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Receiver operating characteristic (ROC) analysis of day 5 morphology grading and metabolomic Viability Score on predicting implantation outcome

  • Assisted Reproduction Technologies
  • Published:
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Abstract

Purpose

Assessment of embryo viability is a key component of in vitro fertilization (IVF) and currently relies largely on embryo morphology and cleavage rate. In this study, we used receiver operating characteristic (ROC) analysis to compare the Viability Score (generated by metabolomic profiling of spent embryo culture media using near infrared (NIR) spectroscopy) to morphologic grading for predicting pregnancy in women undergoing single embryo transfer (SET) on day 5.

Methods

A total of 198 spent embryo culture media samples were collected in four IVF centers located in the USA, Europe and Australia. First, 137 samples (training set) were analyzed by NIR to develop an algorithm that generates a Viability Score predictive of pregnancy for each sample. Next, 61 samples (validation set) were analyzed by observers blinded to embryo morphology and IVF outcome, using the Day 5 algorithm generated with the training set. Pregnancy was defined as fetal cardiac activity (FCA) at 12 weeks of gestation.

Results

The Area Under the Curve (AUC) was greater for the metabolomic Viability Score compared to Morphology [Training set: 0.75 versus 0.55, p = 0.0011; Validation set: 0.68 versus 0.50, P = 0.021], and for a Composite score (obtained using a model combining Viability Score with morphologic grading), compared to morphology alone [0.74 versus 0.50, p = 0.004].

Conclusions

Our findings suggest that Viability Score alone or in combination with morphologic grading has the potential to be a better classifier for pregnancy outcome than morphology alone in women undergoing SET on day 5.

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References

  1. SART. Assisted reproductive technology success rates. National summary and fertility clinic reports. Centers for disease control, USA; 2007.

  2. Ata B, Seli E. Economics of assisted reproductive technologies. Curr Opin Obstet Gynecol. 2010; epub Feb 1.

  3. Steptoe PC, Edwards RG. Birth after the reimplantation of a human embryo. Lancet. 1978;2:366.

    Article  PubMed  CAS  Google Scholar 

  4. Trounson A, Leeton J, Wood C, Webb J, Wood J. Pregnancies in humans by fertilization in vitro and embryo transfer in the controlled ovulatory cycle. Science. 1981;216:681–2.

    Article  Google Scholar 

  5. Edwards R, Fishel S, Cohen J. Factors influencing the success of in vitro fertilization for alleviating human infertility. J In Vitro Fertil Embryo Transf 1984:3–23.

  6. Gardner DK, Schoolcraft WB. In vitro culture of human blastocysts. In: MD JR, editor. Towards reproductive certainty: fertility and genetics beyond. Carnforth: Parthenon; 1999. p. 378–88.

    Google Scholar 

  7. Gerris J, De Neubourg D, Mangelschots K, et al. Prevention of twin pregnancy after in-vitro fertilization or intracytoplasmic sperm injection based on strict embryo criteria: a prospective randomized clinical trial. Hum Reprod. 1999;14:2581–7.

    Article  PubMed  CAS  Google Scholar 

  8. Scott LA, Smith S. The successful use of pronuclear embryo transfer the day following oocyte retrieval. Hum Reprod. 1998;13:1003–13.

    Article  PubMed  CAS  Google Scholar 

  9. Tesarik J, Greco E. The probability of abnormal preimplantation development can be predicted by a single static observation on pronuclear state morphology. Hum Reprod. 1999;14:1318–23.

    Article  PubMed  CAS  Google Scholar 

  10. VanRoyan E, Mangelschots K, De Neubourg D, Valkenburg M, Van de Meerssche M, Ryckaert G, et al. Characterization of a top quality embryo, a step towards single-embryo transfer. Hum Reprod. 1999;14:2345–9.

    Article  Google Scholar 

  11. Veeck L. An atlas of human gametes and conceptuses: an illustrated reference for assisted reproductive technology. New York: Parthenon; 1999.

    Google Scholar 

  12. Sakkas D, Percival G, D’Arcy Y, Sharif K, Afnan M. Assessment of early cleaving in vitro fertilized human embryos at the 2-cell stage before transfer improves embryo selection. Fertil Steril. 2001;76:1150–6.

