“Fertility Chronicles” reposts an op-ed by Univfy Co-founder and CEO Mylene Yao, M.D., that first appeared on Wired.com on Sept. 26, 2013. In it, Dr. Yao responds to a Sept. 11 New York Times op-ed, raising concerns that fertility patients, encouraged by the medical community, continue to pursue treatments even if they are ineffective.
Dr. Yao explains that Univfy IVF Prediction Tests, which provide patients with highly accurate, personalized predictions of their chances of IVF success, offer an answer. When fertility patients know their probability of success, they can make more informed and effective choices regarding treatment and other family-building options.
From Wired.com, September 26, 2013:
Empower Fertility Patients to Understand Their Chances of IVF Success
Posted by Mylene Yao on September 26, 2013 at 9:30 a.m.
Most men and women are hard-wired to give birth, nurture and raise families. That biological drive, as important as survival instinct, has kept our species alive. For over 7 million American couples 1 who suffer from infertility, this drive is just as alive and present, and it has become a source of great controversy.
When over 5 million babies around the world have been born thanks to IVF, we know the science can work. We also have an opportunity -- and a responsibility -- to mitigate the risks and sorrows of ART with rigorous knowledge and data, rather than rejection. 14 million Americans, more than the number living with treated and active cancer, are depending on that.
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?
I have devoted the last fifteen years to researching reproductive medicine with the support of the National Institute of Health (NIH), Stanford University and other academic centers and institutions. Over the past few years, I have had the privilege of learning about patients’ concerns directly, and through surveys and social media. I have also discussed with many IVF doctors how they counsel their patients about IVF success rates.
Doctors whom I’ve met have diligently compiled ART 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.
My research team, originally from Stanford University, has conducted studies with leading IVF clinics and has repeatedly demonstrated that analyses of a patient’s comprehensive health data can provide 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. 2,3,4,5
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. 3,4
Make no mistake about it: patients will continue to face tough decisions. But with dedication, scientific rigor and collaboration, we can help to empower patients to make better decisions with confidence.
1. U.S. Department of Health and Human Services, CDC, NCHS. Fertility, family planning, and reproductive health of U.S. Women: Data from the 2002 National Survey of Family Growth. Vital and Health Statistics. 2005. 23(25).
2. 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.
3. 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.
4. 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.
5. 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.1 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%. However, after her first IVF – even if it has failed – she will be able to use her IVF data to best inform her of her chances of IVF success in subsequent cycles, rather than continue to rely on an assumption that was made before her IVF data became available.
Mylene W. M. Yao, M.D., is co-founder and CEO of Univfy.
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