Abstract
Mismatch repair gene mutation carriers have a high risk of developing colorectal cancer, and can benefit from appropriate surveillance. A combined population based ascertainment cascade genetic testing approach provides a systematic and potentially effective strategy for identifying such carriers. We have developed a Markov Chain computer model system which simulates various factors influencing cascade genetic testing; including demographics, uptake, genetic epidemiology and family size. This was used to evaluate cascade genetic testing for mismatch repair gene mutations in theory and practice. Simulations focussed on the population of Scotland by way of illustration, and were based on a 20-year programme in which index cases were ascertained from colorectal cancer cases aged <55 years at onset. Results indicated that without practical barriers to cascade genetic testing, 545 (95% CI = 522, 568) carriers could be identified; 42% of the population total. This comprised approximately 140 index cases, 302 asymptomatic relatives and 104 previously affected relatives. However, when realistic ascertainment and acceptance rates were used to inform simulations, only 257 (95% CI = 246, 268) carriers, about 20% of the carrier population, were identifiable. Of these approximately 112 were index cases, 108 were asymptomatic relatives, and 37 were previously affected relatives. This contrast emphasises the importance of ascertainment and acceptance rates. Likewise the low number of index cases shows that case identification is a limiting factor. In the absence of robust data from epidemiological studies, these findings can inform decisions about the use of cascade genetic testing for mismatch repair gene mutations.
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Abbreviations
- MMR:
-
Mismatch repair
- CRC:
-
Colorectal cancer
- CGTM:
-
Cascade Genetic Testing Model
- GPM:
-
Genetic Population Model
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Acknowledgements
This work was funded by the Chief Scientist Office of Scotland, grant no. CZH/4/145. The University of Edinburgh acted as sponsor, with vital collaboration from Heriot-Watt University. In addition to the work carried out by the authors, we acknowledge the expert input from Kenneth MacLeod regarding computer programming, and the support provided by Rosa Bisset.
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Appendix 1
Appendix 1
Key input data to Genetic Population Model
Input data | Point estimate (if applicable) | Source/reference | Comments on data accuracy/quality | Generalisability |
---|---|---|---|---|
Population size | 5,094,800 (2005) | GROS | Robust estimate based on census data | Scotland is a relatively small country but data may be extrapolated to populations with similar demographics |
Demographic structure | GROS | Robust estimate | Scotland has a demographic structure that is typical of an aging population in a developed country | |
Deaths (historical data) | GROS | Robust national data | Scotland is broadly representative of developed countries with respect to mortality rate | |
Deaths (projections) | GAD | Projections only | The projected continuation of decreasing mortality rates for Scotland is typical of developed countries | |
Births | GROS | Robust national data | Fertility in Scotland, as with many developed countries, has decreased during the latter part of the 20th century | |
Births (projections) | GAD | Projections only | The projected continuation of decreasing fertility rates for Scotland is typical of developed countries | |
Disease incidence | ISD | Disease incidence has been recorded with a high degree of accuracy since the 1960s; earlier data is of poor quality | Scotland has a relatively high incidence of colorectal cancer, but incidence is comparable with other countries in which the disease is a public health issue | |
Disease incidence (projections) | ISD | Projections, based on current trends and demographic projections | The increasing incidence projected for Scotland is reflected in many other populations | |
Penetrance of MMR gene mutations | To age 70: males: 80% females: 40% | Scientific literature | Limited sources of data, various methods, wide confidence intervals | There is currently no evidence of population variations since differences in published estimates are likely to be due to methods used and lack of statistical power. However, penetrance may vary according to the precise mutation involved and numerous other factors, and may therefore vary by population |
Prevalence of MMR gene mutations | 1:3,139 (95% CI 1:1,247, 1:7,626) | Scientific literature | One source of data only, wide confidence intervals | Prevalence data are scarce, and the single published estimate relates to Scotland. Prevalence is likely to vary by country, particularly when common founder mutations are present in the population (e.g. Finland), but there is no evidence to suggest that Scotland is not representative in this respect |
Disease survival | ISD | Robust national data | In terms of survival, Scotland is representative of countries with modern health care systems | |
Family structure | ONS | Data on frequency distribution of children as well as completed family size is limited to one reliable source | Family structure may vary across populations according to cultural, social and demographic trends. However, Scotland has a stable population which is useful for comparisons, and the observed trend of decreasing family size leading to stabilizing or decreasing population is common |
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Mitchell, R.J., Ferguson, R.K., Macdonald, A. et al. Cascade genetic testing for mismatch repair gene mutations. Familial Cancer 7, 293–301 (2008). https://doi.org/10.1007/s10689-008-9192-x
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DOI: https://doi.org/10.1007/s10689-008-9192-x