For couples who have trouble conceiving, in vitro fertilization (IVF) is often the last resort. The procedure is expensive, emotionally wrenching, and often takes several rounds to succeed—if it does at all. Now researchers say they have come up with a way to better estimate a couple's chance of having a child using IVF. The work is a step toward giving patients more choices with their limited resources, says reproductive endocrinologist Alan Penzias of Harvard Medical School in Boston, who was not affiliated with the study
Many factors determine whether a couple will become pregnant, but a woman's age is near the top of the list. At 21, when a woman is at peak fertility and 90% of her eggs are normal, her chance of conceiving in any given cycle is 24%. It's 15% at 35, 10% at 40, and 2% at 42.
Facing those long odds, many older women turn to IVF. It's a costly proposition. In addition to the $10,000 or more price tag per cycle, a woman must be injected with hormones, visit a doctor more than once a week, and have her eggs harvested and reimplanted. And, even then, the statistics are not in her favor. IVF succeeds for only about 45% of women in their mid-30s and for only about 25% of women in their 40s.
When IVF patients ask about their chance of conceiving, physicians usually quote the success rate at their center for patients of a similar age group. But these are just rough averages and do not consider a patient's specific situation, says IVF researcher Mylene Yao of the Stanford University School of Medicine in Palo Alto, California. "Clinicians know that clinical factors besides age affect IVF outcomes, but there is no way for them to quantify this," she says.
In an attempt to bring hard numbers into IVF forecasting, Yao and colleagues collected data on over 50 variables that influence the success of the treatment. These included figures known before the start of IVF, such as age, number of previous pregnancies, and sperm count, and figures known after the completion of the first round of IVF, such as whether there was fertilization, endometrial thickness, and average number of cells per embryo. In all, the researchers fed data on over 1600 first-round IVF procedures from patients treated at Stanford University Hospital and Clinics.
When the researchers compared the model's predictive powers with a model based on age alone, they found that it was about 1000 times more accurate in gauging success in the second round of IVF. Because clinicians often use a variety of qualitative assessments in estimating a woman's chance of success with IVF, there is no way to directly compare the accuracy of Yao's model with the accuracy of a given clinician. But, based on the accuracy of this first attempt, this type of statistical modeling could be a useful tool in helping clinicians better predict a patient's chance of IVF success, the team reports online today in the Proceedings of the National Academy of Sciences. Yao and a colleague have co-founded a company to further develop the technology.
Reproductive endocrinologist Alan Copperman of Mount Sinai Medical Center in New York City is encouraged by the findings. He thinks the research may eventually help clinicians better estimate how many embryos to transfer without raising the likelihood of a woman carrying more than one fetus at a time. Penzias praises the authors' "clever methodology," though he notes some limitations with the model: how clinicians handled the embryos in the lab was not quantified, for example. Still, he says, a robust way to predict IVF success would be a boon to couples, even if it delivers bad news. "If a couple has little to no chance of conceiving," says Penzias, "the sooner we can tell them this and the sooner they can grieve and move on."