Genetics and Underwriting in Health Insurance Angus Macdonald - PowerPoint PPT Presentation

Genetics and Underwriting in Health Insurance Angus Macdonald Heriot-Watt University, Edinburgh

Outline N Genetic epidemiology N Example 1 – Alzheimer’s disease N Example 2 – Coronary heart disease

Single-Gene Disorders N Extra morbidity and mortality - high N Age at onset or death - often much younger than average, with high probability N Comparatively rare - about 1% of births N Many sufferers will not survive to insuring ages N Probably a strong family history

Multifactorial Disorders N Associated with common causes of death N May occur in healthy lives N May be a family history N May interact with environmental factors N Extra mortality - variable, often quite low N Age at death/illness - not known with much greater probability

What Do Genetic Epidemiologists Study? N Penetrance: p ( x ) = the probability that a given genotype will cause disease by age x N Mutation frequency in the population N Survival after onset of disease N Progression or stages of disease N Gene-environment interactions

Ascertainment Bias N A significant feature is ascertainment bias – Search the world for unusual families with many affected members in several generations – Estimate rates of onset based on affected members of these families N Result: Penetrance estimates may be greatly overstated

Multifactorial Epidemiology N Molecular epidemiology – find out which genes are “switched on” during specific biomedical processes N Population epidemiology – find out which combinations of genetic variants and environment influence disease

UK Biobank N Recruit 500,000 healthy people age 45-69 N Obtain DNA N Obtain data on environmental exposures N Follow up via doctors, hospitals and disease registers N Use as source for large scale case-control studies from 5 years onwards

UK Biobank – Value for Money? N Cost of data collection alone ~ £40 million – Medical Research Council, Department of Health and Wellcome Trust

UK Biobank – Value for Money? N Cost of data collection alone ~ £40 million – Medical Research Council, Department of Health and Wellcome Trust N Power to detect associations? – 50% of population with “interesting” genotype and “interesting” exposure – 4 controls per case – 3,600 cases needed to detect 30% extra risk

UK Biobank – Value for Money? N Cost of data collection alone ~ £40 million – Medical Research Council, Department of Health and Wellcome Trust N Power to detect associations? – 10% of population with “interesting” genotype and “interesting” exposure – 4 controls per case – 12,600 cases needed to detect 60% extra risk

Pharmacogenomics N (1) Use molecular medicine to develop new drugs N (2) Use genetic profiling to target specific drugs to persons who will respond well N Unknown impact on: – Drugs costs, in public and private medicine – Rationing of expensive medicine – Affordability of pooled medical costs

Alzheimer’s Disease N Alzheimer’s Disease – progressive dementia – onset mostly at ages > 65 – accounts for a significant part of LTC costs – no known cure or effective treatment

Alzheimer’s and the ApoE Gene N The ApoE gene has 3 alleles: e2, e3, e4 N e4 allele predisposes to earlier onset of AD N e4/e4 – about 2% of the population – highest risk - up to 10-12 x, males and females N e3/e4 – about 20% of the population – females at up to 4-5 x normal risk

Learning About ApoE N Early 1980s – three variants of the ApoE protein identified N 1980s – e4 allele linked to heart disease N 1991 – e4 allele linked to Alzheimer’s disease N 1997 – Age-dependent risk estimates published

A Model of AD and Care Costs Healthy Onset of AD In Institution Dead

A Model of AD and Care Costs e2/e2, e2/e3 e3/e3 e2/e4 e3/e4 e4/e4

Features of the Model N The “normal” level of insurance N The extent of genetic testing N The probability of a positive result N The behaviour of “adverse selectors” N The behaviour of insurers N The amount and incidence of medical costs N The amount and incidence of care costs

LTC Insurance Policies N LTC policies pay out while suffering: – typically, loss of 3 or more Activities of Daily Living (ADLs) ; or – cognitive impairment, such as AD N Payments are usually linked to an index N Fewer than 30,000 policies sold in the UK N AD accounts for 1/2 - 1/3 of costs (USA)

