p53多态和宫癌风险之间的关联:更新的元分析
Xi-Qin Zhang1, Xiao-Hui Bai2, Hui-Zhen Zhang1
1Department of Gynaecology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, China.
Frontiers in oncology
|March 10, 2025
概括
这次元分析发现,尽管最初的统计学意义,但p53rs1042522的多态性与子宫癌风险没有可靠的关联. 同样,p53 rs17878362的多态性也没有显示出与子宫癌风险的显著联系.
科学领域:
- 遗传学和基因组学 遗传学和基因组学
- 癌症流行病学 癌症流行病学
- 分子生物学分子生物学
背景情况:
- 关于p53基因多态 (rs1042522和rs17878362) 与子宫癌风险之间的关联,存在相互矛盾的发现.
- 以前的研究和元分析得出了相互矛盾的结论,需要进一步调查.
研究的目的:
- 进行更新的元分析,以澄清p53rs1042522和rs17878362多态度与患子宫癌的风险之间的关联.
- 批判性地评估报告的关联的可靠性.
主要方法:
- 在多个数据库 (PubMed,Medline,Ovid,Embase,CNKI,China Wanfang) 进行了全面的文献搜索.
- 统计学关联是使用几率比率 (OR) 和95%置信区间 (CI) 来评估的.
- 使用虚假阳性报告概率 (FPRP),贝叶斯虚假发现概率 (BFDP) 和威尼斯标准来评估显著关联的可信度.
主要成果:
- 起初,p53 rs1042522多态性似乎在各种分析和子组 (例如,高加索人,亚洲人) 中降低了子宫癌风险.
- 在p53rs17878362多态和子宫癌风险之间没有发现显著的关联.
- 可靠性分析 (FPRP,BFDP,威尼斯标准) 表明,对于rs1042522的所有统计学上显著的关联被认为是"不可靠的".
结论:
- 在考虑研究结果的可信性之后,p53 rs1042522多态性与子宫癌风险没有可靠的关联.
- p53 rs17878362的多态性与子宫癌风险无关.
更多相关视频
08:43Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
7.8K
09:38Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
Published on: November 14, 2017
14.8K
相关概念视频
Correlation
11.5K
In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
11.5K
Cause and Effect
10.8K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.8K
Correlation and Regression
1.2K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
1.2K
Correlation and Causation
37.3K
Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
37.3K
Ligand Binding and Linkage
4.7K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked. In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
4.7K
Correlations
32.4K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
32.4K
