Predicted probabilities of live birth following assisted reproductive technology using United States national surveillance data from 2016 to 2018.

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  • Additional Information
    • Source:
      Publisher: Elsevier Country of Publication: United States NLM ID: 0370476 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-6868 (Electronic) Linking ISSN: 00029378 NLM ISO Abbreviation: Am J Obstet Gynecol Subsets: MEDLINE
    • Publication Information:
      Publication: <2005->: New York : Elsevier
      Original Publication: St. Louis.
    • Subject Terms:
      Live Birth*/epidemiology ; Infertility*/therapy; Pregnancy ; Female ; Male ; Humans ; Cohort Studies ; Reproductive Techniques, Assisted ; Fertilization in Vitro ; Birth Rate ; Probability ; Retrospective Studies ; Pregnancy Rate
    • Abstract:
      Background: As the use of in vitro fertilization continues to increase in the United States, up-to-date models that estimate cumulative live birth rates after multiple oocyte retrievals and embryo transfers (fresh and frozen) are valuable for patients and clinicians weighing treatment options.
      Objective: This study aimed to develop models that generate predicted probabilities of live birth in individuals considering in vitro fertilization based on demographic and reproductive characteristics.
      Study Design: Our population-based cohort study used data from the National Assisted Reproductive Technology Surveillance System 2016 to 2018, including 196,916 women who underwent 207,766 autologous embryo transfer cycles and 25,831 women who underwent 36,909 donor oocyte transfer cycles. We used data on autologous in vitro fertilization cycles to develop models that estimate a patient's cumulative live birth rate after all embryo transfers (fresh and frozen) within 12 months after 1, 2, and 3 oocyte retrievals in new and returning patients. Among patients using donor oocytes, we estimated the cumulative live birth rate after their first, second, and third embryo transfers. Multinomial logistic regression models adjusted for age, prepregnancy body mass index (imputed for 18% of missing values), parity, gravidity, and infertility diagnoses were used to estimate the cumulative live birth rate.
      Results: Among new and returning patients undergoing autologous in vitro fertilization, female age had the strongest association with cumulative live birth rate. Other factors associated with higher cumulative live birth rates were lower body mass index and parity or gravidity ≥1, although results were inconsistent. Infertility diagnoses of diminished ovarian reserve, uterine factor, and other reasons were associated with a lower cumulative live birth rate, whereas male factor, tubal factor, ovulatory disorders, and unexplained infertility were associated with a higher cumulative live birth rate. Based on our models, a new patient who is 35 years old, with a body mass index of 25 kg/m 2 , no previous pregnancy, and unexplained infertility diagnoses, has a 48%, 69%, and 80% cumulative live birth rate after the first, second, and third oocyte retrieval, respectively. Cumulative live birth rates are 29%, 48%, and 62%, respectively, if the patient had diminished ovarian reserve, and 25%, 41%, and 52%, respectively, if the patient was 40 years old (with unexplained infertility). Very few recipient characteristics were associated with cumulative live birth rate in donor oocyte patients.
      Conclusion: Our models provided estimates of cumulative live birth rate based on demographic and reproductive characteristics to help inform patients and providers of a woman's probability of success after in vitro fertilization.
      (Copyright © 2023 Elsevier Inc. All rights reserved.)
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    • Grant Information:
      CC999999 United States ImCDC Intramural CDC HHS
    • Contributed Indexing:
      Keywords: assisted reproduction; infertility; in vitro fertilization; live birth
    • Publication Date:
      Date Created: 20230126 Date Completed: 20230501 Latest Revision: 20240430
    • Publication Date:
      20240430
    • Accession Number:
      PMC11057011
    • Accession Number:
      10.1016/j.ajog.2023.01.014
    • Accession Number:
      36702210