Skip to main content
Log in

Predictors of treatment failure in young patients undergoing in vitro fertilization

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

Abstract

Purpose

The purpose of the study was to evaluate whether routinely collected clinical factors can predict in vitro fertilization (IVF) failure among young, “good prognosis” patients predominantly with secondary infertility who are less than 35 years of age.

Methods

Using de-identified clinic records, 414 women <35 years undergoing their first autologous IVF cycle were identified. Logistic regression was used to identify patient-driven clinical factors routinely collected during fertility treatment that could be used to model predicted probability of cycle failure.

Results

One hundred ninety-seven patients with both primary and secondary infertility had a failed IVF cycle, and 217 with secondary infertility had a successful live birth. None of the women with primary infertility had a successful live birth. The significant predictors for IVF cycle failure among young patients were fewer previous live births, history of biochemical pregnancies or spontaneous abortions, lower baseline antral follicle count, higher total gonadotropin dose, unknown infertility diagnosis, and lack of at least one fair to good quality embryo. The full model showed good predictive value (c = 0.885) for estimating risk of cycle failure; at ≥80 % predicted probability of failure, sensitivity = 55.4 %, specificity = 97.5 %, positive predictive value = 95.4 %, and negative predictive value = 69.8 %.

Conclusion

If this predictive model is validated in future studies, it could be beneficial for predicting IVF failure in good prognosis women under the age of 35 years.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Centers for Disease Control and Prevention, American Society for Reproductive Medicine and Society for Assisted Reproductive Technolog. 2012 Assisted Reproductive Technology Success Rates: National Summary and Fertility Clinic Reports: U.S. Department of Health and Human Services. Atlanta: CDC; 2014.

    Google Scholar 

  2. Gourounti K, Anagnostopoulos F, Potamianos G, Lykeridou K, Schmidt L, Vaslamatzis G. Perception of control, coping and psychological stress of infertile women undergoing IVF. Reprod Biomed Online. 2012;24(6):670–9. doi:10.1016/j.rbmo.2012.03.002.

    Article  PubMed  Google Scholar 

  3. Pasch LA, Gregorich SE, Katz PK, Millstein SG, Nachtigall RD, Bleil ME, et al. Psychological distress and in vitro fertilization outcome. Fertil Steril. 2012;98(2):459–64. doi:10.1016/j.fertnstert.2012.05.023.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Almog B, Eldar I, Barkan G, Amit A, Wagman I, Levin I. Embryo quality in controlled ovarian stimulation for in vitro fertilization in young poor responders. Gynecol Endocrinol. 2014;30(9):657–9. doi:10.3109/09513590.2014.920003.

    Article  CAS  PubMed  Google Scholar 

  5. Cataldi T, Cordeiro FB, Costa Ldo V, Pilau EJ, Ferreira CR, Gozzo FC, et al. Lipid profiling of follicular fluid from women undergoing IVF: young poor ovarian responders versus normal responders. Hum Fertil (Camb). 2013;16(4):269–77. doi:10.3109/14647273.2013.852255.

    Article  CAS  Google Scholar 

  6. Figueira RC, Braga DP, Nichi M, Madaschi C, Semiao-Francisco L, Iaconelli A, et al. Poor ovarian response in patients younger than 35 years: is it also a qualitative decline in ovarian function? Hum Fertil (Camb). 2009;12(3):160–5. doi:10.1080/14647270902942928.

    Article  CAS  Google Scholar 

  7. Hanoch J, Lavy Y, Holzer H, Hurwitz A, Simon A, Revel A, et al. Young low responders protected from untoward effects of reduced ovarian response. Fertil Steril. 1998;69(6):1001–4.

    Article  CAS  PubMed  Google Scholar 

  8. Farhi J, Ben-Haroush A, Dresler H, Pinkas H, Sapir O, Fisch B. Male factor infertility, low fertilisation rate following ICSI and low number of high-quality embryos are associated with high order recurrent implantation failure in young IVF patients. Acta Obstet Gynecol Scand. 2008;87(1):76–80. doi:10.1080/00016340701743074.

    Article  PubMed  Google Scholar 

  9. Society for Assisted Reproductive Technology www.sart.org.

  10. Gardner DK, Schoolcraft WB. In vitro culture of human blastocyst. In: Jansen R, Mortimer D, editors. Towards reproductive certainty: fertility and genetics beyond 1999. Carnforth: Parthenon Press; 1999. p. 378–88.

    Google Scholar 

  11. Lintsen AM, Eijkemans MJ, Hunault CC, Bouwmans CA, Hakkaart L, Habbema JD, et al. Predicting ongoing pregnancy chances after IVF and ICSI: a national prospective study. Hum Reprod. 2007;22(9):2455–62. doi:10.1093/humrep/dem183.

    Article  CAS  PubMed  Google Scholar 

  12. Nelson SM, Lawlor DA. Predicting live birth, preterm delivery, and low birth weight in infants born from in vitro fertilisation: a prospective study of 144,018 treatment cycles. PLoS Med. 2011;8(1):e1000386. doi:10.1371/journal.pmed.1000386.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Stolwijk AM, Zielhuis GA, Hamilton CJ, Straatman H, Hollanders JM, Goverde HJ, et al. Prognostic models for the probability of achieving an ongoing pregnancy after in-vitro fertilization and the importance of testing their predictive value. Hum Reprod. 1996;11(10):2298–303.

