The question, Hartge said, was simple: "Does getting your SNPs measured really help with prediction, beyond the simple question of the Gail model?"
After evaluating the data, "we found that it helped some," Hartge said.
To quantify how much exactly is difficult, she said, but to put it in other words: "Our data showed that women in the top 20 percent of risk score from the Gail model alone would comprise about 29.9 percent of the actual breast cancer cases. Our data also show that women in the top 20 percent of risk score from the Gail-Plus-SNPs model would comprise about 33.6 percent of the actual breast cancer cases. So you see adding the SNPs helps some."
But for a model to be considered highly effective, women who score in the top 20 percent of risk would have at account for 80 percent of the women who actually ended up with breast cancer, Hartge said.
The study shows that, by that yardstick, the new risk-assessment model just isn't there yet.
In the future, Hartge said, as more discoveries about genetic variants are made, they can be incorporated into the risk model, hopefully increasing the accuracy of the prediction.
But for now, "based on our current data, we do not recommend that women seek genotyping as a means of better understanding their risk profile," Hartge said.
Doctors use the Gail model to determine risk and sometimes advise women about preventive measures such as the frequency of mammograms.
In an editorial accompanying the report, Dutch researchers took a "stay tuned" stance.
"For women seeking advice on their personal risk of breast cancer, it is obviously too early to incorporate SNP testing into a counseling procedures, although such tests are already advertised for this purpose on the internet," they wrote.
Like Hartge, however, the editorial authors -- Dr. Peter Devilee of Leiden Universi
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