July 2, 2008 — 根據7月2日線上發表於PLOS One的研究,四個因素(胚胎總數、8細胞胚胎數量、胚胎停止分裂百分比、母體的濾泡刺激素[FSH],可以合併用來準確預測70%試管嬰兒胚胎植入(IVF)懷孕的成功率。
  加州史丹佛大學醫學院的Mylene W. M. Yao醫師在新聞稿中指出,如果你與IVF病患及醫師討論,他們對於循環中所有胚胎— 而不是只有植入的那一個 — 的質量很重要並不會感到驚訝;但是,為了推廣此一領域,在直覺之外,更重要的是有科學證據。
  這項研究的限制包括缺乏兄弟姊妹胚胎的冷凍胚胎資料,協助孕育之方式和使用陽性血清 hCG作為懷孕結果等。
  Yao醫師的團隊現在分析順產嬰兒的四年追蹤結果— 而非陽性 beta-hCG — 作為研究終點。
  國家健康研究中心與March of Dimes贊助此研究。
  PLOS One線上發表於2008年7月2日。

Four Combined Factors Predict Success of In Vitro Fertilization

By Laurie Barclay, MD
Medscape Medical News

July 2, 2008 — Four factors (total number of embryos, number of 8-cell embryos, percentage of embryos that stopped dividing, and maternal follicle-stimulating hormone [FSH]), when combined, were 70% accurate in predicting pregnancy following in vitro fertilization (IVF), according to a study published online July 2 in PLOS One.

"If you talk with IVF patients or doctors, they wouldn't be surprised to hear that the quality of all embryos in a cycle — not just the transferred one — matters," Mylene W. M. Yao, MD, from Stanford University School of Medicine in California, says in a news release. "But it's important to go beyond intuition and to prove it scientifically, in order to move the field forward."

The hypothesis of this study was that embryo cohort–specific variables describing sibling embryos as a group could predict developmental competence, as reflected in pregnancy outcomes of IVF cycles.

The investigators analyzed data for all 1117 IVF cycles performed during 2005 at Stanford University Medical Center, as well as additional clinical data from the 665 fresh IVF, nondonor cycles and their associated 4144 embryos. Regression tree models were used for the unbiased analysis of 30 variables related to patient characteristics, clinical diagnoses, treatment protocol, and embryo characteristics, based on pregnancy outcomes measured by positive serum beta-human chorionic gonadotropin (beta-hCG).

The most accurate prediction of IVF cycle outcomes was approximately 70% and resulted from the use of 4 embryo cohort–specific variables. Surprisingly, these variables were more predictive than were any variables related to individual, transferred embryos.

"People make decisions based on probability," said Dr. Yao. "At that point, it's really important to give a more accurate prediction."

The 4 most predictive cohort factors were total number of embryos, number of 8-cell embryos, rate (percentage) of cleavage arrest in the cohort, and FSH level on day 3. Of these 4 variables, only the rate of cleavage arrest was independent of any known variables.

"Our findings support defining human embryo phenotypes by non-redundant, prognostic variables that are specific to sibling embryos in a cohort," the study authors write. "The concept of cohort-specific determinants suggest[s] a paradigm shift from strictly focusing research efforts on selecting the 'best' embryos to identifying methods that would improve the quality of the entire cohort."

Limitations of this study include lack of data on cryopreservation of sibling embryos and assisted hatching and use of positive serum hCG status as a surrogate outcome for pregnancy.

Dr. Yao's group is now analyzing results from a follow-up study with 4 years of data using live birth — rather than positive beta-hCG — as the endpoint.

"While embryo-specific parameters may help to identify embryos that would maximize the immediate pregnancy outcome for each couple, in the long term, understanding cohort-specific parameters is critical in counseling patients, improving treatment, and ultimately in developing mechanism-specific and more customized treatments," the study authors conclude.

The National Institutes of Health and the March of Dimes supported this study.

PLOS One. Published online July 2, 2008.

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