    Article  PubMed  CAS  Google Scholar 

  13. Toner JP. Progress we can be proud of: U.S. trends in assisted reproduction over the first 20 years. Fertil Steril. 2002;78:943–50.

    Article  PubMed  Google Scholar 

  14. Bromer JG, Seli E. Assessment of embryo viability in assisted reproductive technologies: shortcomings of current approaches and the emerging role of metabolomics. Curr Opin Obstet Gynecol. 2008;20:234–41.

    Article  PubMed  Google Scholar 

  15. Sakkas D, Gardner DK. Noninvasive methods to assess embryo quality. Curr Opin Obstet Gynecol. 2005;17:283–8.

    Article  PubMed  Google Scholar 

  16. Botros L, Sakkas D, Seli E. Metabolomics and its application for non-invasive embryo assessment in IVF. Mol Hum Reprod. 2008;14:679–90.

    Article  PubMed  CAS  Google Scholar 

  17. Katz-Jaffe MG, Schoolcraft WB, Gardner DK. Analysis of protein expression (secretome) by human and mouse preimplantation embryos. Fertil Steril. 2006;86:678–85.

    Article  PubMed  CAS  Google Scholar 

  18. Fuzzi B, Rizzo R, Criscuoli L, Noci I, Melchiorri L, Scarselli B, et al. HLA-G expression in early embryos is a fundamental prerequisite for the obtainment of pregnancy. Eur J Immunol. 2002;32:311–5.

    Article  PubMed  CAS  Google Scholar 

  19. Vercammen MJ, Verloes A, Van de Velde H, Haentjens P. Accuracy of soluble human leukocyte antigen-G for predicting pregnancy among women undergoing infertility treatment: meta-analysis. Hum Reprod Update. 2008;14:209–18.

    Article  PubMed  CAS  Google Scholar 

  20. Oliver SG, Winson MK, Kell DB, Baganz F. Systematic functional analysis of the yeast genome. Trends Biotechnol. 1998;16:373–8.

    Article  PubMed  CAS  Google Scholar 

  21. Seli E, Sakkas D, Scott R, Kwok JS, Rosendahl S, Burns DH. Non-invasive metabolomic profiling of human embryo culture media using Raman and near infrared spectroscopy correlates with reproductive potential of embryos in women undergoing in vitro fertilization. Fertil Steril. 2007;88:1350–7.

    Article  PubMed  Google Scholar 

  22. Scott RT, Seli E, Miller K, Sakkas D, Scott K, Burns DH. Non-invasive metabolomic profiling of human embryo culture media using Raman spectroscopy predicts embryonic reproductive potential: a prospective blinded pilot study. Fertil Steril. 2008;90:77–83.

    Article  PubMed  Google Scholar 

  23. Vergouw CG, Botros LL, Roos P, Lens JW, Schats R, Hompes PGA, et al. Metabolomic profiling by near-infrared spectroscopy as a tool to assess embryo viability: a novel, non-invasive method for embryo selection. Hum Reprod. 2008;23:1499–504.

    Article  PubMed  CAS  Google Scholar 

  24. Seli E, Vergouw CG, Morita H, Botros L, Roos P, Lambalk CB, et al. Non-invasive metabolomic profiling as an adjunct to morphology for non-invasive embryo assessment in women undergoing single embryo transfer. Fertil Steril. 2010;94:535–42.

    Article  PubMed  Google Scholar 

  25. Seli E, Botros L, Henson M, Roos P, Sakkas D, group. Ms. Viability scores determined by metabolomic assessment of embryo culture media correlate with IVF outcome in women undergoing single embryo transfer on day 2: a prospective multi-center trial. In: Annual Meeting of American Society of Reproductive Medicine; 2009; Atlanta, GA.; 2009.

  26. Sing T, Sander O, Beerenwinkel N, Lengauer T. ROCR: visualizing classifier performance in R. Bioinformatics. 2005;21:3940–1.

    Article  PubMed  CAS  Google Scholar 

  27. R Development Core Team. R: A language and environment for statistical computing. In: R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL: http://www.R-project.org; 2005.

