Clinical and Experimental Reproductive Medicine

  • 제48권2호
  • /
  • Pages.163-173
  • /
  • 2021
  • /
  • 2233-8233(pISSN)
  • /
  • 2233-8241(eISSN)
대한생식의학회 (The Korean Society for Reproductive Medicine)
권호 표지
DOI QR코드

DOI QR Code

Novel nomogram-based integrated gonadotropin therapy individualization in in vitro fertilization/intracytoplasmic sperm injection: A modeling approach

  • 투고 : 2020.06.23
  • 심사 : 2020.12.10
  • 발행 : 2021.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Objective: This study aimed to characterize a validated model for predicting oocyte retrieval in controlled ovarian stimulation (COS) and to construct model-based nomograms for assistance in clinical decision-making regarding the gonadotropin protocol and dose. Methods: This observational, retrospective, cohort study included 636 women with primary unexplained infertility and a normal menstrual cycle who were attempting assisted reproductive therapy for the first time. The enrolled women were split into an index group (n=497) for model building and a validation group (n=139). The primary outcome was absolute oocyte count. The dose-response relationship was tested using modified Poisson, negative binomial, hybrid Poisson-Emax, and linear models. The validation group was similarly analyzed, and its results were compared to that of the index group. Results: The Poisson model with the log-link function demonstrated superior predictive performance and precision (Akaike information criterion, 2,704; λ=8.27; relative standard error (λ)=2.02%). The covariate analysis included women's age (p<0.001), antral follicle count (p<0.001), basal follicle-stimulating hormone level (p<0.001), gonadotropin dose (p=0.042), and protocol type (p=0.002 and p<0.001 for short and antagonist protocols, respectively). The estimates from 500 bootstrap samples were close to those of the original model. The validation group showed model assessment metrics comparable to the index model. Based on the fitted model, a static nomogram was built to improve visualization. In addition, a dynamic electronic tool was created for convenience of use. Conclusion: Based on our validated model, nomograms were constructed to help clinicians individualize the stimulation protocol and gonadotropin doses in COS cycles.