    Article  CAS  PubMed  Google Scholar 

  14. Harlow SD, Linet MS. Agreement between questionnaire data and medical records. The evidence for accuracy of recall. Am J Epidemiol. 1989;129(2):233–48.

    CAS  PubMed  Google Scholar 

  15. Kristensen P, Irgens LM. Maternal reproductive history: a registry based comparison of previous pregnancy data derived from maternal recall and data obtained during the actual pregnancy. Acta Obstet Gynecol Scand. 2000;79(6):471–7.

    Article  CAS  PubMed  Google Scholar 

  16. Wilcox AJ, Horney LF. Accuracy of spontaneous abortion recall. Am J Epidemiol. 1984;120(5):727–33.

    CAS  PubMed  Google Scholar 

  17. Cassell DL. Don’t be loopy: re-sampling and simulation the SAS way. SAS Global Forum. Cary: SAS Institute Inc; 2007.

    Google Scholar 

  18. Guidelines for the number of embryos to transfer following in vitro fertilization No. 182, September 2006. Int J Gynaecol Obstet. 2008; 102(2):203–16.

  19. Elective single-embryo transfer. Fertil Steril. 2012;97(4):835–42. doi:10.1016/j.fertnstert.2011.11.050.

  20. Cutting R, Morroll D, Roberts SA, Pickering S, Rutherford A. Elective single embryo transfer: guidelines for practice British Fertility Society and Association of Clinical Embryologists. Hum Fertil (Camb). 2008;11(3):131–46. doi:10.1080/14647270802302629.

    Article  Google Scholar 

  21. 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. doi:10.1093/humrep/deq213.

    Article  CAS  PubMed  Google Scholar 

  22. Terriou P, Sapin C, Giorgetti C, Hans E, Spach JL, Roulier R. Embryo score is a better predictor of pregnancy than the number of transferred embryos or female age. Fertil Steril. 2001;75(3):525–31.

    Article  CAS  PubMed  Google Scholar 

  23. van Loendersloot LL, van Wely M, Limpens J, Bossuyt PM, Repping S, van der Veen F. Predictive factors in in vitro fertilization (IVF): a systematic review and meta-analysis. Hum Reprod Update. 2010;16(6):577–89. doi:10.1093/humupd/dmq015.

    Article  PubMed  Google Scholar 

  24. Klonoff-Cohen H. Female and male lifestyle habits and IVF: what is known and unknown. Hum Reprod Update. 2005;11(2):179–203. doi:10.1093/humupd/dmh059.

    CAS  PubMed  Google Scholar 

  25. Lintsen AM, Pasker-de Jong PC, de Boer EJ, Burger CW, Jansen CA, Braat DD, et al. Effects of subfertility cause, smoking and body weight on the success rate of IVF. Hum Reprod. 2005;20(7):1867–75. doi:10.1093/humrep/deh898.

    Article  CAS  PubMed  Google Scholar 

  26. Wellons MF, Fujimoto VY, Baker VL, Barrington DS, Broomfield D, Catherino WH, et al. Race matters: a systematic review of racial/ethnic disparity in Society for Assisted Reproductive Technology reported outcomes. Fertil Steril. 2012;98(2):406–9. doi:10.1016/j.fertnstert.2012.05.012.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Barad D, Gleicher N. Effect of dehydroepiandrosterone on oocyte and embryo yields, embryo grade and cell number in IVF. Hum Reprod. 2006;21(11):2845–9. doi:10.1093/humrep/del254.

    Article  CAS  PubMed  Google Scholar 

  28. Batioglu AS, Sahin U, Gurlek B, Ozturk N, Unsal E. The efficacy of melatonin administration on oocyte quality. Gynecol Endocrinol. 2012;28(2):91–3. doi:10.3109/09513590.2011.589925.

    Article  PubMed  Google Scholar 

  29. Gleicher N, Weghofer A, Barad DH. Improvement in diminished ovarian reserve after dehydroepiandrosterone supplementation. Reprod Biomed Online. 2010;21(3):360–5. doi:10.1016/j.rbmo.2010.04.006.

    Article  CAS  PubMed  Google Scholar 

  30. Papaleo E, Unfer V, Baillargeon JP, Fusi F, Occhi F, De Santis L. Myo-inositol may improve oocyte quality in intracytoplasmic sperm injection cycles. A prospective, controlled, randomized trial. Fertil Steril. 2009;91(5):1750–4. doi:10.1016/j.fertnstert.2008.01.088.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marni B. Jacobs.

Ethics declarations

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. For this type of study, formal consent is not required.

Conflict of interest

The authors declare that they have no conflict of interest.

Funding

None.

Additional information

Capsule If this predictive model is validated in future studies, it could be beneficial for predicting IVF failure in good prognosis women under the age of 35 years.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jacobs, M.B., Klonoff-Cohen, H., Agarwal, S. et al. Predictors of treatment failure in young patients undergoing in vitro fertilization. J Assist Reprod Genet 33, 1001–1007 (2016). https://doi.org/10.1007/s10815-016-0725-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10815-016-0725-1

Keywords

Navigation