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Related Concept Videos

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A complete procedure of testing the hypothesis about a population mean is explained here.
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Testing a Claim about Mean: Unknown Population SD01:21

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A complete procedure of testing a hypothesis about a population mean when the population standard deviation is unknown is explained here.
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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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Population Based Testing for Primary Prevention: A Systematic Review.

Ranjit Manchanda1,2,3, Faiza Gaba4,5

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Population genetic testing for cancer susceptibility genes is more effective and cost-efficient than current methods. This approach identifies more at-risk individuals, enabling earlier cancer prevention strategies.

Keywords:
BRCAJewishcancer preventiongeneral populationgenetic testingpopulation testingprimary prevention

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Area of Science:

  • Genetics and Genomics
  • Preventive Medicine
  • Health Economics

Background:

  • Current genetic testing relies on family history and clinical criteria, which is inefficient and misses many at-risk individuals.
  • This reactive approach requires cancer development before identifying unaffected relatives for targeted prevention.
  • Population-based genetic testing offers a proactive solution to overcome these limitations.

Purpose of the Study:

  • To evaluate the effectiveness and cost-efficiency of population-based genetic testing strategies compared to current clinical-criteria based approaches.
  • To assess the feasibility, acceptability, and clinical utility of large-scale genetic screening for cancer susceptibility genes.
  • To provide evidence supporting changes in guidelines for population-based genetic testing.

Main Methods:

  • Systematic literature search of MEDLINE, EMBASE, Pubmed, CINAHL, and PsychINFO databases.
  • Screening of reference lists, web platforms, Google, and clinical trial registries.
  • Quality assessment of retrieved studies using appropriate checklists.

Main Results:

  • Population-based BRCA testing in the Jewish population is acceptable, feasible, clinically effective, safe, and highly cost-effective.
  • Panel testing for multiple genes (BRCA1/2, RAD51C/D, BRIP1, PALB2) is the most cost-effective strategy for general population women.
  • This strategy can prevent significantly more breast and ovarian cancers than current clinical-criteria based methods.

Conclusions:

  • Population-based genetic testing, particularly panel testing, is a superior strategy for identifying individuals at risk of hereditary cancers.
  • Current guidelines should be updated to incorporate population-based genetic testing for BRCA mutations, especially in at-risk populations.
  • Further implementation studies are needed to expand population-based genetic testing for multiple cancer genes and potentially other chronic diseases.