IVF success: What researchers are doing to empower patients
When over 5 million babies around the world have been born thanks to IVF, we know the science can work.
We have an opportunity — and a responsibility — to maximize the potential of IVF to bring more healthy babies to hopeful parents with rigorous knowledge and data. Fourteen million Americans — more than the number living with treated and active cancer — are depending on that. IVF is a highly effective treatment for infertility and yet it is underutilized. The high cost of IVF and the uncertainty of outcome might be some reasons that women and couples are discouraged to try.
Never mind what is generally believed to be the IVF success rate. The most important questions are: What are your chances of having a baby with your first IVF? What are your chances without IVF? If you’ve had IVF before, what are your chances of having a baby if you do IVF again? What is the success rate that you will tolerate, and at what emotional and financial costs?
In my past research role, I devoted more than fifteen years to researching reproductive medicine with the support of the National Institute of Health (NIH), Stanford University, the American Society of Reproductive Medicine (ASRM) and other academic centers and institutions. Over the past few years, as co-founder and CEO of Univfy, I have had the privilege of learning about the concerns of patients from them directly, and through providers, surveys and social media. Many fertility specialists have raised concerns about the challenges they face when counseling their patients about their IVF success rates.
Fertility specialists have diligently compiled ART (assisted reproductive technology) statistics and have provided the rates of treatment success and failure to patients with sincerity and honesty. However, most national online reporting of IVF success rates across clinics are designed for safety monitoring and quality assurance, and do not provide the level of personalization and accuracy necessary to support an individual’s decision-making.
The Univfy research team has conducted studies with leading IVF clinics and has repeatedly demonstrated that analyses of a patient’s comprehensive health data is more accurate than conventional age-based estimates and can better distinguish patients with truly different probabilities of success. With prediction technology, we found that up to 60-80 percent of patients have different success rates than those estimated by age, and more than half of patients have a higher predicted probability of success than what is estimated by age. 1, 2, 3, 4
We found that by the time a woman has experienced one failed IVF, her age contributes to only 40 percent of the IVF success prediction, while her health data, including data learned from her failed IVF (e.g. blood and ultrasound test results during IVF stimulation and embryo quality), contributes to 60 percent of the prediction. That means age-based estimates are no longer useful after a patient has had one IVF. Therefore, the key to saving women from a missed opportunity — or a slippery slope — is to illuminate the meaningful use of comprehensive health data and its predictive value when counseling patients faced with these tough decisions. 2,3
Make no mistake about it: choosing a fertility treatment is not easy and paying for it can be challenging. But with dedication, scientific rigor and collaboration, we can help to empower patients to make better decisions with confidence.
1: Banerjee P, Choi B, Shahine LK, et al. Deep phenotyping to predict live birth outcomes in in vitro fertilization. PNAS 2010;107(31):13559-60.
2: Choi B, Bosch E, Benjamin ML et al. Personalized prediction of first-cycle in vitro fertilization success. Fertil Steril. 2013. doi: 10.1016/j.fertnstert.
3: Choi B, Santo-Domingo K, Penzias A.S. et al. Turning past IVF data into personalized prognostics through a validated, multi-center IVF prediction model. Abstract. Presented at the Society for Gynecologic Investigations, Orlando, FL. 2013.
4: Although knowing an accurate and personalized prediction of IVF success (in terms of having a baby) is important, patients need to learn the information that is conveyed in a probability. For example, if a patient has 50% chance of having a baby with her first IVF treatment, that puts her within the top 40% of all women taking their first IVF treatment. While 50% chance is considered very high, there is still a 50% chance of not having a baby from her first IVF. When the patient is deciding whether to go for her first IVF, she does not yet have IVF data that can inform her of her chances of success in the second or third IVF cycles, if needed. Therefore, it’s fair to assume that her chance of success in each of the first 3 cycles will be 50%, such that her chance of having a baby within the first 3 cycles will be 88%.
Mylene Yao, MD, Co-Founder and CEO, has led Univfy since the e company started operations in 2010. Her vision is to make IVF more accessible to patients and to break barriers to treatment through the power of predictive analytics. Dr. Yao has over 15 years of experience in clinical and scientific research in fertility. Prior to founding Univfy, she was on the faculty at Stanford University, where she led NIH-funded fertility and embryo genetics research.
Dr. Yao graduated from medical school at the University of Toronto and completed her obstetrics and gynecology residency training at McGill University. She received her clinical subspecialty training in reproductive endocrinology and infertility at Brigham and Women’s Hospital at Harvard University. Dr. Yao received multiple research awards for her fertility research work, including pre-implantation embryo development, the role of stem cell genes in the embryo, and uterine receptivity at implantation, and is co-author of the chapter on Infertility in Novak’s Gynecology, one of the top medical textbooks for obstetricians and gynecologists.