因的累积死亡率.
主要成果:
- 在14种恶性瘤中,非癌症死亡人数超过了指数癌症死亡人数 (48.7%的术后死亡人数),主要是由心血管疾病和感染引起的.
- 到2020年代,非癌症原因成为许多癌症的主要死亡率驱动因素,尽管胰腺,卵巢和脑瘤的指数癌症死亡率仍然很高.
- 手术切除显著增加了非癌症死亡率 (例如肺癌,胰腺癌),突出了加强术后并发症管理的需要.
结论:
- 观察到手术后死亡率的范式转变,非癌症原因现在超过大多数固体瘤的癌症相关死亡.
- 专注于心血管健康和感染预防的多学科护理的紧急整合对于幸存者计划至关重要.
- 优化长期生存需要优先管理癌症幸存者的非癌症并发症.
相关概念视频
01:21Cancer Survival Analysis
650
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...
650
01:23Peripheral Artery Disease V: Postoperative Nursing Management
379
During the postoperative period, it is crucial to focus on maintaining circulation, identifying and managing potential complications, and planning for discharge.Nursing AssessmentVital signs monitoring: Regularly monitor vital signs, including blood pressure, heart rate, respiratory rate, and temperature, to detect early signs of complications such as bleeding and infection.Circulation assessment: Monitor pulses, perform Doppler assessments, and check capillary refill, color, temperature, and...
379
02:49Cancer Therapies
9.8K
Cancer therapies are various modes of treatment, such as surgery, radiation therapy, and chemotherapy that are administered to cancer patients.
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
9.8K
01:20Actuarial Approach
290
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,...
290
01:15Assumptions of Survival Analysis
401
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
401
01:24Kaplan-Meier Approach
581
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
581