FamEvent (version 3.2)

LSfam: Ontario Lynch Syndrom families

Description

Data from 32 Lynch Syndrome families segregating mismatch repair mutations selected from the Ontario Familial Colorectal Cancer Registry that includes 765 individuals, both probands and relatives. The families were ascertained throughout affected and mutation carrier probands.

Usage

data("LSfam")

Format

A data frame with 765 observations on the following 11 variables.

famID

Family identification (ID) numbers.

indID

Individuals ID numbers.

fatherID

Father ID numbers.

motherID

Mother ID numbers.

gender

Gender indicators: 1 for male, 0 for female.

status

Disease statuses: 1 for affected, 0 for unaffected.

time

Ages at diagnosis of colorectal cancer for the affected or ages of last follow-up for the unaffected.

currentage

Current ages in years.

mgene

MLH1 or MSH2 mutation indicators: 1 for mutated gene carriers, 0 for mutated gene noncarriers, or NA if missing.

proband

Proband indicators: 1 for proband, 0 for non-proband.

relation

Family members' relationship with the proband. Relation codes:

1	Proband (self)
2	Brother or sister
3	Son or daughter
4	Parent
5	Nephew or niece
6	Spouse
7	Brother or sister in law
8	Paternal grandparent
9	Paternal uncle or aunt
10	Paternal cousin
11	Maternal grandparent
12	Maternal uncle or aunt
13	Maternal cousin
14	Son or daughter in law
15	Grandchild
16	Uncle's or aunt's spouse.

References

Choi, Y.-H., Cotterchio, M., McKeown-Eyssen, G., Neerav, M., Bapat, B., Boyd, K., Gallinger, S., McLaughlin, J., Aronson, M., and Briollais, L. (2009). Penetrance of Colorectal Cancer among MLH1/ MSH2 Carriers Participating in the Colorectal Cancer Familial Registry in Ontario, Hereditary Cancer in Clinical Practice, 7:14.

Examples

data(LSfam)

# Summary of LSfam
summary.simfam(LSfam)

# Pedigree plot for the first family
plot.simfam(LSfam)

# Assign minimum age for fitting penmodel
attr(LSfam, "agemin") <- 18

fit <- penmodelEM(Surv(time, status) ~ gender + mgene, cluster = "famID", 
       parms = c(0.05, 2, 1, 3), data = LSfam[!is.na(LSfam$time) & LSfam$time > 18, ], 
       method = "mendelian", base.dist = "Weibull", design = "pop+", robust = TRUE)

summary(fit)

penetrance(fit, fixed = c(1, 1), age = c(50, 60, 70), CI = TRUE, MC = 100)