A Model of AD and Care Costs Healthy Onset of AD In Institution Dead

Extra Premiums? Female age 60 Proportion of Relative Risk e4/e4 e3/e4 e2/e4 % % % 1.00 37 23 21

Population Risk: Parameter m N Rates of onset based on case-control studies N Expect strong selection bias, lower genetic risk in a population sample N Modelled by reducing excess e4 onset rate – by 50% ( m =0.5) – by 75% ( m =0.25) N Delphic estimates may be even lower

Extra Premiums? Female age 60 Proportion of Relative Risk e4/e4 e3/e4 e2/e4 % % % 1.00 37 23 21 0.50 21 13 12 0.25 11 7 6

Long-Term Care Costs of AD N Holmes et al. (1998) model: – £41,794 p.a. PLUS – £436.6 p.a, for each year since onset MINUS – £336.0 p.a., for each year of age PLUS – £17,840 p.a., if in an institution N Includes costs of unpaid care

AD Costs at Age 60 (£,000) e2/e3 e3/e3 e2/e4 e3/e4 e4/e4 Ave M 17 44 28 37 95 39 F 37 56 93 95 116 64

Population Risk: m =0.25 e2/e3 e3/e3 e2/e4 e3/e4 e4/e4 Ave M 33 38 35 37 50 37 F 55 58 71 70 78 62

Combined Pension and LTC? N AD has opposite effects on pensions and LTC: – Increases LTC costs – Decreases pension costs N Pension/LTC (AD) benefit in ratio 1:3 – Average pension = £3,200 p.a. – Average LTC benefit = £9,600 p.a.

Extra Premiums for Combined Pension + LTC? Female age 60 Prop’n of RR e4/e4 e3/e4 e2/e4 % % % LTC only 1.00 37 23 21 0.25 11 7 6 LTC+Pen 1.00 3 3 2 0.25 1 1 0

Conclusions N e4/e4 as a separate risk group? N Timescale of ~10 years between discovery and reliable assessment N Great uncertainty about results: N Recommend continuing research: – Development of actuarial models – More collaboration/interdisciplinary work

Coronary Heart Disease (CHD) N Major common cause of death N Caused by fatty deposits in coronary arteries N Outcome myocardial infarction (MI, meaning heart attack) N Genetic component is multifactorial

CHD N “Lifestyle” risk factors: – Sex, smoking, body mass index (BMI) N “Clinical” risk factors: – Hypertension – Hypercholesterolaemia – Diabetes N These are also risk factors for stroke

Examples of Extra Premiums N Model from Macdonald, Waters & Wekwete (2004) based on Framingham study N Compare a mutation that increases the intensity of: – Progression through a clinical risk factor – MI or stroke directly

Examples of Extra Premiums Male, 35, N-S, Normal BMI, 10-year term 5 x risk of Extra Premium Hypertension 14% Hypercholesterolaimia 6% Diabetes type 1 2% Diabetes type 2 5% CHD (directly) 192% Stroke (directly) 30%

Examples of Extra Premiums Male, 35, N-S, Normal BMI, Severe Hypertension, 10-year term 5 x risk of Extra Premium 97% (basic) Hypercholesterolaemia 113% Diabetes type 1 99% Diabetes type 2 105% CHD (directly) 597% Stroke (directly) 203%

Conclusion N Genotypes that confer high additional risks of risk factors in complex disorders do not imply large additional risks of the disease endpoints N The genetic contributions to complex disorders will mostly act in this way N Important message for public debate

What is the Purpose of Research? N NOT to allow more discrimination N Main purpose is to obtain quantitative information to: – inform policymakers; – identify potential problems; – allay unnecessary fears; and – help to achieve fairness in provision

Genetics and Underwriting in Health Insurance Angus Macdonald Heriot-Watt University, Edinburgh