Anti-Müllerian hormone concentrations and antral follicle counts for the prediction of pregnancy outcomes after intrauterine insemination

Anti-Müllerian hormone does not predict cumulative pregnancy rate in non-infertile women following four IUI cycles with donor sperm

PURPOSE

To evaluate the predictive value of serum AMH for clinical pregnancy in non-infertile population undergoing intrauterine insemination with donor sperm (ds-IUI).

METHODS

This multicenter prospective study (ClinicalTrials.gov ID: NCT06263192) recruited all non-infertile women undergoing ds-IUI from June 2020 to December 2022 in three different fertility clinics in Spain and Chile. Indications for ds-IUI included severe oligoasthenoteratozoospermia, female partner, or single status. Clinical pregnancy rates were compared between women with AMH ≥ 1.1 and < 1.1 ng/mL. The main outcome measure was the cumulative clinical pregnancy rate after up to 4 ds-IUI cycles.

RESULTS

A total of 458 ds-IUI cycles were performed among 245 patients, of whom 108 (44.08%) achieved clinical pregnancy within 4 cycles, 60.2% of these occurring in the first attempt and 84.2% after two attempts. We found no significant differences in AMH levels or other parameters (such as age, BMI, FSH, AFC) between women who became pregnant and those who did not. Cumulative pregnancy rates and logistic regression analysis revealed that AMH ≥ 1.1 ng/mL was not predictive of ds-IUI success. While a high positive correlation was observed between AFC and AMH (r = 0.67, p < 0.001), ROC curve analyses indicated that neither of these ovarian reserve markers accurately forecasts cumulative ds-IUI outcomes in non-infertile women.

CONCLUSIONS

The findings of this multicenter study suggest that AMH is not a reliable predictor of pregnancy in non-infertile women undergoing ds-IUI. Even women with low AMH levels can achieve successful pregnancy outcomes, supporting the notion that diminished ovarian reserve should not restrict access to ds-IUI treatments in eligible non-infertile women.

Anti-Müllerian hormone for screening, diagnosis, evaluation, and prediction: A systematic review and expert opinions

AIM

To present evidence-based recommendations for anti-Müllerian hormone (AMH) measurement as an ovarian reserve test.

METHODS

A systematic literature search for the clinical utility of AMH was conducted in PubMed from its inception to August 2022 to identify studies, including meta-analyses, reviews, randomized controlled trials, and clinical trials, followed by an additional systematic search using keywords. Based on this evidence, an expert panel developed clinical questions (CQs).

RESULTS

A total of 1895 studies were identified and 95 articles were included to establish expert opinions subdivided into general population, infertility treatment, primary ovarian insufficiency, polycystic ovary syndrome, surgery, and oncofertility. We developed 13 CQs and 1 future research question with levels of evidence and recommendations.

CONCLUSION

The findings of the current systematic review covered the clinical utility of AMH including its screening, diagnosis, evaluation, and prediction. Although some clinical implications of AMH remain debatable, these expert opinions may help promote a better understanding of AMH and establish its clinical significance.

The Value of Anti-Müllerian Hormone in Predicting Ovulation Induced by Aromatase Inhibitors in Women With Polycystic Ovary Syndrome

OBJECTIVES

This study aimed to evaluate the value of anti-Müllerian hormone (AMH) in predicting ovulation induced by aromatase inhibitors (AI) and pregnancy outcomes in women with polycystic ovary syndrome (PCOS).

METHODS

From January 2018 to December 2020, this prospective cohort study enrolled women with PCOS aged between 18 and 45 years who underwent ovulation induction using AI protocol and intrauterine insemination (IUI) for infertility at a Center for Reproductive Endocrinology and Infertility, University Hospital. Receiver operating characteristic curves were used to estimate the chance of ovulation responses and pregnancy outcomes.

RESULTS

In total, 64% of 65 women with PCOS were recruited following AI treatment, and the clinical pregnancy rate was 19.4% following IUI. Patients who experienced ovulation had a lower mean serum AMH concentration than non-responders (7.11 ng/mL vs. 8.95 ng/mL, respectively), but the difference was not statistically significant. Between the pregnancy and non-pregnancy groups, statistically significant differences in AMH concentrations were observed (8.71 ng/mL vs. 6.73 ng/mL, respectively, P = 0.040). The area under the curve of the receiver operating characteristic for non-ovulation prediction was 0.445, 95% CI (0.284-0.606) with P = 0.467, and for clinical pregnancy was 0.735, 95% CI (0.561-0.910) with P = 0.104.

CONCLUSIONS

In women with PCOS, the AMH level does not predict ovarian responsiveness to AI treatment, but it does predict the success of IUI cycles.

