Predicting personalized cumulative live birth following in vitro fertilization.
| Autor: | McLernon DJ; Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom. Electronic address: d.mclernon@abdn.ac.uk., Raja EA; Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom., Toner JP; Department of Gynecology and Obstetrics, Emory University, Atlanta, Georgia., Baker VL; Division of Reproductive Endocrinology and Infertility, Johns Hopkins University School of Medicine, Lutherville, Maryland., Doody KJ; Center for Assisted Reproduction, Bedford, Texas., Seifer DB; Division of Reproductive Endocrinology and Infertility, Yale University School of Medicine, New Haven, Connecticut., Sparks AE; Center for Advanced Reproductive Care, University of Iowa Health Care, Iowa City, Iowa., Wantman E; Redshift Technologies, Inc., New York, New York., Lin PC; Seattle Reproductive Medicine, Seattle, Washington., Bhattacharya S; School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom., Van Voorhis BJ; Department of Obstetrics and Gynecology, University of Iowa Health Care, Iowa City, Iowa. |
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| Jazyk: | angličtina |
| Zdroj: | Fertility and sterility [Fertil Steril] 2022 Feb; Vol. 117 (2), pp. 326-338. Date of Electronic Publication: 2021 Oct 19. |
| DOI: | 10.1016/j.fertnstert.2021.09.015 |
| Abstrakt: | Objective: To develop in vitro fertilization (IVF) prediction models to estimate the individualized chance of cumulative live birth at two time points: pretreatment (i.e., before starting the first complete cycle of IVF) and posttreatment (i.e., before starting the second complete cycle of IVF in those couples whose first complete cycle was unsuccessful). Design: Population-based cohort study. Setting: National data from the Society for Assisted Reproductive Technology (SART) Clinic Outcome Reporting System. Patient(s): Based on 88,614 women who commenced IVF treatment using their own eggs and partner's sperm in SART member clinics. Intervention(s): Not applicable. Main Outcome Measure(s): The pretreatment model estimated the cumulative chance of a live birth over a maximum of three complete cycles of IVF, whereas the posttreatment model did so over the second and third complete cycles. One complete cycle included all fresh and frozen embryo transfers resulting from one episode of ovarian stimulation. We considered the first live birth episode, including singletons and multiple births. Result(s): Pretreatment predictors included woman's age (35 years vs. 25 years, adjusted odds ratio 0.69, 95% confidence interval 0.66-0.73) and body mass index (35 kg/m 2 vs. 25 kg/m 2 , adjusted odds ratio 0.75, 95% confidence interval 0.72-0.78). The posttreatment model additionally included the number of eggs from the first complete cycle (15 vs. 9 eggs, adjusted odds ratio 1.10, 95% confidence interval 1.03-1.18). According to the pretreatment model, a nulliparous woman aged 34 years with a body mass index of 23.3 kg/m 2 , male partner infertility, and an antimüllerian hormone level of 3 ng/mL has a 61.7% chance of having a live birth over her first complete cycle of IVF (and a cumulative chance over three complete cycles of 88.8%). If a live birth is not achieved, according to the posttreatment model, her chance of having a live birth over the second complete cycle 1 year later (age 35 years, number of eggs 7) is 42.9%. The C-statistic for all models was between 0.71 and 0.73. Conclusion(s): The focus of previous IVF prediction models based on US data has been cumulative live birth excluding cycles involving frozen embryos. These novel prediction models provide clinically relevant estimates that could help clinicians and couples plan IVF treatment at different points in time. (Copyright © 2021 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.) |
| Databáze: | MEDLINE |
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