相关实验视频

Updated: Sep 13, 2025

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

Published on: March 8, 2022

用随机,固定和混合效应模型对转移性黑色素瘤免疫治疗中的生存,风险和治疗有效性的比较元分析

Jelena Ivetić¹, Jovana Dedeić¹, Srđan Milićević¹

¹Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia.

Journal of clinical medicine

|July 29, 2025

概括

对转移性黑色素瘤的组合免疫疗法比单一疗法提供更高的生存益处,但增加了与免疫相关的不良事件的风险. 这一元分析为明智的治疗决策提供了可靠的疗效和毒性估计.

科学领域:

在瘤学瘤学.
免疫治疗是一种免疫疗法.
临床试验临床试验

背景情况:

免疫检查点抑制剂 (ICI) 已经改变了转移性黑色素瘤的治疗方法.
组合ICI治疗显示出更好的反应和生存,但更高的免疫相关不良事件 (irAEs).
在治疗决策中,平衡利益和风险至关重要.

研究的目的:

系统地审查和元分析临床试验,比较ICI单疗法和晚期黑色素瘤组合疗法.
为了提供可靠的治疗疗效和毒性估计,考虑研究变异性.

主要方法:

14项临床试验 (>5000名患者) 的系统审查和元分析.
对ICI单疗法 (尼沃卢马布,伊皮利穆马布,潘布罗利祖马布) 与组合疗法 (尼沃卢马布+伊皮利穆马布) 的比较.
利用通用线性混合模型 (GLMMs) 进行结果综合和生存分析.

主要成果:

组合疗法产生了更高的整体反应 (52.2%对31.6%) 和5年生存率 (OS 55.7%对34.3%;PFS 39.0%对17.2%).
组合疗法增加了irAEs (93.2%与81.9%相比),在严重毒性方面一致.
GLMMs提供了可靠的估计和模拟的生存动态.

结论:

组合免疫疗法在转移性黑色素瘤中提供了更大的长期临床益处,但毒性增加.
基于模型的元分析,特别是使用GLMMs,提高了疗效和风险估计的可靠性.
这些发现支持在晚期黑色素瘤治疗中基于证据的决策.

关键词:

临床益处临床益处固定效应模型的固定效应模型.一般化的线性混合模型.免疫检查点抑制剂免疫检查点抑制剂与免疫相关的不良事件.黑色素瘤免疫疗法免疫疗法这是一个元分析.总体存活率总体存活率没有进展的生存率.随机效应模型的随机效应模型.治疗风险治疗风险

更多相关视频

A 3D Organotypic Melanoma Spheroid Skin Model

A 3D Organotypic Melanoma Spheroid Skin Model

Published on: May 18, 2018

Predictive Immune Modeling of Solid Tumors

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

相关概念视频

Cancer Survival Analysis

Cancer Survival Analysis

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...

Comparing the Survival Analysis of Two or More Groups

Comparing the Survival Analysis of Two or More Groups

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...

Tumor Immunotherapy

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.

Kaplan-Meier Approach

Kaplan-Meier Approach

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,...