키워드

참고문헌

  1. Farquhar C, Marjoribanks J. Assisted reproductive technology: an overview of Cochrane Reviews. Cochrane Database Syst Rev 2018;8:CD010537.
  2. Lazer T, Dar S, Shlush E, Al Kudmani BS, Quach K, Sojecki A, et al. Comparison of IVF outcomes between minimal stimulation and high-dose stimulation for patients with poor ovarian reserve. Int J Reprod Med 2014;2014:581451. https://doi.org/10.1155/2014/581451
  3. Toftager M, Bogstad J, Bryndorf T, Lossl K, Roskaer J, Holland T, et al. Risk of severe ovarian hyperstimulation syndrome in GnRH antagonist versus GnRH agonist protocol: RCT including 1050 first IVF/ICSI cycles. Hum Reprod 2016;31:1253-64. https://doi.org/10.1093/humrep/dew051
  4. Siristatidis C, Salamalekis G, Dafopoulos K, Basios G, Vogiatzi P, Papantoniou N. Mild versus conventional ovarian stimulation for poor responders undergoing IVF/ICSI. In Vivo 2017;31:231-7. https://doi.org/10.21873/invivo.11050
  5. Arce JC, Andersen AN, Fernandez-Sanchez M, Visnova H, Bosch E, Garcia-Velasco JA, et al. Ovarian response to recombinant human follicle-stimulating hormone: a randomized, antimullerian hormone-stratified, dose-response trial in women undergoing in vitro fertilization/intracytoplasmic sperm injection. Fertil Steril 2014;102:1633-40. https://doi.org/10.1016/j.fertnstert.2014.08.013
  6. Nyboe Andersen A, Nelson SM, Fauser BC, Garcia-Velasco JA, Klein BM, Arce JC, et al. Individualized versus conventional ovarian stimulation for in vitro fertilization: a multicenter, randomized, controlled, assessor-blinded, phase 3 noninferiority trial. Fertil Steril 2017;107:387-96. https://doi.org/10.1016/j.fertnstert.2016.10.033
  7. Allegra A, Marino A, Volpes A, Coffaro F, Scaglione P, Gullo S, et al. A randomized controlled trial investigating the use of a predictive nomogram for the selection of the FSH starting dose in IVF/ICSI cycles. Reprod Biomed Online 2017;34:429-38. https://doi.org/10.1016/j.rbmo.2017.01.012
  8. La Marca A, Grisendi V, Giulini S, Argento C, Tirelli A, Dondi G, et al. Individualization of the FSH starting dose in IVF/ICSI cycles using the antral follicle count. J Ovarian Res 2013;6:11. https://doi.org/10.1186/1757-2215-6-11
  9. Oliveira JB, Baruffi RL, Petersen CG, Mauri AL, Nascimento AM, Vagnini L, et al. A new ovarian response prediction index (ORPI): implications for individualised controlled ovarian stimulation. Reprod Biol Endocrinol 2012;10:94. https://doi.org/10.1186/1477-7827-10-94
  10. La Marca A, Sunkara SK. Individualization of controlled ovarian stimulation in IVF using ovarian reserve markers: from theory to practice. Hum Reprod Update 2014;20:124-40. https://doi.org/10.1093/humupd/dmt037
  11. Oehninger S, Nelson SM, Verweij P, Stegmann BJ. Predictive factors for ovarian response in a corifollitropin alfa/GnRH antagonist protocol for controlled ovarian stimulation in IVF/ICSI cycles. Reprod Biol Endocrinol 2015;13:117. https://doi.org/10.1186/s12958-015-0113-1
  12. Vuong TN, Vo MT, Ho MH. Predictive value of AMH, FSH and AFC for determining ovarian response in Vietnamese women undergoing assisted reproductive technologies: a prospective study. J Fertil In Vitro IVF Worldw Reprod Med Genet Stem Cell Biol 2015;3:151.
  13. Altman DG, Royston P. The cost of dichotomising continuous variables. BMJ 2006;332:1080.
  14. Ou J, Xing W, Li Y, Xu Y, Zhou C. Short versus long gonadotropin-releasing hormone analogue suppression protocols in IVF/ICSI cycles in patients of various age ranges. PLoS One 2015;10:e0133887. https://doi.org/10.1371/journal.pone.0133887
  15. Islam Y, Aboulghar MM, AlEbrashy AE, Abdel-Aziz O. The value of different ovarian reserve tests in the prediction of ovarian response in patients with unexplained infertility. Middle East Fertil Soc J 2016;21:69-74. https://doi.org/10.1016/j.mefs.2015.08.005
  16. Felmlee MA, Morris ME, Mager DE. Mechanism-based pharmacodynamic modeling. Methods Mol Biol 2012;929:583-600. https://doi.org/10.1007/978-1-62703-050-2_21
  17. Plan EL. Modeling and simulation of count data. CPT Pharmacometrics Syst Pharmacol 2014;3:e129.
  18. Al-Azemi M, Killick SR, Duffy S, Pye C, Refaat B, Hill N, et al. Multi-marker assessment of ovarian reserve predicts oocyte yield after ovulation induction. Hum Reprod 2011;26:414-22. https://doi.org/10.1093/humrep/deq339
  19. Moon KY, Kim H, Lee JY, Lee JR, Jee BC, Suh CS, et al. Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation. Clin Exp Reprod Med 2016;43:112-8. https://doi.org/10.5653/cerm.2016.43.2.112
  20. Pinto F, Oliveira C, Cardoso MF, Teixeira-da-Silva J, Silva J, Sousa M, et al. Impact of GnRH ovarian stimulation protocols on intracytoplasmic sperm injection outcomes. Reprod Biol Endocrinol 2009;7:5. https://doi.org/10.1186/1477-7827-7-5
