Skip to main content
SpringerLink
Log in

Development and validation of a conventional in vitro total fertilization failure prediction model

  • Assisted Reproduction Technologies
  • Published:
Journal of Assisted Reproduction and Genetics Aims and scope Submit manuscript

Abstract

Background

Conventional total fertilization failure (TFF) is a challenging problem for clinicians. The predictive model developed in this study aims to predict the individual probability of conventional in vitro total fertilization failure.

Methods

The prediction model was developed based on 1635 patients who underwent first-attempt in vitro fertilization (IVF) cycles from January 2018 to January 2020. Total fertilization failure and normal fertilization occurred in 218 and 1417 cycles, respectively. Multivariate logistic regression analyses were used to develop the prediction model. Performance of our model was evaluated using calibration (Hosmer-Lemeshow test) and discrimination (area under the receiver operating characteristic curve [AUC]).

Results

Thirteen risk factors for TFF were included in the prediction model, as follows: female age; female body mass index; infertility duration; number of oocytes retrieved; stimulation protocol; infertility etiology; infertility diagnosis; male age; sperm concentration; total sperm motility; normal sperm morphology percentage; swim-up sperm motility; and swim-up sperm concentration. The AUC of our model was 0.815 (95% CI: 0.783–0.846), indicating satisfactory discrimination performance.

Conclusion

Considering female and male factors (especially sperm parameters), we established a model that predicts the probability of TFF in conventional IVF procedures that will be helpful in the laboratory supporting IVF to facilitate physicians in determining optimal treatment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Mahutte NG, Arici A. Failed fertilization: is it predictable? Curr Opin Obstet Gynecol. 2003;15(3):211–8. https://doi.org/10.1097/00001703-200306000-00001.

    Article  PubMed  Google Scholar 

  2. Molloy D, Harrison K, Breen T, Hennessey J. The predictive value of idiopathic failure to fertilize on the first in vitro fertilization attempt. Fertil Steril. 1991;56(2):285–9. https://doi.org/10.1016/s0015-0282(16)54486-0.

    Article  CAS  PubMed  Google Scholar 

  3. Xia QLY, Zhang Y, Tian F, Zhang Q, Yao Z. Identification of factors related to fertilization failure in in vitro fertilization-embryo transfer. Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2020;45(8):960–5. https://doi.org/10.11817/j.issn.1672-7347.2020.200076.

    Article  PubMed  Google Scholar 

  4. Sohn JO, Jun JH, Kim SH, Kim MJ, Lim JM, Song HJ. P-001 - Does vitamin D deficiency affect the IVF-ET outcomes in infertile Korean women? Reprod Biomed Online. 2018;37:e4. https://doi.org/10.1016/j.rbmo.2018.04.002.

    Article  Google Scholar 

  5. Check JH, Chang E, Cohen R, Choe J, Wilson C, Summers D. Pregnancy rates following in vitro fertilization-embryo transfer (IVF-ET) in women with diminished oocyte reserve who only had one day 3 fresh embryo to transfer. Fertil Steril. 2018;110(4, Supplement):e324. https://doi.org/10.1016/j.fertnstert.2018.07.910.

    Article  Google Scholar 

  6. Kastrop PM, Weima SM, Van Kooij RJ, Te Velde ER. Comparison between intracytoplasmic sperm injection and in-vitro fertilization (IVF) with high insemination concentration after total fertilization failure in a previous IVF attempt. Hum Reprod. 1999;14(1):65–9. https://doi.org/10.1093/humrep/14.1.65.

    Article  CAS  PubMed  Google Scholar 

  7. Chen L, Li D, Ni X, et al. Effects of the normal sperm morphology rate on the clinical and neonatal outcomes of conventional IVF cycles. Andrologia. 2020;52(5):e13568. https://doi.org/10.1111/and.13568.

    Article  PubMed  Google Scholar 

  8. Fang QYWL, Tong XH. Logistic regression analysis of risk factors associated with fertilization failure in routine IVF. Progress in Obstetrics and Gynaecology. 2020;29(03):199–202. https://doi.org/10.13283/j.cnki.xdfckjz.2020.03.010.

  9. Cai Q, Wan F, Huang R, Zhang H. Factors predicting the cumulative outcome of IVF/ICSI treatment: a multivariable analysis of 2450 patients. Hum Reprod. 2011;26(9):2532–40. https://doi.org/10.1093/humrep/der228.

    Article  CAS  PubMed  Google Scholar 

  10. Roberts SA, Hirst WM, Brison DR, Vail A. Embryo and uterine influences on IVF outcomes: an analysis of a UK multi-centre cohort. Hum Reprod. 2010;25(11):2792–802. https://doi.org/10.1093/humrep/deq213.

    Article  CAS  PubMed  Google Scholar 

  11. The Vienna consensus: report of an expert meeting on the development of art laboratory performance indicators. Hum Reprod Open. 2017;2017(2):hox011. https://doi.org/10.1093/hropen/hox011.

