The Success Rate and Factors Affecting the Outcome of Assisted Reproductive Treatment in Subfertile Men
Background: This study was conducted to evaluate the success rate of male infertility treatment and the factors affecting its outcome.
Methods: In a historical cohort study, from Mar 2013 to Mar 2014, 323 couples with male factor were investigated. Couples had treated with IUI or/and ICSI were included randomly. Assisted reproduction technology (ART) outcome (treatment success) was defined as a live birth. Age, duration of infertility, type of infertility, treatment history and clinical examination results were investigated. The logistic regression and survival analysis were applied.
Results: The average of men age, duration of infertility and BMI were 33.5, 4.7 (yr) and 26.6 (kg/m2) respectively. 87.9% of men have primary infertility and average duration of treatment was 14.1(month). Previous treatment, type of infertility, treatment method, man's BMI, normality of sperm and sperm head were important variable that affecting outcome. The rate of live birth in the first attempt was 29.7%, and 44.9% of the couples succeeded to give live birth after several treatment cycles. Couples who had no previous history of treatment were 8.5 times more successful in live birth. The Cox analysis showed that "BMI of man" and percentage of "Sperm with normal head" are predictors that had a significant effect on live birth.
Conclusion: Live birth in the first treatment cycles was influenced by four variables but two other variable were affecting several treatment cycles outcome. The chances of successful treatment were higher with taking into account the length of time and having live birth was determined as 78% for five years of continuous treatment.
2. Kazemijaliseh H, Behboudi-Gandevani S, Hosseinpanah F, Khalili D, Azizi F (2015). The Prevalence and Causes of Primary Infertility in Iran: A Population-Based Study. Glob J Health Sci, 7(6):226-232.
3. Akhondi M, kamali K, Ranjbar F et al (2013). Prevalence of Primary Infertility in Iran in 2010. Iran J Public Health, 42(12):1398-1404.
4. Centers for Disease Control and Preven-tion, American Society for Reproductive Medicine, Society for Assisted Reproduc-tive Technology (2017). 2015 Assisted Reproductive Technology National Summary Report. Atlanta (GA): US Dept of Health and Human Services.
5. van Loendersloot L, Repping S, Bossuyt PM, et al (2014). Prediction models in in vitro fertilization where are we? A mini review. J Adv Res, 5:295-301.
6. Peter AO, Temi AP, Olufemi AP et al (2016). Pattern of Semen Parameters and Factors Associated with Infertility in Male Part-ners of Infertile Couples in Nigeria. An-drology (Los Angel), 5: 161.
7. Borges Jr E, Zanetti BF, Braga DPdAF et al (2017). Overcoming male factor infertility with intracytoplasmic sperm injection. Rev Assoc Med Bras(1992), 63(8):697-703.
8. Zarinara A, Zeraati H, Kamali K, Moham-mad K, Shahnazari P, Akhondi MM (2016). Models predicting success of in-fertility treatment: A systematic review. J Reprod Infertil, 17(2):68-81.
9. Samani RO, Almasi-Hashiani A, Shokri F, Maroufizadeh S, Vesali S, Sepidarkish M (2017). Validation study of the Fertility Problem Inventory in Iranian infertile pa-tients. Middle East Fertil. Soc. J, 22(1):48-53.
10. Skakkebaek NE, Rajpert-De Meyts E, et al (2015). Male reproductive disorders and fertility trends: Influences of environment and genetic susceptibility. Physiol Rev, 96(1):55-97.
11. Tjon-Kon-Fat RI, Wang R, Eijkemans MJ et al (2019). Interventions for unexplained subfertility: A systematic review and net-work meta-analysis. (The Cochrane Library) Cochrane Database Syst Rev, 5;9:CD012692.
12. Dessolle L, Barrière P, Fréour T (2016). Models for predicting live birth before a first IVF cycle. Hum Reprod, 31(6):1375.
13. Van Geloven N, Van der Veen F, Bossuyt P, Hompes P, Zwinderman A, Mol B (2013). Can we distinguish between infer-tility and subfertility when predicting nat-ural conception in couples with an unful-filled child wish? Hum Reprod, 28(3):658-65.
14. Tomassetti C, Geysenbergh B, Meuleman C, Timmerman D, Fieuws S, D'Hooghe T (2013). External validation of the endo-metriosis fertility index (EFI) staging sys-tem for predicting non-ART pregnancy after endometriosis surgery. Hum Reprod, 28(5):1280-8.
15. van der Steeg JW, Steures P, Eijkemans MJ et al (2008). Predictive value of pregnancy history in subfertile couples: Results from a nationwide cohort study in the Nether-lands. Fertil Steril, 90(3):521-7.
