Part II: Methods and Approaches 1: Assessing Disease Associations and Interactions Chapter 11 Tables



Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease

 

Epidemiologic Approach to Genetic Tests: Population-Based Data for Preventive Medicine

Marta Gwinn, Muin J. Khoury


Characteristic
How is it defined?
How is it determined?
How is it used?
Table 11-1Analytic validity, clinical validity, and clinical utility of a genetic test
Analytic validity
sensitivity, specificity, and predictive value in relation to genotype
laboratory analyses comparing test result with gold standard
validating test before clinical or research use
Clinical validity
sensitivity, specificity, and predictive value in relation to genotype
population-based, epidemiologic studies (cohort, case-control)
predicting risk, screening, making diagnosis
Clinical utility
benefits and risks accruing from both positive and negative tests
clinical trials; synthesis of observational data
assessing added value of testing in preventing disease outcomes

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Average
Moderate
High
Risk Factor
No 1°relative a
Any 1°relative a
HNPCC
FAP b
Table 11-2Analytic validity, clinical validity, and clinical utility of a genetic test
Prevalence
9/10
1/10
1/3,000 c
1/8,000
Absolute Risk
0.04
0.055
0.80 d
~1
Relative Risk
1.7
~20
~30
Attributable fraction
0.07
unk
~0.004

a Fuchs CS, Giovannucci EL, Colditz GA, et al. A prospective study of family history and the risk of colorectal cancer. New Engl J Med 1994;331:1669-1674.

b Bodmer W. Familial adenomatous polyposis (FAP) and its gene, APC. Cytogenet Cell Genet 1999;86:99-104.

c Dunlop MG, Farrington SM, Nicholl I, et al. Population carrier frequency of hMSH2 and hMLH1 mutations. Brit J Cancer 2000;83:1643-1645.

d Lynch HT, Lynch JF. Hereditary nonpolyposis colorectal cancer. Semin Surg Oncol 2000;18:305-313.

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Disease
Yes
No
Total
Appendix 11Joint probability distribution of susceptibility genotype anddisease outcome in a hypothetical population.
Genotype Present
P(GD)
P( icon
)
P(G)
Absent
p( icon
)
P( icon
)
P( icon
)
Total
P(D)
P( icon
)
1
probability of genotype = P(G)
probability of disease = P(D)
population odds of disease = P(D) / P(icon)
joint probability of G and D = P(GD)
sensitivity = P(GD) / P(D) = P(G|D)
specificity = P(icon|icon), 1 – specificity = P(G|icon)
positive predictive value (ppv) of genotype = P(D|G)
negative predictive value (npv) of genotype = P(icon|icon)The improved ability to predict disease using genotype can be summarized:P(GD)/P(icon) = [P(G|D) / P(G|icon)] [P(D)/P(icon)]

or,odds of disease in presence of genotype = [sensitivity/(1 – specificity)](population disease odds)

The factor by which disease prediction can be improved in persons with the genotype,
relative to the whole population, is [sensitivity/(1 – specificity)], known as the likelihood
ratio.a
Likewise, the relative risk of disease in persons with the genotype can be expressed:
[P(GD)/P(G)]/[P(iconD)/P(icon)] = P(D|G) / P(D|icon) = ppv / (1-npv)

aReference 31.

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Page last reviewed: January 1, 2004 (archived document)