scholarly journals Sampling Distributions of Critical Illness Insurance Premium Rates: Breast and Ovarian Cancer

2008 ◽  
Vol 38 (02) ◽  
pp. 527-542 ◽  
Author(s):  
Li Lu ◽  
Angus Macdonald ◽  
Howard Waters

Evaluating the risk of disorders in long-term insurance often relies on rates of onset estimated from quite small epidemiological studies. These estimates can carry considerable uncertainty, hence so may functions of them, such as a premium rate. In the case of genetic disorders, where it may be required to demonstrate the reliability of genetic information as a risk factor, such uncertainty may be material. Epidemiological studies publish their results in a variety of forms and it is rarely easy to estimate the sampling distribution of a premium rate without access to the original data. We found a large study of breast and ovarian cancer that cited relative risks of breast and ovarian cancer onset, with confidence intervals, in 10-year age groups. We obtained critical illness premium rates and their sampling distributions by parametric bootstrapping, and investigated the effect of possible patterns of sampling correlations. We found that this study provides ample statistical evidence that known BRCA1 or BRCA2 mutations, or a typical family history of breast or ovarian cancer, are reliable risk factors, but the sampling covariances of the relative risks could be important at some ages and terms. Studies that cite only standard errors of parameter estimates erect a small but awkward barrier between the models they describe, and some important actuarial questions.

2008 ◽  
Vol 38 (2) ◽  
pp. 527-542 ◽  
Author(s):  
Li Lu ◽  
Angus Macdonald ◽  
Howard Waters

Evaluating the risk of disorders in long-term insurance often relies on rates of onset estimated from quite small epidemiological studies. These estimates can carry considerable uncertainty, hence so may functions of them, such as a premium rate. In the case of genetic disorders, where it may be required to demonstrate the reliability of genetic information as a risk factor, such uncertainty may be material. Epidemiological studies publish their results in a variety of forms and it is rarely easy to estimate the sampling distribution of a premium rate without access to the original data. We found a large study of breast and ovarian cancer that cited relative risks of breast and ovarian cancer onset, with confidence intervals, in 10-year age groups. We obtained critical illness premium rates and their sampling distributions by parametric bootstrapping, and investigated the effect of possible patterns of sampling correlations. We found that this study provides ample statistical evidence that known BRCA1 or BRCA2 mutations, or a typical family history of breast or ovarian cancer, are reliable risk factors, but the sampling covariances of the relative risks could be important at some ages and terms. Studies that cite only standard errors of parameter estimates erect a small but awkward barrier between the models they describe, and some important actuarial questions.


2003 ◽  
Vol 2003 (1) ◽  
pp. 28-50 ◽  
Author(s):  
Angus S. Macdonald ◽  
Howard R. Waters ◽  
Chessman T. Wekwete

2006 ◽  
Vol 1 (2) ◽  
pp. 319-343 ◽  
Author(s):  
A. S. Macdonald ◽  
K. R. McIvor

ABSTRACTMutations in the BRCA1 and BRCA2 genes confer very high risk of breast cancer (BC), but only account for about 25% of the observed familial clustering of BC. Antoniou et al. (2002) proposed a model which included the BRCA1 and BRCA2 genes, and a polygenic component which acted multiplicatively on the rate of onset of BC. We use this model to find premium rates for critical illness insurance: (a) given knowledge of an applicant's polygenotype; and (b) given knowledge of a family history of BC or ovarian cancer. We find that the polygenic component causes large variation in premium rates even among non-mutation carriers, therefore affecting the whole population. In some cases the polygenic contribution is protective enough to reduce or remove the additional risk of a BRCA1/2 mutation, leading to cases where it will be advantageous to disclose genetic test results which are adverse in absolute terms. Premiums based on family history are lower than those found in an earlier study which attributed all genetic BC risk to the BRCA1/2 genes.


2007 ◽  
Vol 2 (2) ◽  
pp. 413-419

A.A.S. 1, 319-343 (2007)Application of a Polygenic Model of Breast and Ovarian Cancer to Critical Illness Insurance


Sign in / Sign up

Export Citation Format

Share Document