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相关概念视频

Cancer Survival Analysis01:21

Cancer Survival Analysis

311
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...
311
Multiple Regression01:25

Multiple Regression

2.9K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
2.9K
Relative Risk01:12

Relative Risk

99
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
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Cancer Prevention02:59

Cancer Prevention

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Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
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Multicompartment Models: Overview01:14

Multicompartment Models: Overview

70
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
70
Odds Ratio01:09

Odds Ratio

86
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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相关实验视频

Updated: May 17, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

187

使用简单的多变量模型预测结肠直肠癌风险.

Gillian S Dite1, Chi Kuen Wong1, Aviv Gafni1

  • 1Genetic Technologies Limited, Fitzroy, Victoria, Australia.

PloS one
|May 13, 2025
PubMed
概括

新模型使用多基因风险分数和家族病史准确地分层结直肠癌风险,使高风险个体能够进行个性化查. 这种方法可以改善早期检测和降低风险的策略,从而改善患者的治疗结果.

科学领域:

  • 遗传学和基因组学 遗传学和基因组学
  • 流行病学 流行病学
  • 在瘤学瘤学.

背景情况:

  • 对结直肠癌 (CRC) 风险的精确人口分层对于有针对性的查和降低风险的干预措施至关重要.
  • 现有的风险预测模型可能无法完全捕捉个人CRC易感性.
  • 英国生物银行为开发和验证强大的风险预测模型提供了大量队列.

研究的目的:

  • 在未受影响的英国人口中开发和验证10年CRC风险的新风险预测模型.
  • 为了比较包含多基因风险评分 (PRS) 和家族史的多变量和简化模型的性能.
  • 识别可能受益于个性化查和风险降低策略的个人.

主要方法:

  • 一项基于人口的队列研究,对近40万英国生物银行参与者 (40-69岁) 进行了基因确定的英国祖先.
  • 开发两个模型: (i) 多变量 (家族史,PRS,临床因素) 和 (ii) 简单 (家族史,PRS),分别用于女性和男性.
  • 考克斯回归模型用于开发 (70%的培训数据) 和绩效评估 (30%的测试数据),包括歧视 (哈雷尔的C指数) 和校准.

主要成果:

  • 与测试数据集中的简单模型相比,新的多变量模型显示出优异的歧视 (例如,Harrell的C指数为女性0.690和男性0.699).

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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相关实验视频

Last Updated: May 17, 2025

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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

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Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
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Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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  • 这两种新模型都显示了比现有模型更好的歧视,具有统计学上显著的变化 (女性P=0.02,男性P=0.01).
  • 该研究确定了患结直肠癌风险增加的特定亚组.
  • 结论:

    • 开发的多变量和简单的风险预测模型有效地根据10年结直肠癌风险对个人进行分层.
    • 这些模型结合了多基因风险得分和家族史,为识别有风险的个体提供了更好的歧视.
    • 这些发现支持基于遗传和家族风险因素的个性化查和风险降低策略的实施.