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. 2020 Apr 28;35(4):743-750.
doi: 10.1093/humrep/deaa048.

Preimplantation loss of fertilized human ova: estimating the unobservable

Affiliations

Preimplantation loss of fertilized human ova: estimating the unobservable

Allen J Wilcox et al. Hum Reprod. .

Abstract

Study question: What proportion of fertilized human ova are lost before implantation?

Summary answer: An estimated 40 to 50% of fertilized ova fail to implant.

What is known already: Preimplantation loss is not detectable with current technology. Published estimates of preimplantation loss range from 10 to 70%.

Study design, size, duration: We combine data from epidemiologic, demographic, laboratory and in vitro fertilization studies to construct an empirical framework for the estimation of preimplantation loss. This framework is summarized in a user-friendly Excel file included in supplement.

Participants/materials, setting, methods: We draw from multiple sources to generate plausible estimates of fecundability, sterility, transient anovulation, intercourse patterns and the proportion of ova fertilized in the presence of sperm. We combine these estimates to generate a summary estimate of preimplantation loss. This estimate can be considered an average for couples in their prime reproductive years.

Main results and the role of chance: Under a plausible range of assumptions, we estimate that 40 to 50% of fertilized ova fail to implant.

Limitations, reasons for caution: A crucial factor in estimating preimplantation loss is the probability that an ovum will be fertilized when exposed to sperm. Human data are available only from in vitro fertilization (IVF), which may not accurately represent events in vivo. We therefore assume a range of in vivo fertilization rates, from 64% (human IVF data) to 90% (mouse data).

Wider implications of the findings: Our estimate of preimplantation loss takes into account the biological processes relevant to fertilization and loss. Using this empirical basis for estimation, we find support for the usual assumption that risk of loss is highest in the earliest days following fertilization. Furthermore, this framework can provide improved estimates as better reproductive data become available. To the extent that our estimates are accurate, more fertilized ova are apparently lost in vitro than in vivo, suggesting that further improvements in IVF success rates may be possible.

Study funding/competing interest(s): This study was supported by the Intramural Program of the National Institute of Environmental Health Sciences, NIH. Professor Adashi serves as Co-Chair of the Safety Advisory Board of Ohana Biosciences, Inc. The other authors have no competing interests.

Trial registration number: N/A.

Keywords: epidemiology; fertilization; implantation; oocyte quality; pregnancy.

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Figures

Figure 1
Figure 1. Potential range of preimplantation loss among 100 unselected couples in their first-cycle attempt of pregnancy. We assume that 36% of couple will have an implanting pregnancy and 24% of couples will have a live birth. We also take into account cycles where no fertilization is possible due to sterility, anovulation or mis-timed intercourse (14%), leaving 86 couples (or cycles) as the denominator for possible preimplantation loss.
Figure 2
Figure 2. Potential range of preimplantation loss among 100 unselected couples in their first-cycle attempt of pregnancy. This takes into account the cycles in which fertilization cannot take place (dark gray area, A; see also Fig. 1) and assumes two possible estimates of ova fertilization in the presence of sperm (64% and 90%, B). In C and D, the estimated numbers of fertilized ova become the new denominators for estimating preimplantation loss. For instance, in C, there are 55 cycles with fertilized ova (64% of 86 cycles with viable ova). Given that 36 cycles achieve implantation, the number of cycles with preimplantation loss is 19 (55 minus 36), with a preimplantation loss rate of 19/55 or 35%. Pregs: pregnancies.
Figure 3
Figure 3. Continuous relationship of fertilization rate and estimated preimplantation loss. Estimated for first-attempt cycles with the following assumptions: 14% of cycles have no opportunity for fertilization (sterility, anovulation, mistimed intercourse) and 36% of first-attempt cycles result in an implanting pregnancy. Assumes a range of 64–90% human ova fertilized in the presence of sperm (based on human IVF data (64%) and animal data (90%)).
Figure 4
Figure 4. Estimated range of preimplantation loss under a series of varying assumptions about underlying biological processes. Numbers in parentheses are the baseline assumptions used in the main analysis, holding constant the assumption of ovum fertilization within the range of 64–90%. Even within these variations, there is a range of preimplantation loss (40 to 50%, shown by the gray vertical panel) that remains under all assumptions.
Figure 5
Figure 5. Estimated survival curves for fertilized ova. Scenario A assumes that 40% of fertilized ova will be lost before implantation, while Scenario B assumes 50%. The bar plot at the right of each panel shows the cumulative fate of fertilized ova: loss or live birth. By these estimates, 60–67% of fertilized ova do not result in a live birth, with the largest proportion of loss in both scenarios occurring prior to implantation.

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References

    1. Abma JC, Chandra A, Mosher WD, Peterson LS, Piccinino LJ. Fertility, family planning, and women’s health: new data from the 1995 National Survey of Family Growth. Vital Health Stat 1997;23:1–114. - PubMed
    1. Babariya D, Fragouli E, Alfarawati S, Spath K, Wells D. The incidence and origin of segmental aneuploidy in human oocytes and preimplantation embryos. Hum Reprod 2017;32:2549–2560. - PubMed
    1. Baird DD, Mcconnaughey DR, Weinberg CR, Musey PI, Collins DC, Kesner JS, Knecht EA, Wilcox AJ. Application of a method for estimating day of ovulation using urinary estrogen and progesterone metabolites. Epidemiology 1995;6:547–550. - PubMed
    1. Baird DD, Strassmann BI. Women’s fecundability and factors affecting it. In: Goldman MB, Hatch MC (eds). Women and Health. San Diego:Academic Press, 2000.
    1. Bonde JP, Hjollund NH, Jensen TK, Ernst E, Kolstad H, Henriksen TB, Giwercman A, Skakkebaek NE, Andersson AM, Olsen J. A follow-up study of environmental and biologic determinants of fertility among 430 Danish first-pregnancy planners: design and methods. Reprod Toxicol 1998;12:19–27. - PubMed

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