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Epidemiologic Approaches for Studying Assisted Reproductive Technologies: Design, Methods, Analysis, and Interpretation

  • Reproductive and Perinatal Epidemiology (R Platt, Section Editor)
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Abstract

Purpose

While considerable progress has been made since the advent of assisted reproductive technology (ART), the field remains a complex and challenging one for clinicians and researchers alike. This review discusses some of the most salient issues pertaining to the study of ART and whenever possible suggestions on how to address them.

Recent Findings

More than 5 million babies have been born through ART to date, representing up to 4% of all births worldwide. While technologies continue to evolve and demand for treatment grows, it is more important than ever to conduct rigorous and timely research to help guide clinical practice that is safe and effective, and that minimizes potential short- and long-term adverse outcomes to mother and child.

Summary

ART research will require exceedingly more sophisticated research methods, designs, and analyses that are rooted in a reproductive epidemiological framework in order to improve future research and ultimately promote better outcomes for all subfertile couples and their children.

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References

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  1. Ishihara O, Adamson GD, Dyer S, de Mouzon J, Nygren KG, Sullivan EA, et al. International committee for monitoring assisted reproductive technologies: world report on assisted reproductive technologies, 2007. Fertil Steril. 2015;103(2):402–13 e11. doi:10.1016/j.fertnstert.2014.11.004.

    Article  PubMed  Google Scholar 

  2. Zegers-Hochschild F, Mansour R, Ishihara O, Adamson GD, de Mouzon J, Nygren KG, et al. International Committee for Monitoring Assisted Reproductive Technology: world report on assisted reproductive technology, 2005. Fertil Steril. 2014;101(2):366–78. doi:10.1016/j.fertnstert.2013.10.005.

    Article  PubMed  Google Scholar 

  3. ESHRE. The world’s number of IVF and ICSI babies has now reached a calculated total of 5 million. Istanbul, Turkey: European society of human reproduction and embryology; 2012 [cited 2012 October 16th]; Available from: http://www.eshre.eu/ESHRE/English/Press-Room/Press-Releases/Press-releases-2012/5-million-babies/page.aspx/1606. 2012.

  4. Connolly MP, Hoorens S, Chambers GM. The costs and consequences of assisted reproductive technology: an economic perspective. Hum Reprod Update. 2010;16(6):603–13. doi:10.1093/humupd/dmq013.

    Article  PubMed  Google Scholar 

  5. Dyer S, Chambers GM, de Mouzon J, Nygren KG, Zegers-Hochschild F, Mansour R, et al. International Committee for Monitoring Assisted Reproductive Technologies world report: assisted reproductive technology 2008, 2009 and 2010. Hum Reprod. 2016;31(7):1588–609. doi:10.1093/humrep/dew082.

    Article  CAS  PubMed  Google Scholar 

  6. Chronopoulou E, Harper JC. IVF culture media: past, present and future. Hum Reprod Update. 2015;21(1):39–55. doi:10.1093/humupd/dmu040.

    Article  CAS  PubMed  Google Scholar 

  7. •• ESHRE. Failures (with some successes) of assisted reproduction and gamete donation programs. Hum Reprod Update. 2013;19(4):354–65. doi:10.1093/humupd/dmt007. A comprehensive overview by ESHRE working group on timely issues pertaining to infertility and assisted reproductive technology with important key messages and next steps included in the conclusion.

    Article  Google Scholar 

  8. Toner JP. Progress we can be proud of: U.S. trends in assisted reproduction over the first 20 years. Fertil Steril. 2002;78(5):943–50.

    Article  PubMed  Google Scholar 

  9. • Pinborg A, Wennerholm UB, Romundstad LB, Loft A, Aittomaki K, Soderstrom-Anttila V, et al. Why do singletons conceived after assisted reproduction technology have adverse perinatal outcome? Systematic review and meta-analysis. Hum Reprod Update. 2013;19(2):87–104. doi:10.1093/humupd/dms044. A complete review and thorough discussion on understanding the complexities of why singletons conceived after assisted reproducitve technology have a higher risk of adverse outcomes.

    Article  CAS  PubMed  Google Scholar 

  10. Gurunath S, Pandian Z, Anderson RA, Bhattacharya S. Defining infertility—a systematic review of prevalence studies. Hum Reprod Update. 2011;17(5):575–88. doi:10.1093/humupd/dmr015.

    Article  CAS  PubMed  Google Scholar 

  11. Gnoth C, Godehardt E, Frank-Herrmann P, Friol K, Tigges J, Freundl G. Definition and prevalence of subfertility and infertility. Hum Reprod. 2005;20(5):1144–7.

