New Method for Predicting IVF Success
Researchers Look at 52 Factors to Estimate Chances of Success From in Vitro Fertlization
July 19, 2010 -- A new method for predicting IVF success that takes 52 variables into account works better overall than the commonly used age model, according to a new report.
In IVF (in vitro fertilization), eggs and sperm are brought together in a lab dish to fertilize an egg.
''Our model is more than 1,000 times more predictive than the age-based model," researcher Mylene Yao, MD, an assistant professor of obstetrics and gynecology at Stanford University School of Medicine, tells WebMD.
"We are pinpointing patients more specifically, using [more than] 50 variables rather than one, " she says.
The model estimates the likelihood of a live birth with future IVF cycles for women who have already gone through one cycle.
Eventually, Yao hopes the method will be available for commercial use. The report is published online in the Proceedings of the National Academy of Sciences.
Predicting IVF Success: The Model
Nearly 75% of IVF treatments don't produce a live birth, Yao writes. When deciding whether to try another IVF cycle, patients are guided mostly by age considerations, with estimates based on that.
Yao and her colleagues wanted to develop a more personalized way to estimate future success. So they evaluated data from 1,676 first IVF cycles done at Stanford Hospital & Clinics between 2003 and 2006. They found 52 factors, including age but also hormone levels, quality of eggs, and embryo characteristics, that had an effect on the chances of having a live baby.
"It's basic information," Yao tells WebMD. "We stuck to information that is freely available in people's medical records."
Next, they put together a computer model that classified patients into subgroups based on their clinical characteristics, a method called ''deep phenotyping."
They validated the model by testing it on 634 first IVF cycles and 230 second IVF cycles done at the facility from 2007-2008.
The findings? The new model wasn't perfect, but was often more accurate than using age alone, Yao says. "For every patient for whom the age test was more predictive, there were more than 1,000 for whom our test was more predictive."
Yao and another co-author have founded a company, Univfy Inc., a start-up that will focus on refining the model and bringing it to market. Stanford holds the patent on the test.