Pregnancy outcomes after superovulation-intrauterine insemination (SO-IUI) using gonadotropins versus letrozole in the obese population

PURPOSE: To compare fertility outcomes of obese patients (body mass index [BMI] ≥ 30 kg/m2) undergoing superovulation and intrauterine insemination (SO-IUI) using gonadotropins versus letrozole. METHODS: A single centre retrospective cohort study of obese patients undergoing SO-IUI using gonadotropins or letrozole between January/2019 and June/2022. Primary outcome was clinical pregnancy rate (intrauterine pregnancy with positive fetal heart rate). Secondary outcomes included rates of multifollicular development, multiple pregnancy, spontaneous abortion and cycle cancellation. Subgroup analysis was done stratifying by obesity class. A multivariate logistic regression model was used for primary/secondary outcomes, adjusting for clinically determined covariates. RESULTS: Out of 802 total identified SO-IUI cycles, 715 cycles were completed (518-gonadotropins and 197-letrozole cycles). The clinical pregnancy rates were not significantly different in obese patients undergoing SO-IUI with gonadotropins versus letrozole when adjusted for age, gravidity, parity, cause of infertility, IUI cycle number, endometrial thickness, sperm source and post-wash motile sperm count (adjusted odds ratio [aOR] 1.37, 95% confidence interval [CI] 0.72-2.59). Similarly, no significant associations were found in spontaneous abortion (aOR1.46, 95%CI 0.42-5.08), multiple pregnancy (aOR1.33, 95%CI 0.20-8.88) or cancellation rates (OR0.89, 95%CI 0.55-1.45) between the two groups. The rates of multifollicular development were also comparable between the two groups (aOR0.51, 95% CI 0.19-1.38). For cycles involving gonadotropins, higher BMI classes required higher total gonadotropin dose (p < 0.001). CONCLUSION: After adjusting for patient and cycle factors, gonadotropins and letrozole led to comparable odds of achieving pregnancy in obese patients undergoing SO-IUI. Future research in the obese population will help to better understand how to optimize fertility treatments for this growing population.