Anti-Müllerian Hormone: A Predictor of Successful Intrauterine Insemination

INTRODUCTION

The anti-Müllerian hormone (AMH) produced by the granulosa cells of ovarian follicles has been shown to correlate with ovarian reserve and is often measured for fertility therapies. In this study, we evaluated the relationship between serum AMH values and the clinical pregnancy (CP) rates of female partners with unexplained infertility undergoing intrauterine insemination utilizing varying ovarian simulation protocols.

METHODS

This is a retrospective cohort study conducted among couples who underwent intrauterine insemination therapy over a period of four years at Charleston Area Medical Center, a tertiary care medical center in West Virginia, USA. Logistic regression was used to determine the best predictor of CP.

RESULTS

A total of 509 intrauterine inseminations resulting in 81 (15.9%) Cps were analyzed. The cycles with a CP had higher mean AMH values (3.7+3.5 vs. 2.2+2.1; p<0.001). The majority of patients were nulliparous (77.0%) with a mean age of 33.6+5.0 years. After including only patients with unexplained infertility (the predominate infertility diagnosis; n=255 (50.1% of the cycles)) and stimulation cycles >10, the final sample size for the analysis was 245/509=48.1%. Following a receiver operating characteristic (ROC) curve analysis, the optimal AMH cut-off point was 2.1 ng/mL with an area under the curve (AUC) equal to 0.61 and 95% confidence intervals (CIs) of 0.55- 0.67 (p=0.002). The CP rate was significantly higher with the AMH >2.1 ng/mL (20.0%) compared to <2.1 ng/mL (10.0%; p=0.041). With Clomid/human gonadotropins/human chorionic gonadotropin (hCG) trigger treatment, the CP rate quadrupled (odds ratio (OR): 4.6; 95% CI: 2.1-9.7; p<0.001).

CONCLUSION

This study indicates that higher AMH levels and a more aggressive ovarian stimulation protocol for intrauterine insemination therapy (IUI) have a better probability of resulting in CP.

Investigation of the Predictive Factors of Diminished Ovarian Reserve in Women Aged Less Than 40 Years and Undergoing ICSI Cycle

Diminished ovarian reserve (DOR) is one of the primary causes of poor ICSI outcomes. Therefore, this study was performed to speculate which of the following parameters: AMH, AFC, and women's age can be used as a predictor factor of the DOR in women aged < 40 years. This prospective study enrolled 500 women suffering from idiopathic infertility problems and who underwent GnRH antagonist multiple-dose stimulation protocol. The women were divided into two groups: normal fertility (FSH ≤ 10 mIU/mL, n = 300) and DOR (FSH > 10 mIU/mL, n = 200). At the time of the study, the average of women age was 29.3 ± 5.7 years. A significant reduction was found in AMH level, AFC, number of mature, immature oocytes, fertilized oocytes, embryos transferred, and β-hCG level in the DOR group compared to the normal fertility group (P < 0.001). Conversely, a significant increase was shown in the age of the DOR group compared to the normal fertility group (30.8 ± 5.8 vs. 28.2 ± 5.4, respectively; P < 0.001). A significant negative association was found between the AFC, the number of mature oocytes, fertilized oocytes, embryos transferred, and the basal level of FSH in the DOR group (P < 0.01). The receiver operating characteristics (ROC) demonstrated that AMH level and AFC had the highest accuracy, followed by age in the prediction of DOR (P < 0.001) with a cut-off value of ≤ 1.2 ng/mL, ≤ 4.5, and > 29.5 years, respectively. This study exhibited that the levels of AMH and AFC are the best biomarkers, followed by age for the prediction of DOR in women < 40 years old. Furthermore, AMH is the only independent factor that is significantly related to DOR in women.

Factors Influencing the Pregnancy Outcome of Intrauterine Insemination and Follow-up Treatment

Background

Many factors were reported associated with the pregnancy rate of intrauterine insemination (IUI), which played key role is still debated.

Aims

The aim of this study was to explore related clinical pregnancy outcome factor in IUI cycles of non-male factor.

Settings and Design

The clinical data of 1232 IUI cycles in 690 couples experiencing infertility who attended the Reproductive Center of Jinling Hospital between July 2015 and November 2021 were retrospectively analysed.

Materials and Methods

Female and male age, body mass index (BMI), anti-Müllerian hormone (AMH), male semen parameters before and after wash, endometrial thickness (EMT), artificial insemination timing and ovarian stimulation (OS) protocols were compared between the pregnant group and the non-pregnant group in order to explore any correlation.

Statistical Analysis Used

Continuous variables were analysed using independent-samples t-test, and Chi-square test was used for comparison of measurement data between the two groups. P <0.05 was considered statistical significance.

