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Not knowing their personal chances of IVF success may cause many women to be missing out on a treatment that could be highly effective for them.
Mylene Yao, M.D., CEO and co-founder
In vitro fertilization (IVF) is the most effective treatment for many women and couples diagnosed with infertility. But as with any medical treatment, most patients want to know their personal likelihood of IVF success.
For years, fertility doctors have focused primarily on maternal age when advising women and couples on whether to pursue IVF or to seek other options for building their families. But age doesn’t tell the full story, nor do the independent effects of other fertility factors. Although many fertility doctors and researchers have also studied how other factors, such as ovarian reserve, male factor, and clinical diagnoses, independently impact IVF success, until now, there has been no method to measure how they affect a particular patient’s chances to have a baby with IVF.
Univfy recognizes that each woman has a unique reproductive profile, encompassing many factors that must be analyzed together for their collective impact on her IVF success. Univfy IVF Prediction Tests use a woman’s complete reproductive profile—and important information about her partner or donor—to accurately and reliably predict the likelihood of having a baby with IVF or a multiple birth. We provide the information that women and their partners need to make real-life decisions.
We have found that patient data can be used to accurately predict a woman’s probability of IVF success from a first cycle. Univfy PreIVF analyzes each individual’s fertility profile -- including age; body mass index, (BMI) comprising height and weight; ovarian reserve tests (e.g. serum anti-mullerian hormone or Day 3 FSH tests); semen analysis; and prior fertility and medical history. We then compare that information to profiles of thousands of others who have completed first IVF cycles to deliver a personalized prediction of IVF success instantly. More than half of first-time IVF cases tested by Univfy PreIVF had a significantly higher likelihood of IVF success than estimated by age.
Read the research:
Choi B, Bosch E, Lannon BM, Leveille MD, Wong WH, Leader A, Pellicer A, Penzias AS, Yao, MWM. Fertil Steril 2013;99(7):1905-11. doi: 10.1016/j.fertnstert.2013.02.016. Epub 2013 Mar 21.
More than 80% of patients tested by Univfy’s prediction models were proven to have higher probabilities of IVF success, compared to age-based estimates. Further, nearly 60% of patients were found to have a better chance of having a baby than was estimated by age.
Why the discrepancy? Because age-based predictions fail to consider important reproductive factors that more reliably predict IVF success. Likewise, other methods that analyze fertility factors independently do not consider the patient’s entire reproductive profile either. Univfy IVF Prediction Tests analyze an entire profile of reproductive factors to deliver the most accurate estimate of having a baby, whether from a first IVF or subsequent IVF treatment.
*Univfy IVF prediction models have 1,000 times bigger likelihood than age-based estimates. Alternatively, we measured the percentage improvement in predictive power by comparing the posterior log-likelihoods of each prediction model and its age-based prediction, against the baseline model. Univfy PreIVF shows a 36% improvement in predictive power over age-based prediction, while Univfy PredictIVF shows a 77% improvement in predictive power over age-based prediction.
Read the research:
Turning Past IVF Data Into Personalized Prognostics Through A Validated, Multi-Center IVF Prediction Model.
Choi B, Santo-Domingo K, Penzias AS, Bosch E, Leader A, Leveille MC, Lannon B, Pellicer A, Wong WH, Yao MWM. Abstract presented at the Society of Gynecologic Investigations, Orlando, Florida, 2013.
Banerjee P*, Choi B*, Shahine LK, Jun SH, O’Leary K, Lathi RB, Westphal LM, Wong WH, Yao MWM. PNAS 2010;107(31):13559-60. doi: 10.1073/pnas.1002296107. Epub 2010 Jul 19.
Univfy has developed and tested a prediction model that can calculate a woman’s probability of having twins from IVF (when two embryos are transferred). The model uses a woman’s reproductive history, laboratory tests, response from her current IVF treatment, and embryo quality to determine her probability of having twins if two fresh embryos are transferred instead of just one. Personalized predictions of multiple birth risk can support physicians when counseling their patients about the benefits of elective single embryo transfer (eSET).
Read the research:
Lannon BM*, Choi B*, Hacker MR, Dodge LE, Malizia BA, Barrett CB, Wong WH, Yao MWM, Penzias AS. Fertil Steril 2012;98(1):69-76. doi:10.1016/j.fertnstert.2012.0411. Epub 2012 Jun 4.
In their research, Univfy’s founding team identified several powerful predictors of IVF success. Specifically, four variables--the total number of embryos, number of 8-cell embryos, percentage of embryos arrested at cleavage stages, and Day 3 FSH level-- were more powerful predictors of IVF success than measures associated with individual transferred embryos. Three of the four predictors above describe the embryo group (or embryo cohort), rather than individual embryos.
Read the research:
Jun SH*, Choi B*, Shahine L, Westphal LM, Behr B, Reijo Pera, Wong WH, Yao MWM.
PLoS ONE 2008;3(7): e2562. doi:10.1371/journal.pone.0002562.
Univfy works with the best minds in reproductive science—reproductive endocrinologists, physicians, researchers, professors from top universities, research institutes, and hospitals from around the world.