Colorectal Cancer (CRC) and CRC Screening Programs
5.6 The Effect of a CRC Surveillance Program on Life Insurance
A semi-Markov model for HNPCC in life insurance is presented in Figure 5.3, for a sub-population labelled i defined by genotype.
We stratify the whole population into the following three sub-populations:
(a) sub-population 1: non-mutation carriers;
(b) sub-population 2: mutation MLH1 carriers;
(c) sub-population 3: mutation MSH2 carriers;
We take non-mutation carriers not going through CRC Surveillance Program as stan-dard risks. The onset intensities of CRC, EC (females only) and OECC associated with HNPCC and the post-onset mortalities were introduced in Section 3.4. The onset rates of CRC for mutation carriers going through CRC Surveillance Program will be reduced by 56% (see Section 5.5).
able5.1:Levelnetlifeinsurancepremiumratesforpersonsnottakingpartinascreeningprogramandtaking inascreeningprogram. NoScreeningProgramScreeningProgram AgeTermFemalesMalesFemalesMales 20100.000342(100%)0.000867(100%)0.000342(100%)0.000867(100%) 200.000459(100%)0.000973(100%)0.000459(100%)0.000973(100%) 300.000684(100%)0.001268(100%)0.000679(99%)0.001265(100%) 400.001066(100%)0.001874(100%)0.001052(99%)0.001861(99%) 30100.000653(100%)0.001148(100%)0.000653(100%)0.001148(100%) 200.001038(100%)0.001687(100%)0.001029(99%)0.001680(100%) 300.001681(100%)0.002737(100%)0.001654(98%)0.002713(99%) 40100.001679(100%)0.002592(100%)0.001656(99%)0.002574(99%) 200.002759(100%)0.004424(100%)0.002704(98%)0.004375(99%) 50100.004590(100%)0.007589(100%)0.004480(98%)0.007482(99%)
?
State i1 State i2 State i3
State i4
Figure 5.3: A semi-Markov model for HNPCC in life insurance for sub-population i, defined by genotype.
In this model, insured applicants pay premiums continuously while remaining in states i0, i1, i2 or i3, and the claim is paid when they enter state i4. We calculate the net level premium for a unit sum assured. We assume constant force of interest δ = 0.05. The expressions for the EPVs of a unit of premium and a unit of benefit follow, assuming the entry age is x and policy term is n:
EPV[Premium] = Then the net level premium for a unit of benefit payable continuously should be EPV[Benefit]/EPV[Premium]. Table 5.2 and Table 5.3 show, respectively, the level net premium rates per unit sum assured, and the same as a percentage of standard risk, respectively; for MLH1 and MSH2 mutation carriers not taking part in a CRC Surveillance Program and taking part in a CRC Surveillance Program.
We can see some features from the above two tables.
(a) For persons who choose not to take part in a CRC Surveillance Program, mutation-carrying applicants are uninsurable in most cases, except for a few cases at high ages. For persons who choose to take part in a CRC Surveillance Program, we can see substantial decreases in premium, and most cases become insurable at increased premium rates. However, premium rates for female mutation MSH2 carriers are generally above 300% of the premium rates for standard risks. Therefore they are still probably uninsurable.
(b) Female mutation carriers are more likely to be declined than male mutation carriers,
Table5.2:LevelnetlifeinsurancepremiumratesforMLH1andMSH2mutationcarriersnottakingpartina CRCSurveillanceProgramandtakingpartinaSurveillanceProgram. NoSurveillanceProgramSurveillanceProgram MLH1MSH2MLH1MSH2 AgeTermFemalesMalesFemalesMalesFemalesMalesFemalesMales 20100.0009760.0018060.0007550.0017140.0006240.0012770.0006340.001265 200.0022980.0034040.0017500.0034470.0013340.0020690.0013400.002136 300.0035660.0048460.0032510.0054790.0021800.0029410.0024440.003356 400.0046380.0060950.0045230.0069390.0030370.0039180.0034900.004536 30100.0031890.0043580.0026840.0049560.0018840.0025770.0019990.002889 200.0052930.0067750.0053500.0085190.0033100.0040470.0039470.005022 300.0069270.0087140.0073810.0107750.0046640.0056230.0056280.006922 40100.0058910.0072980.0072810.0103410.0040940.0047260.0053920.006289 200.0087000.0107740.0107250.0142310.0063840.0074940.0082210.009553 50100.0096220.0126080.0120940.0150880.0077450.0099680.0096170.011588
able5.3:LevelnetlifeinsurancepremiumratesforMLH1andMSH2mutationcarriersnottakingpartina CSurveillanceProgramandtakingpartinaCRCSurveillanceProgram,expressedaspercentagesofstandard NoSurveillanceProgramSurveillanceProgram MLH1MSH2MLH1MSH2 AgeTermFemalesMalesFemalesMalesFemalesMalesFemalesMales %%%%%%%% 2010285208221198182147185146 20501350381354291213292220 30521382475432319232357265 40435325424370285209327242 3010488380411432289224306252 20510402515505319240380298 30412318439394277205335253 4010351282434399244182321243 20315244389322231169298216 5010210166263199169131210153
(c) Table 5.2 and Table 5.3 are based on known genetic test results. However, under-writing based on genetic test results is banned in the UK, while family history (FH) underwriting is more realistic. In this case, the net level premium will be the ratio of the EPV of 1 unit of benefit to the EPV of 1 unit of premium each weighted by the probability
P [genotype gi | healthy at age x and with family history] ,
for sub-population i. We should expect that more weight would be given to the non-mutation carrier sub-population. As in (a), Table 5.3 shows that most cases going through the CRC Surveillance Program are insurable at increased premium rates with their genetic testing result known to insurers. Because of ‘averaging-out’ effect, we expect all applicants with a family history taking part in a CRC Surveillance Program to be accepted by life insurers at increased premium rates (or even at an ordinary rate at high ages).
5.7 Conclusions
We give short conclusions as follows:
(a) CRC Screening Programs have been proved to reduce the CRC related risk by early detection and effective treatment. In this chapter, we described two types of CRC Screening Program, one for the entire population, called BCSP in the UK, and the other for HNPCC families, called CRC Surveillance Program, implemented in Finland. In the case of the BCSP, Hewitson et al. (2007), a meta-analysis, concluded that participants allocated to screening had a 16% reduction in the relative risk of CRC mortality, whereas in the case of the CRC Surveillance Program, J¨arvinen et
al. (2000) concluded that the onset rate of CRC for mutation carriers was reduced by 56%.
(b) We calculated life insurance premium rates for persons taking part in the BCSP and not taking part in the BCSP. We found that the BCSP may reduce the life insurance premium rates by about 1% (for females aged 50 seeking 10-year policy the reduction in life insurance premium rate is about 2%).
(c) We evaluted life insurance premium rates for persons taking part in the CRC Surveil-lance Program and those not doing so. We found that the CRC SurveilSurveil-lance Pro-gram made mutation MLH1 and MSH2 carriers insurable at increased life insurance premium rates with genetic testing results known to insurers. Hence, under family history underwriting, persons carrying HNPCC family history would also be more likely to be insurable.
(d) We concluded in Chapter 4 that in order to recoup the cost of genetic risk the insurers need to increase the insurance premium rates by about 1% under very extreme circumstances, e.g. severe adverse selection and moratorium on using both genetic testing rests and family history. It is very interesting to see that the BCSP actually appears to negate the genetic risk by about the same magnitude, without even considering the general trend of mortality improvement.