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Understanding variation in disease risk: the elusive concept of frailty.

Aalen OO, Valberg M, Grotmol T, Tretli S - Int J Epidemiol (2014)

Bottom Line: Heterogeneity often manifests itself as clustering of cases in families more than would be expected by chance.We emphasize that apparently moderate familial relative risks can only be explained by strong underlying variation in disease risk between families and individuals.Finally, we highlight the potential impact of frailty variation in the interpretation of standard epidemiological measures such as hazard and incidence rates.

View Article: PubMed Central - PubMed

Affiliation: Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway and Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway o.o.aalen@medisin.uio.no.

No MeSH data available.


The modified familial relative risk, , associated with a diseased sibling as a function of r according to formula (2) in the text, where the two individuals in the family have a common risk component that is gamma distributed with shape parameter . Here r is the familial relative risk from formula (1), that is the familial relative risk without the skewness introduced by the common, gamma distributed component.  is plotted for given values of . Note that  implies .
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dyu192-F4: The modified familial relative risk, , associated with a diseased sibling as a function of r according to formula (2) in the text, where the two individuals in the family have a common risk component that is gamma distributed with shape parameter . Here r is the familial relative risk from formula (1), that is the familial relative risk without the skewness introduced by the common, gamma distributed component. is plotted for given values of . Note that implies .

Mentions: Formula (1) presumes a normal distribution of the risk factor(s), which one would usually assume for simple polygenetic inheritance. Some skewness might be introduced, which might appear more realistic if some genes have a stronger effect than others, for example due to higher penetrance. To investigate the effect of introducing additional skewness in the distribution of the risk factor(s) into the model, we shall assume that two individuals have a common risk component which is gamma distributed with shape parameter . Following Aalen,65 the modified familial relative risk, rF, is given by:(2)rF={1+lnrδ−2(δlnr)1/2}δ.Note that when the shape parameter goes to infinity, this expression will converge to r (because an infinite implies a normal distribution for the common component). Plots of formula (2) as a function of and r are given in Figure 4. The major deviation occurs for which corresponds to an exponential distribution of the common familial risk. This represents a high degree of skewness (Figure 5). It means that members of a minority of families have a much higher risk than others. However, the familial relative risk still appears to be moderate. Figure 5 also includes an illustration of an even more skewed gamma distribution.Figure 4.


Understanding variation in disease risk: the elusive concept of frailty.

Aalen OO, Valberg M, Grotmol T, Tretli S - Int J Epidemiol (2014)

The modified familial relative risk, , associated with a diseased sibling as a function of r according to formula (2) in the text, where the two individuals in the family have a common risk component that is gamma distributed with shape parameter . Here r is the familial relative risk from formula (1), that is the familial relative risk without the skewness introduced by the common, gamma distributed component.  is plotted for given values of . Note that  implies .
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4588855&req=5

dyu192-F4: The modified familial relative risk, , associated with a diseased sibling as a function of r according to formula (2) in the text, where the two individuals in the family have a common risk component that is gamma distributed with shape parameter . Here r is the familial relative risk from formula (1), that is the familial relative risk without the skewness introduced by the common, gamma distributed component. is plotted for given values of . Note that implies .
Mentions: Formula (1) presumes a normal distribution of the risk factor(s), which one would usually assume for simple polygenetic inheritance. Some skewness might be introduced, which might appear more realistic if some genes have a stronger effect than others, for example due to higher penetrance. To investigate the effect of introducing additional skewness in the distribution of the risk factor(s) into the model, we shall assume that two individuals have a common risk component which is gamma distributed with shape parameter . Following Aalen,65 the modified familial relative risk, rF, is given by:(2)rF={1+lnrδ−2(δlnr)1/2}δ.Note that when the shape parameter goes to infinity, this expression will converge to r (because an infinite implies a normal distribution for the common component). Plots of formula (2) as a function of and r are given in Figure 4. The major deviation occurs for which corresponds to an exponential distribution of the common familial risk. This represents a high degree of skewness (Figure 5). It means that members of a minority of families have a much higher risk than others. However, the familial relative risk still appears to be moderate. Figure 5 also includes an illustration of an even more skewed gamma distribution.Figure 4.

Bottom Line: Heterogeneity often manifests itself as clustering of cases in families more than would be expected by chance.We emphasize that apparently moderate familial relative risks can only be explained by strong underlying variation in disease risk between families and individuals.Finally, we highlight the potential impact of frailty variation in the interpretation of standard epidemiological measures such as hazard and incidence rates.

View Article: PubMed Central - PubMed

Affiliation: Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway and Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway o.o.aalen@medisin.uio.no.

No MeSH data available.