    Article  CAS  PubMed  Google Scholar 

  12. Messerlian C, Maclagan L, Basso O. Infertility and the risk of adverse pregnancy outcomes: a systematic review and meta-analysis. Hum Reprod. 2013;28(1):125–37. doi:10.1093/humrep/des347.

    Article  PubMed  Google Scholar 

  13. Zegers-Hochschild F, Adamson GD, de Mouzon J, Ishihara O, Mansour R, Nygren K, et al. The International Committee for Monitoring Assisted Reproductive Technology (ICMART) and the World Health Organization (WHO) revised glossary on ART terminology, 2009. Hum Reprod. 2009;24(11):2683–7. doi:10.1093/humrep/dep343.

    Article  CAS  PubMed  Google Scholar 

  14. Allen VM, Wilson RD, Cheung A. Pregnancy outcomes after assisted reproductive technology. J Obstet Gynaecol Can. 2006;28(3):220–50.

    Article  PubMed  Google Scholar 

  15. Donckers J, Evers JL, Land JA. The long-term outcome of 946 consecutive couples visiting a fertility clinic in 2001–2003. Fertil Steril. 2011;96(1):160–4. doi:10.1016/j.fertnstert.2011.04.019.

    Article  PubMed  Google Scholar 

  16. •• Farland LV, Collier AR, Correia KF, Grodstein F, Chavarro JE, Rich-Edwards J, et al. Who receives a medical evaluation for infertility in the United States? Fertil Steril. 2016;105(5):1274–80. doi:10.1016/j.fertnstert.2015.12.132. This paper details the demographic, lifestyle, and access barriers associated with seeking infertility treatment in the US and gives readers an idea of how representative infertility treatment cohorts are of women experiencing infertility.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Schieve LA, Devine O, Boyle CA, Petrini JR, Warner L. Estimation of the contribution of non-assisted reproductive technology ovulation stimulation fertility treatments to US singleton and multiple births. Am J Epidemiol. 2009;170(11):1396–407. doi:10.1093/aje/kwp281.

    Article  PubMed  Google Scholar 

  18. Messerlian C, Platt RW, Tan SL, Gagnon R, Basso O. Low-technology assisted reproduction and the risk of preterm birth in a hospital-based cohort. Fertil Steril. 2015;103(1):81–8 e2. doi:10.1016/j.fertnstert.2014.10.006.

    Article  PubMed  Google Scholar 

  19. Messerlian C, Platt RW, Ata B, Tan SL, Basso O. Do the causes of infertility play a direct role in the aetiology of preterm birth? Paediatr Perinat Epidemiol. 2015;29(2):101–12. doi:10.1111/ppe.12174.

    Article  PubMed  Google Scholar 

  20. Chandra A, Copen CE, Stephen EH. Infertility service use in the United States: data from the National Survey of Family Growth, 1982–2010. Natl Health Stat Rep. 2014;22(73):1–21.

    Article  Google Scholar 

  21. Hotaling JM, Davenport MT, Eisenberg ML, VanDenEeden SK, Walsh TJ. Men who seek infertility care may not represent the general U.S. population: data from the National Survey of Family Growth. Urology. 2012;79(1):123–7. doi:10.1016/j.urology.2011.09.021.

    Article  PubMed  Google Scholar 

  22. • Ahrens KA, Cole SR, Westreich D, Platt RW, Schisterman EF. A cautionary note about estimating effects of secondary exposures in cohort studies. Am J Epidemiol. 2015;181(3):198–203. doi:10.1093/aje/kwu276. This paper details the potential bias that can arise when studying secondary exposures in cohorts enriched for a primary exposure.While the example used throughout the paper is maternal smoking (exposure), study population (fetal growth restriction), and outcome (preterm birth), the same logic applies using ART as the study population and miscarriage as the outcome.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sunderam S, Kissin DM, Crawford SB, Folger SG, Jamieson DJ, Warner L, et al. Assisted reproductive technology surveillance—United States, 2014. MMWR Surveill Summ. 2017;66(6):1–24. doi:10.15585/mmwr.ss6606a1.

    Article  PubMed  Google Scholar 

  24. Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies (ART) in Canada: 2007 results from the Canadian ART Register. Fertil Steril. 2011;95(2):542–7 e1-10. doi:10.1016/j.fertnstert.2010.05.057.