  21. Lukaszuk K, Kunicki M, Liss J, Lukaszuk M, Jakiel G. Use of ovarian reserve parameters for predicting live births in women undergoing in vitro fertilization. Eur J Obstet Gynecol Reprod Biol 2013;168:173-7. https://doi.org/10.1016/j.ejogrb.2013.01.013
  22. Tsakos E, Tolikas A, Daniilidis A, Asimakopoulos B. Predictive value of anti-mullerian hormone, follicle-stimulating hormone and antral follicle count on the outcome of ovarian stimulation in women following GnRH-antagonist protocol for IVF/ET. Arch Gynecol Obstet 2014;290:1249-53. https://doi.org/10.1007/s00404-014-3332-3
  23. Rustamov O, Wilkinson J, La Marca A, Fitzgerald C, Roberts SA. How much variation in oocyte yield after controlled ovarian stimulation can be explained? A multilevel modelling study. Hum Reprod Open 2017;2017:hox018. https://doi.org/10.1093/hropen/hox018
  24. Magnusson A, Nilsson L, Olerod G, Thurin-Kjellberg A, Bergh C. The addition of anti-Mullerian hormone in an algorithm for individualized hormone dosage did not improve the prediction of ovarian response-a randomized, controlled trial. Hum Reprod 2017;32:811-9. https://doi.org/10.1093/humrep/dex012
  25. Gonadotrophin therapy individualization tool [Internet]. 2021 [cited 2021 May 1]. Available at: https://individualization.shinyapps.io/dynnomapp/.
  26. Broekmans FJ. Individualization of FSH doses in assisted reproduction: facts and fiction. Front Endocrinol (Lausanne) 2019;10:181. https://doi.org/10.3389/fendo.2019.00181
  27. Drakopoulos P, Santos-Ribeiro S, Bosch E, Garcia-Velasco J, Blockeel C, Romito A, et al. The effect of dose adjustments in a subsequent cycle of women with suboptimal response following conventional ovarian stimulation. Front Endocrinol (Lausanne) 2018;9:361. https://doi.org/10.3389/fendo.2018.00361
  28. Hashish NM, Shaeer EK. Choosing the optimal dose of human menopausal gonadotropins for ovarian stimulation in ICSI cycles. Middle East Fertil Soc J 2014;19:124-8. https://doi.org/10.1016/j.mefs.2013.06.004
  29. Borges E Jr, Zanetti BF, Setti AS, Braga DP, Figueira RC, Iaconelli A Jr. FSH dose to stimulate different patient' ages: when less is more. JBRA Assist Reprod 2017;21:336-42.
  30. Zhu M, Wang S, Yi S, Huang X, Meng J, Chen L, et al. A predictive formula for selecting individual FSH starting dose based on ovarian reserve markers in IVF/ICSI cycles. Arch Gynecol Obstet 2019;300:441-6. https://doi.org/10.1007/s00404-019-05156-2
  31. Salahudeen MS, Nishtala PS. An overview of pharmacodynamic modelling, ligand-binding approach and its application in clinical practice. Saudi Pharm J 2017;25:165-75. https://doi.org/10.1016/j.jsps.2016.07.002
  32. Lensen SF, Wilkinson J, Leijdekkers JA, La Marca A, Mol BW, Marjoribanks J, et al. Individualised gonadotropin dose selection using markers of ovarian reserve for women undergoing in vitro fertilisation plus intracytoplasmic sperm injection (IVF/ICSI). Cochrane Database Syst Rev 2018;2:CD012693.
  33. Xiao JS, Su CM, Zeng XT. Comparisons of GnRH antagonist versus GnRH agonist protocol in supposed normal ovarian responders undergoing IVF: a systematic review and meta-analysis. PLoS One 2014;9:e106854. https://doi.org/10.1371/journal.pone.0106854
  34. Al-Inany HG, Youssef MA, Ayeleke RO, Brown J, Lam WS, Broekmans FJ. Gonadotrophin-releasing hormone antagonists for assisted reproductive technology. Cochrane Database Syst Rev 2016;4:CD001750.
  35. Lambalk CB, Banga FR, Huirne JA, Toftager M, Pinborg A, Homburg R, et al. GnRH antagonist versus long agonist protocols in IVF: a systematic review and meta-analysis accounting for patient type. Hum Reprod Update 2017;23:560-79. https://doi.org/10.1093/humupd/dmx017
  36. Van Belle V, Van Calster B. Visualizing risk prediction models. PLoS One 2015;10:e0132614. https://doi.org/10.1371/journal.pone.0132614
  37. Papaleo E, Zaffagnini S, Munaretto M, Vanni VS, Rebonato G, Grisendi V, et al. Clinical application of a nomogram based on age, serum FSH and AMH to select the FSH starting dose in IVF/ICSI cycles: a retrospective two-centres study. Eur J Obstet Gynecol Reprod Biol 2016;207:94-9. https://doi.org/10.1016/j.ejogrb.2016.10.021
  38. Zhou J, Wang B, Hu Y, Sun H. Association between the number of oocytes retrieved and cumulative live birth rate in women aged 35-40 years undergoing long GnRH agonist IVF/ICSI cycles. Arch Gynecol Obstet 2017;296:1005-12. https://doi.org/10.1007/s00404-017-4503-9
  39. Farmer KC. Methods for measuring and monitoring medication regimen adherence in clinical trials and clinical practice. Clin Ther 1999;21:1074-90. https://doi.org/10.1016/S0149-2918(99)80026-5