  12. Embryologist Group CSoRM, Chinese Medical Association. Consensus on human IVF-ET laboratory manipulations (2016). J Reprod Med. 2017;26(01):1-8.

    Google Scholar 

  13. World Health Organization. WHO laboratory manual for the examination and processing of human semen. 5th ed. Geneva: World Health Organization; 2010.

    Google Scholar 

  14. Li M, Huang J, Zhuang X, et al. Obstetric and neonatal outcomes after the transfer of vitrified-warmed blastocysts developing from nonpronuclear and monopronuclear zygotes: a retrospective cohort study. Fertil Steril. 2021;115(1):110–7. https://doi.org/10.1016/j.fertnstert.2020.07.019.

    Article  PubMed  Google Scholar 

  15. Liu N, Ma Y, Li R, et al. Comparison of follicular fluid amphiregulin and EGF concentrations in patients undergoing IVF with different stimulation protocols. Endocrine. 2012;42(3):708–16. https://doi.org/10.1007/s12020-012-9706-z.

    Article  CAS  PubMed  Google Scholar 

  16. van der Westerlaken L, Helmerhorst F, Dieben S, Naaktgeboren N. Intracytoplasmic sperm injection as a treatment for unexplained total fertilization failure or low fertilization after conventional in vitro fertilization. Fertil Steril. 2005;83(3):612–7. https://doi.org/10.1016/j.fertnstert.2004.08.029.

    Article  PubMed  Google Scholar 

  17. Patel AS, Leong JY, Ramasamy R. Prediction of male infertility by the World Health Organization laboratory manual for assessment of semen analysis: a systematic review. Arab J Urol. 2018;16(1):96–102. https://doi.org/10.1016/j.aju.2017.10.005.

    Article  PubMed  Google Scholar 

  18. Li B, Ma Y, Huang J, et al. Probing the effect of human normal sperm morphology rate on cycle outcomes and assisted reproductive methods selection. PloS One. 2014;9(11):e113392. https://doi.org/10.1371/journal.pone.0113392.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zhu Y, Zhang F, Cheng H, Sun XX, Jiang F. Modified strict sperm morphology threshold aids in the clinical selection of conventional in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI). Asian J Androl. 2022;24(1):62–6. https://doi.org/10.4103/aja.aja_45_21.

    Article  PubMed  Google Scholar 

  20. Panner Selvam MK, Agarwal A. Update on the proteomics of male infertility: a systematic review. Arab J Urol. 2018;16(1):103–12. https://doi.org/10.1016/j.aju.2017.11.016.

    Article  PubMed  Google Scholar 

  21. Zhang T, Wu J, Liao C, Ni Z, Zheng J, Yu F. System analysis of teratozoospermia mRNA profile based on integrated bioinformatics tools. Mol Med Rep. 2018;18(2):1297–304. https://doi.org/10.3892/mmr.2018.9112.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Paoli D, Pecora G, Pallotti F, et al. Cytological and molecular aspects of the ageing sperm. Hum Reprod. 2019;34(2):218-227. https://doi.org/10.1093/humrep/dey357

  23. Kashanian JA, Brannigan RE. Sperm morphology and reproductive outcomes: a perplexing relationship. Fertil Steril. 2014;102(6):1561–2. https://doi.org/10.1016/j.fertnstert.2014.09.025.

    Article  PubMed  Google Scholar 

  24. Li XYBX, Song XR. Influence of sperm morphology on pregnancy result in in-vitro-fertilization and embryo transfer. Journal Of International Obstetrics And Gynecology. 2011;38(01):72–5.

  25. YX. X. The correlation between male semen factors and IVF-ET outcomes. Int J Lab Med. 2016;37(11):1505–7.

    Google Scholar 

  26. Harris AL, Vanegas JC, Hariton E, et al. Semen parameters on the day of oocyte retrieval predict low fertilization during conventional insemination IVF cycles. J Assist Reprod Genet. 2019;36(2):291–8. https://doi.org/10.1007/s10815-018-1336-9.

    Article  CAS  PubMed  Google Scholar 

  27. Chen SWWM, Fu L. Correlative analysis of three sperm indexes and IVF-ET outcome after semen treatment. Chongqing Med. 2017;46(32):4526–8.

    Google Scholar 

  28. Gelbaya TA, Potdar N, Jeve YB, Nardo LG. Definition and epidemiology of unexplained infertility. Obstet Gynecol Surv. 2014;69(2):109–15. https://doi.org/10.1097/ogx.0000000000000043.

    Article  PubMed  Google Scholar 

  29. Demirol A, Guven S, Baykal C, Gurgan T. Effect of endometrioma cystectomy on IVF outcome: a prospective randomized study. Reprod Biomed Online. 2006;12(5):639–43. https://doi.org/10.1016/s1472-6483(10)61192-3.