    Article  PubMed  Google Scholar 

  25. Kupka MS, D’hooghe T, Ferraretti AP, de Mouzon J, Erb K, Castilla JA, et al. Assisted reproductive technology in Europe, 2011: results generated from European registers by ESHRE. Hum Reprod. 2016;31(2):233–48. doi:10.1093/humrep/dev319.

    CAS  PubMed  Google Scholar 

  26. Nyboe Andersen A, Erb K. Register data on assisted reproductive technology (ART) in Europe including a detailed description of ART in Denmark. Int J Androl. 2006;29(1):12–6. doi:10.1111/j.1365-2605.2005.00577.x.

    Article  PubMed  Google Scholar 

  27. Khamsi F, Lacanna I, Endman M, Wong J. Recent advances in assisted reproductive technologies. Endocrine. 1998;9(1):15–25. doi:10.1385/ENDO:9:1:15.

    Article  CAS  PubMed  Google Scholar 

  28. Land JA, Evers JL. Risks and complications in assisted reproduction techniques: report of an ESHRE consensus meeting. Hum Reprod. 2003;18(2):455–7.

    Article  CAS  PubMed  Google Scholar 

  29. Guidelines on number of embryos transferred. Fertil Steril. 2009;92(5):1518–9. doi:10.1016/j.fertnstert.2009.08.059.

  30. Land JA, Evers JL. What is the most relevant standard of success in assisted reproduction? Defining outcome in ART: a Gordian knot of safety, efficacy and quality. Hum Reprod. 2004;19(5):1046–8. doi:10.1093/humrep/deh215.

    Article  PubMed  Google Scholar 

  31. Steptoe PC, Edwards RG, Purdy JM. Clinical aspects of pregnancies established with cleaving embryos grown in vitro. Br J Obstet Gynaecol. 1980;87(9):757–68.

    Article  CAS  PubMed  Google Scholar 

  32. Romundstad LB, Romundstad PR, Sunde A, von During V, Skjaerven R, Gunnell D, et al. Effects of technology or maternal factors on perinatal outcome after assisted fertilisation: a population-based cohort study. Lancet. 2008;372(9640):737–43. doi:10.1016/S0140-6736(08)61041-7.

    Article  PubMed  Google Scholar 

  33. Saunders DM, Mathews M, Lancaster PA. The Australian Register: current research and future role. A preliminary report. Ann N Y Acad Sci. 1988;541:7–21.

    Article  CAS  PubMed  Google Scholar 

  34. McElrath TF, Wise PH. Fertility therapy and the risk of very low birth weight. Obstet Gynecol. 1997;90(4 Pt 1):600–5.

    Article  CAS  PubMed  Google Scholar 

  35. Hill GA, Bryan S, Herbert 3rd CM, Shah DM, Wentz AC. Complications of pregnancy in infertile couples: routine treatment versus assisted reproduction. Obstet Gynecol. 1990;75(5):790–4.

    CAS  PubMed  Google Scholar 

  36. Braun JM, Messerlian C, Hauser R. Fathers matter: why it’s time to consider the impact of paternal environmental exposures on children’s health. Curr Epidemiol Rep. 2017.

  37. Messerlian C, Wylie BJ, Minguez-Alarcon L, Williams PL, Ford JB, Souter IC, et al. Urinary concentrations of phthalate metabolites and pregnancy loss among women conceiving with medically assisted reproduction. Epidemiology. 2016;27(6):879–88. doi:10.1097/EDE.0000000000000525.

    Article  PubMed  Google Scholar 

  38. Minguez-Alarcon L, Chiu YH, Messerlian C, Williams PL, Sabatini ME, Toth TL, et al. Urinary paraben concentrations and in vitro fertilization outcomes among women from a fertility clinic. Fertil Steril. 2016;105(3):714–21. doi:10.1016/j.fertnstert.2015.11.021.

    Article  CAS  PubMed  Google Scholar 

  39. Hauser R, Gaskins AJ, Souter I, Smith KW, Dodge LE, Ehrlich S, et al. Urinary phthalate metabolite concentrations and reproductive outcomes among women undergoing fertilization: results from the EARTH study. Environ Health Perspect. 2015; doi:10.1289/ehp.1509760.

