The Genetics of Breast and Ovarian Cancer II: A Model of Critical Illness Insurance

Macdonald, Angus S.; Waters, Howard R.; Wekwete, Chessman T

doi:10.1080/03461230308485

Cited by 26 publications

(28 citation statements)

References 6 publications

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“…Unfortunately, onset rates are of much more use to actuaries.) We can only conclude that actuaries must highlight the possible lack of robustness in such models, and even quite crude sensitivity tests (such as the arbitrary reductions in onset rates in Macdonald, Waters & Wekwete (2003)) might be advisable. It is then up to assessors, such as GAIC in the UK, to judge the evidence.…”

Section: Application To Sibshipsmentioning

confidence: 99%

“…Properly designed studies are strongly advocated, but in their absence the data that are to hand will be analysed, often with some approximate adjustment for ascertainment bias. Actuaries have to use caution when applying these results to questions of insurance pricing; for example, Macdonald, Waters & Wekwete (2003) reduced published onset rates of breast and ovarian cancer associated with BRCA1 and BRCA2 mutations by 50% and 75%, to allow for possible unquantified ascertainment bias.…”

Section: Likelihoodsmentioning

confidence: 99%

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Survival Analysis on Pedigrees: A Marked Point Process Model

Macdonald¹

2010

ASTIN Bull.

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Regulation of insurers' use of genetic information means actuaries are interested in age-at-onset of genetic disorders. Arjas & Haara (1984) suggested marked point processes (MPPs) as useful models for life history data with complex covariates. Age-at-onset distributions (or equivalently, hazard rates) in respect of inherited disorders are often estimated from pedigrees, which are life histories with unusually complex covariates, as well as strong dependencies induced by shared genes. Since Elston (1973) parametric models have often been used, conditioning the likelihood on known genotypes. However, a genotype identified by a presymptomatic genetic test is a form of internal covariate (Kalbfleisch & Prentice, 2002). We propose a very general MPP model of a pedigree, including presymptomatic genetic testing, ('the full model') and show under what circumstances the partial model leading to Elston's likelihood is valid. In practice, pedigrees are often ascertained retrospectively. Many such events can be modelled by augmenting the natural filtration of the MPP. We show that, except in simple special cases, the partial model is no longer valid, and the resulting likelihoods appear to be intractable. In particular, ascertainment interacts even with independent censoring so that likelihoods no longer factorize. For one simple special case -studies of sibships -we generalise a classical result to age-at-onset data. We conclude that the study of genetic conditions with variable age at onset gains insights from the underlying principles of survival analysis in their modern form, but that great care is needed in translating epidemiological studies into actuarial models.keywords

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Section: Application To Sibshipsmentioning

confidence: 99%

Section: Likelihoodsmentioning

confidence: 99%

Survival Analysis on Pedigrees: A Marked Point Process Model

Macdonald¹

2010

ASTIN Bull.

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“…The small discontinuity in the incidence rates in respect of females is caused by the introduction of breast cancer screening in the United Kingdom in 1988 (see Macdonald, Waters, and Wekwete 2003a). Note that we have not attempted to remove cases of APKD from the numbers of kidney failure cases included in the "other minor causes" adjustment.…”

Section: Figurementioning

confidence: 99%

Adult Polycystic Kidney Disease and Critical Illness Insurance

Gutiérrez

F.F.A.

2003

North American Actuarial Journal

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Adult polycystic kidney disease (APKD) is a single-gene autosomal dominant genetic disorder leading to end-stage renal disease (ESRD, meaning kidney failure). It is associated with mutations in at least two genes, APKD1 and APKD2, but diagnosis is mostly by ultrasonography. We propose a model for critical illness (CI) insurance and estimate rates of onset of ESRD from APKD using two studies. Other events leading to claims under CI policies are included in the model, which we use to study (a) extra premiums under CI policies if the presence of an APKD mutation is known, and (b) the possible costs arising from adverse selection if this information is unavailable to insurers. The extra premiums are typically very high, but because APKD is rare, the possible cost of adverse selection is low. However, APKD is just one of a significant number of single-gene disorders, and this benign conclusion cannot be assumed to apply to all genetic disorders taken together. Moreover, ignoring known genetic risks in underwriting sets a precedent that could have unintended consequences for the underwriting of nongenetic risks of similar magnitude.

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“…We shall see some examples from this, by way of introducing models for adverse selection. Later work has concentrated on measuring the impact of specific genes, including Lemaire et al (2000), , Macdonald, Waters & Wekwete (2003a, 2003b, Pokorski & Ohlmer (2000) on the BRCA1 and BRCA2 genes linked to familial breast and ovarian cancer; Smith (1998) on Huntington's disease; and Macdonald & Pritchard (2000, 2001 and Warren et al (1999) on Alzheimer's disease. Surprisingly, this short list includes most of the quantitative financial work on genetics and insurance.…”

Section: Human Genetics and Insurancementioning

confidence: 99%

Genetics and health costs: some actuarial models

Macdonald¹

2002

Law, Probability and Risk

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Concerns have been raised about the implications of genetics for insurance and care costs, both from the public's and the insurance industry's points of view. Insurers worry that applicants might have increasingly precise knowledge of their own risks, which will lead to adverse selection. Public worries focus on the creation of a "genetic underclass" that cannot get access to insurance or essential services. The most striking feature about this, often heated, debate is the almost total absence of numerical estimates of the cost implications.Actuarial modelling is beginning to provide such numerical estimates, in the first instance to the question of the costs of adverse selection if life insurers did not know genetic test results. The answers point to a sharp distinction between dominant single-gene disorders and multifactorial disorders. The former are rare enough that solutions outwith the free market should be sought, and (with some exceptions) the latter probably will not provide clear and reliable estimates of lifetime risk, distinguishable from lifestyle and environmental factors; they might therefore not meet criteria of accuracy and reliability such as those that govern discriminatory pricing in respect of disability.Health and long-term care insurance present more difficult problems, however. Genetical research itself is only beginning to unravel the complex influences on molecular pathways leading to disability, and epidemiological research on large populations has to follow. In this paper, we choose one disorder -Alzheimer's disease (AD) -for which a susceptibility gene is known, called ApoE. We discuss a mathematical model for AD and payments depending on AD, and illustrate the heterogeneity that might be introduced to risk pools by the ApoE gene. We give examples of the possible impact on long-term care insurance underwriting, of adverse selection in the insurance pool, and of AD-related care costs in the U.K..

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The Genetics of Breast and Ovarian Cancer II: A Model of Critical Illness Insurance

Cited by 26 publications

References 6 publications

Survival Analysis on Pedigrees: A Marked Point Process Model

Survival Analysis on Pedigrees: A Marked Point Process Model

Adult Polycystic Kidney Disease and Critical Illness Insurance

Genetics and health costs: some actuarial models

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