    Article  PubMed  Google Scholar 

  30. Liu DY, Baker HW. Acrosome status and morphology of human spermatozoa bound to the zona pellucida and oolemma determined using oocytes that failed to fertilize in vitro. Hum Reprod. 1994;9(4):673–9. https://doi.org/10.1093/oxfordjournals.humrep.a138570.

    Article  CAS  PubMed  Google Scholar 

  31. McAvey B, Zapantis A, Jindal SK, Lieman HJ, Polotsky AJ. How many eggs are needed to produce an assisted reproductive technology baby: is more always better? Fertil Steril. 2011;96(2):332–5. https://doi.org/10.1016/j.fertnstert.2011.05.099.

    Article  PubMed  Google Scholar 

  32. Manna C, Barbagallo F, Manzo R, Rahman A, Francomano D, Calogero AE. Sperm parameters before and after swim-up of a second ejaculate after a short period of abstinence. J Clin Med. 2020;9(4):1029. https://doi.org/10.3390/jcm9041029.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Wang J, Zhang J, Sun X, et al. Novel bi-allelic variants in ACTL7A are associated with male infertility and total fertilization failure. Hum Reprod. 2021;36(12):3161–9. https://doi.org/10.1093/humrep/deab228.

    Article  CAS  PubMed  Google Scholar 

  34. Dai C, Hu L, Gong F, et al. ZP2 pathogenic variants cause in vitro fertilization failure and female infertility. Genet Med. 2019;21(2):431–40. https://doi.org/10.1038/s41436-018-0064-y.

    Article  CAS  PubMed  Google Scholar 

  35. Intracytoplasmic sperm injection (ICSI) for non-male factor indications: a committee opinion. Fertil Steril. 2020;114(2):239–45. https://doi.org/10.1016/j.fertnstert.2020.05.032.

  36. Bai F, Wang DY, Fan YJ, et al. Assisted reproductive technology service availability, efficacy and safety in mainland China: 2016. Hum Reprod. 2020;35(2):446–52. https://doi.org/10.1093/humrep/dez245.

    Article  CAS  PubMed  Google Scholar 

  37. Dang VQ, Vuong LN, Luu TM, et al. Intracytoplasmic sperm injection versus conventional in-vitro fertilisation in couples with infertility in whom the male partner has normal total sperm count and motility: an open-label, randomised controlled trial. Lancet. 2021;397(10284):1554–63. https://doi.org/10.1016/s0140-6736(21)00535-3.

    Article  PubMed  Google Scholar 

  38. Rajender S, Avery K, Agarwal A. Epigenetics, spermatogenesis and male infertility. Mutat Res. 2011;727(3):62–71. https://doi.org/10.1016/j.mrrev.2011.04.002.

    Article  CAS  PubMed  Google Scholar 

  39. Qiao J, Chen Y, Yan LY, Yan J, Liu P, Sun QY. Changes in histone methylation during human oocyte maturation and IVF- or ICSI-derived embryo development. Fertil Steril. 2010;93(5):1628–36. https://doi.org/10.1016/j.fertnstert.2009.03.002.

    Article  CAS  PubMed  Google Scholar 

  40. Noori S, Nedaeifard L, Agarasouli Z, Koohpaiehzadeh J, Kermani RM, Fazeli AS. Prelinguistic behavior of infants of assisted reproductive techniques. Iran J Pediatr. 2012;22(4):535–8.

    PubMed  PubMed Central  Google Scholar 

Download references

Funding

This study was funded by the Beijing Municipal Science and Technology Commission (grant no. Z191100006619076) and the National Natural Science Foundation of China (grant no. 82071721).

Author information

Author notes

  1. Ming Li and Xiangyue Duan contributed equally to this work.

Authors and Affiliations

  1. Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, No. 49 North Huayuan Road, Haidian District, Beijing, 100191, China

    Ming Li, Xiangyue Duan, Nan Zhang, Feng Ding, Yuanyuan Wang, Ping Liu & Rong Li

  2. Key Laboratory of Assisted Reproduction (Peking University), Ministry of Education, Beijing, 100191, China

    Ming Li, Xiangyue Duan, Nan Zhang, Feng Ding, Yuanyuan Wang, Ping Liu & Rong Li

  3. Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive, Technology, Beijing, 100191, China

    Ming Li, Xiangyue Duan, Nan Zhang, Feng Ding, Yuanyuan Wang, Ping Liu & Rong Li

Authors
  1. Ming Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiangyue Duan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Feng Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yuanyuan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ping Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rong Li.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, M., Duan, X., Zhang, N. et al. Development and validation of a conventional in vitro total fertilization failure prediction model. J Assist Reprod Genet 40, 1915–1923 (2023). https://doi.org/10.1007/s10815-023-02851-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10815-023-02851-7

Keywords

Search

Navigation