    Google Scholar 

  40. Minguez-Alarcon L, Afeiche MC, Chiu YH, Vanegas JC, Williams PL, Tanrikut C, et al. Male soy food intake was not associated with in vitro fertilization outcomes among couples attending a fertility center. Andrology. 2015;3(4):702–8. doi:10.1111/andr.12046.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Gaskins AJ, Afeiche MC, Hauser R, Williams PL, Gillman MW, Tanrikut C, et al. Paternal physical and sedentary activities in relation to semen quality and reproductive outcomes among couples from a fertility center. Hum Reprod. 2014;29(11):2575–82. doi:10.1093/humrep/deu212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. McLernon DJ, Steyerberg EW, Te Velde ER, Lee AJ, Bhattacharya S. Predicting the chances of a live birth after one or more complete cycles of in vitro fertilisation: population based study of linked cycle data from 113,873 women. BMJ. 2016;355:i5735. doi:10.1136/bmj.i5735.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Ammon Avalos L, Galindo C, Li DK. A systematic review to calculate background miscarriage rates using life table analysis. Birth Defects Res A Clin Mol Teratol. 2012;94(6):417–23. doi:10.1002/bdra.23014.

    Article  CAS  PubMed  Google Scholar 

  44. Mumford SL, Schisterman EF, Cole SR, Westreich D, Platt RW. Time at risk and intention-to-treat analyses: parallels and implications for inference. Epidemiology. 2015;26(1):112–8. doi:10.1097/EDE.0000000000000188.

    Article  PubMed  Google Scholar 

  45. Maity A, Williams PL, Ryan L, Missmer SA, Coull BA, Hauser R. Analysis of in vitro fertilization data with multiple outcomes using discrete time-to-event analysis. Stat Med. 2014;33(10):1738–49. doi:10.1002/sim.6050.

    Article  PubMed  Google Scholar 

  46. Missmer SA, Pearson KR, Ryan LM, Meeker JD, Cramer DW, Hauser R. Analysis of multiple-cycle data from couples undergoing in vitro fertilization: methodologic issues and statistical approaches. Epidemiology. 2011;22(4):497–504. doi:10.1097/EDE.0b013e31821b5351.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Pearson KR, Hauser R, Cramer DW, Missmer SA. Point of failure as a predictor of in vitro fertilization treatment discontinuation. Fertil Steril. 2009;91(4 Suppl):1483–5. doi:10.1016/j.fertnstert.2008.07.1732.

    Article  PubMed  Google Scholar 

  48. Fitzmaurice GM, Laird NM, Ware JH. Missing data and dropout. Applied longitudinal analysis. Hoboken: John Wiley and Sons, Inc.; 2004.

    Google Scholar 

  49. Zhang J, Yu KF. What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 1998;280(19):1690–1.

    Article  CAS  PubMed  Google Scholar 

  50. Sunderam S, Kissin DM, Flowers L, Anderson JE, Folger SG, Jamieson DJ, et al. Assisted reproductive technology surveillance—United States, 2009. MMWR Surveill Summ. 2012;61(7):1–23.

    PubMed  Google Scholar 

  51. Austin PC, Laupacis A. A tutorial on methods to estimating clinically and policy-meaningful measures of treatment effects in prospective observational studies: a review. Int J Biostat. 2011;7(1):6. doi:10.2202/1557-4679.1285.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Zou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702–6.

    Article  PubMed  Google Scholar 

  53. Austin PC. Absolute risk reductions and numbers needed to treat can be obtained from adjusted survival models for time-to-event outcomes. J Clin Epidemiol. 2010;63(1):46–55. doi:10.1016/j.jclinepi.2009.03.012.

    Article  PubMed  Google Scholar 

  54. Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole C, Goodman SN, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016;31(4):337–50. doi:10.1007/s10654-016-0149-3.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Wasserstein R, Lazar N. The ASA’s statement on p-values: context, process, and purpose. Am Stat. 2016;70(2):129–33. doi:10.1080/00031305.2016.1154108.

    Article  Google Scholar 

  56. • Farland LV, Correia KF, Wise LA, Williams PL, Ginsburg ES, Missmer SA. P-values and reproductive health: what can clinical researchers learn from the American Statistical Association? Hum Reprod. 2016;31(11):2406–10. doi:10.1093/humrep/dew192. A thorough discussion of the utility of p-values in reproductive epidemiology research complete with recommendations for presenting results moving forward.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank Dr. Russ Hauser, Harvard T.H. Chan School of Public Health, for his invaluable feedback of this review.

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Correspondence to Audrey J. Gaskins.

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Carmen Messerlian and Audrey J. Gaskins each declare no potential conflicts of interest.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

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This article is part of the Topical Collection on Reproductive and Perinatal Epidemiology

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Messerlian, C., Gaskins, A.J. Epidemiologic Approaches for Studying Assisted Reproductive Technologies: Design, Methods, Analysis, and Interpretation. Curr Epidemiol Rep 4, 124–132 (2017). https://doi.org/10.1007/s40471-017-0105-0

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