16. Tournaye H (2012). Male factor infertility and ART. Asian J Androl, 14(1):103-8.
17. McLernon DJ, Steyerberg EW, Te Velde ER, Lee AJ, Bhattacharya S (2016). Pre-dicting the chances of a live birth after one or more complete cycles of in vitro fertilisation: Population based study of linked cycle data from 113873 women. BMJ, 16;355:i5735.
18. Bensdorp AJ, van der Steeg JW, Steures P et al (2017). A revised prediction model for natural conception. Reprod Biomed Online, 34(6):619-626.
19. Vaegter KK, Lakic TG, Olovsson M, Ber-glund L, Brodin T, Holte J (2017). Which factors are most predictive for live birth after in vitro fertilization and intracyto-plasmic sperm injection (IVF/ICSI) treatments? Analysis of 100 prospectively recorded variables in 8400 IVF/ICSI sin-gle-embryo transfers. Fertil Steril, 107(3):641-648.e2.
20. Zhang H, Legro RS, Zhang J et al (2010). Decision trees for identifying predictors of treatment effectiveness in clinical trials and its application to ovulation in a study of women with polycystic ovary syn-drome. Hum Reprod, 25(10):2612-21.
21. Isa AM, Abu-Rafea B, Alasiri SA et al (2014). Accurate diagnosis as a prognostic factor in intrauterine insemination treatment of infertile Saudi patients. J Reprod Infertil, 15(4):184-9.
22. Jedrzejczak P, Taszarek-Hauke G, Hauke J, Pawelczyk L, Duleba AJ (2008). Predic-tion of spontaneous conception based on semen parameters. Int J Androl, 31(5):499-507.
23. Yi Y, Lu G, Ouyang Y, Gong F, Li X (2016). A logistic model to predict early pregnancy loss following in vitro fertiliza-tion based on 2601 infertility patients. Re-prod Biol Endocrinol, 31;14:15.
24. Merviel P, Heraud MH, Grenier N, Lourdel E, Sanguinet P, Copin H (2010). Predic-tive factors for pregnancy after intrauter-ine insemination (IUI): An analysis of 1038 cycles and a 6review of the literature. Fertil Steril, 93(1):79-88.
25. Sabbaghian M, Modarresi T, Hosseinifar H et al (2013). Predictive value of semen pa-rameters and age of the couple in preg-nancy outcome after Intrauterine insemi-nation. Tehran University Medical Journal, 71(8):530-535.
26. Meijerink AM, Ramos L, Fleischer K, Velt-man JA, Hendriks JC, Braat DD (2016). Influence of paternal age on ongoing pregnancy rate at eight weeks' gestation in assisted reproduction. Reprod Biomed Online, 32(1):96-103.
27. Sermondade N, Dupont C, Faure C et al (2013). Body mass index is not associated with sperm–zona pellucida binding ability in subfertile males. Asian J Androl, 15(5): 626–629.
28. Kort HI, Massey JB, Elsner CW et al (2006). Impact of body mass index values on sperm quantity and quality. J Androl, 27(3):450-2.
29. MacDonald AA, Stewart AW, Farquhar CM (2013). Body mass index in relation to semen quality and reproductive hor-mones in New Zealand men: A cross-sectional study in fertility clinics. Hum Re-prod, 28(12):3178-87.
30. Repokari L, Punamäki R-L, Unkila-Kallio L et al (2007). Infertility treatment and mari-tal relationships: A 1-year prospective study among successfully treated ART couples and their controls. Hum Reprod, 22(5):1481-91.
31. Janosek-Albright KJ, Schlegel PN, Dabaja AA (2015). Testis sperm extraction. Asian J Urol, 2(2):79-84.
32. Palermo GD, Neri QV, Monahan D, Ko-cent J, Rosenwaks Z (2012). Develop-ment and current applications of assisted fertilization. Fertil Steril, 97(2):248-59.
33. Luke B, Brown MB, Wantman E et al (2014). A prediction model for live birth and multiple births within the first three cycles of assisted reproductive technolo-gy. Fertil Steril, 102(3):744-52.
34. Wichmann L, Isola J, Tuohimaa P (1994). Prognostic variables in predicting preg-nancy: A prospective follow up study of 907 couples with an infertility problem. Hum Reprod, 9(6):1102-8.
35. Lintsen A, Eijkemans M, Hunault C et al (2007). Predicting ongoing pregnancy chances after IVF and ICSI: A national prospective study. Hum Reprod, 22(9):2455-62.