  28. Hosmer DW, Lemeshow S. Applied logistic regression. 2nd ed. Wiley; 2000.

  29. Vergara IA, Norambuena T, Ferrada E, Slater AW, Melo F. StAR: a simple tool for the statistical comparison of ROC curves. BMC Bioinform. 2008;9:265.

    Article  Google Scholar 

  30. He X, Frey E, ROC, LROC, FROC, AFROC. An alphabet soup. J Am Coll Radiol. 2009;6:652–5.

    Article  PubMed  Google Scholar 

  31. Gardner DK. Dissection of culture media for embryos: the most important and less important components and characteristics. Reprod Fertil Dev. 2008;20:9–18.

    Article  PubMed  Google Scholar 

  32. Biggers JD, Summers MC. Choosing a culture medium: making informed choices. Fertil Steril. 2008;90:473–83.

    Article  PubMed  Google Scholar 

  33. Gardner DK, Schoolcraft WB, Wagley L, Schlenker T, Stevens J, Hesla J. A prospective randomized trial of blastocyst culture and transfer in in-vitro fertilization. Hum Reprod. 1998;13:3434–40.

    Article  PubMed  CAS  Google Scholar 

  34. Behr B, Pool TB, Milki AA, Moore D, Gebhardt J, Dasig D. Preliminary clinical experience with human blastocyst development in vitro without co-culture. Hum Reprod. 1999;14:454–7.

    Article  PubMed  CAS  Google Scholar 

  35. Van der Auwera I, Debrock S, Spiessens C, Afschrift H, Bakelants E, Meuleman C, et al. A prospective randomized study: day 2 versus day 5 embryo transfer. Hum Reprod. 2002;17:1507–12.

    Article  PubMed  Google Scholar 

  36. Gardner DK, Surrey E, Minjarez D, Leitz A, Stevens J, Schoolcraft WB. Single blastocyst transfer: a prospective randomized trial. Fertil Steril. 2004;81:551–5.

    Article  PubMed  CAS  Google Scholar 

  37. Blake DA, Farquhar CM, Johnson N, Proctor M. Cleavage stage versus blastocyst stage embryo transfer in assisted reproduction. Cochrane Database Syst Rev. 2007;4:CD002118.

    PubMed  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, 310 Cedar street, LSOG 304D, New Haven, CT, 06520-8063, USA

    Emre Seli & Denny Sakkas

  2. Department of Molecular Biochemistry and Biophysics, and W.M. Keck Foundation, Biotechnology Resource Laboratory, Yale University, New Haven, CT, USA

    Can Bruce

  3. Molecular Biometrics,® Inc, New Haven, CT, USA

    Lucy Botros, Mark Henson, Pieter Roos, Kevin Judge & Denny Sakkas

  4. FertilitetsCentrum, Gothenburg, Sweden

    Thorir Hardarson & Aishling Ahlström

  5. Sydney IVF Clinic, Sydney, Australia

    Paul Harrison & Michael Henman

  6. Reproductive Sciences Center, Boston, MA, USA

    Kathryn Go & Nicole Acevedo

  7. Shady Grove Fertility Clinic, Rockville, MD, USA

    Jeannette Siques & Michael Tucker

Authors
  1. Emre Seli
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  2. Can Bruce
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  3. Lucy Botros
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  4. Mark Henson
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  5. Pieter Roos
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  7. Thorir Hardarson
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  8. Aishling Ahlström
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  9. Paul Harrison
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  11. Kathryn Go
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  13. Jeannette Siques
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  14. Michael Tucker
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  15. Denny Sakkas
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Corresponding author

Correspondence to Emre Seli.

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Capsule

In women undergoing single embryo transfer on day 5, receiver operating characteristic (ROC) analysis suggests that metabolomic Viability Score alone or in combination with morphologic grading has the potential to be a better classifier for pregnancy outcome than morphology alone.

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Seli, E., Bruce, C., Botros, L. et al. Receiver operating characteristic (ROC) analysis of day 5 morphology grading and metabolomic Viability Score on predicting implantation outcome. J Assist Reprod Genet 28, 137–144 (2011). https://doi.org/10.1007/s10815-010-9501-9

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  • DOI: https://doi.org/10.1007/s10815-010-9501-9

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