|
|
|
|
|
|
|
|
Abstract
Background:
There are several
well-established environmental risk factors for ovarian cancer, and
recent genome-wide association
studies have also identified six variants that
influence disease risk. However, the interplay between such risk factors
and
susceptibility loci has not been studied.
Methods:
Data from 14 ovarian cancer case-control
studies were pooled, and stratified analyses by each environmental risk
factor with tests for heterogeneity were conducted
to determine the presence of interactions for all histological subtypes.
A genetic "risk score" was created to consider the
effects of all six variants simultaneously. A multivariate model was fit
to examine the association between all
environmental risk factors and genetic risk score on ovarian cancer
risk.
Results:
Among 7,374 controls and 5,566 cases,
there was no statistical evidence of interaction between the six SNPs or
genetic
risk score and the environmental risk factors on
ovarian cancer risk. In a main effects model, women in the highest
genetic
risk score quartile had a 65% increased risk of
ovarian cancer compared to women in the lowest (95% CI 1.48-1.84).
Analyses
by histological subtype yielded risk differences
across subtype for endometriosis (phet<0.001), parity (phet<0.01),
and tubal
ligation (phet=0.041).
Conclusions:
The lack of interactions suggests that
a multiplicative model is the best fit for these data. Under such a
model,
we provide a robust estimate of each risk factor's
effect, which sets the stage for absolute risk prediction modeling that
considers both environmental and genetic risk
factors. Further research into the observed differences in risk across
histological
subtype is warranted.
0 comments :
Post a Comment
Your comments?
Note: Only a member of this blog may post a comment.