Results

There were statistically significant differences in female AMH, EMT and duration of OS between the two groups. The AMH was higher in the pregnant group than in the non-pregnant group (P < 0.01), the stimulated days was significantly longer (P < 0.05) and EMT was significantly greater (P < 0.01) in the pregnant group than in the non-pregnant group. Further analysis showed that when patients with IUI had the following conditions: AMH > 4.5 ng/ml, EMT between 8 and 12 mm and letrozole + human menopausal gonadotropin stimulation with higher clinical pregnancy. However, there were no differences between the pregnant group and the non-pregnant group amongst the female and male age, BMI, hormones on baseline and day of human chorionic gonadotrophin, number of ovulated oocytes, sperm parameters before and after wash, treatment protocols and the timing of IUI (P > 0.05). Furthermore, there were 240 couples who not pregnant received one or more cycles of in vitro fertilisation/intracytoplasmic sperm injection/ pre-implantation genetic technology treatment, and another 182 couples forgo follow-up treatment.

Conclusion

The results of the present study demonstrate that the clinical IUI pregnancy rate is correlated with the factors of female AMH, EMT and OS protocol; more studies and samples are necessary to evaluate whether other factors affect pregnancy rate.

Predictive factors of ovarian response to GnRH antagonist stimulation protocol: AMH and age are potential candidates

Background

Prediction of ovarian response prior to the ovarian stimulation cycle is useful in determining the optimal starting dose of recombinant follicle-stimulating hormone (r-FSH). This study was designed to (I) evaluate which of the following parameters (age, AMH, and FSH) can be used as a predictor of ovarian response to GnRH antagonist stimulation protocol, (II) determine the cutoff value of AMH and age for predicting poor and high ovarian response, and (III) investigate the relationship between age, AMH level, and other clinical parameters. It is a retrospective study. A total of 318 women with a mean age of 28.2 ± 5.9 years old were included in this study. Hormone levels (FSH, LH, PRL, E2, and AMH) and the number of collected oocytes were determined. Based on the number of retrieved oocytes, the participants were divided into three groups: poor response (oocytes < 4, n= 51), normal response (oocytes 4–14, n= 192), and high response (oocytes > 14, n= 75).

Results

A significant increase has been found in AMH level and number of retrieved oocytes and mature oocytes from low to normal and high ovarian response group (P < 0.001). Also, the age in the poor ovarian response group was significantly greater than normal and high ovarian response groups (P < 0.001). A significant positive correlation has been found between the number of retrieved oocytes and mature oocytes and level of AMH (P < 0.001). The receiver operating characteristic (ROC) curves showed that both AMH and age had the highest accuracy in the prediction of poor ovarian response with a cutoff value < 1.45 and > 31.5 years, respectively. Additionally, the ROC analysis has shown that the AMH had the highest accuracy, followed by age in the prediction of high ovarian response with a cutoff value > 3.55 and < 27.5 years, respectively.

Conclusions

This study demonstrates that AMH level and women’s age may be used as potential predictors of ovarian response to GnRH antagonist stimulation protocol.

CNFE-SE: a novel approach combining complex network-based feature engineering and stacked ensemble to predict the success of intrauterine insemination and ranking the features

Background

Intrauterine Insemination (IUI) outcome prediction is a challenging issue which the assisted reproductive technology (ART) practitioners are dealing with. Predicting the success or failure of IUI based on the couples' features can assist the physicians to make the appropriate decision for suggesting IUI to the couples or not and/or continuing the treatment or not for them. Many previous studies have been focused on predicting the in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) outcome using machine learning algorithms. But, to the best of our knowledge, a few studies have been focused on predicting the outcome of IUI. The main aim of this study is to propose an automatic classification and feature scoring method to predict intrauterine insemination (IUI) outcome and ranking the most significant features.

Methods

For this purpose, a novel approach combining complex network-based feature engineering and stacked ensemble (CNFE-SE) is proposed. Three complex networks are extracted considering the patients' data similarities. The feature engineering step is performed on the complex networks. The original feature set and/or the features engineered are fed to the proposed stacked ensemble to classify and predict IUI outcome for couples per IUI treatment cycle. Our study is a retrospective study of a 5-year couples' data undergoing IUI. Data is collected from Reproductive Biomedicine Research Center, Royan Institute describing 11,255 IUI treatment cycles for 8,360 couples. Our dataset includes the couples' demographic characteristics, historical data about the patients' diseases, the clinical diagnosis, the treatment plans and the prescribed drugs during the cycles, semen quality, laboratory tests and the clinical pregnancy outcome.

Results

Experimental results show that the proposed method outperforms the compared methods with Area under receiver operating characteristics curve (AUC) of 0.84 ± 0.01, sensitivity of 0.79 ± 0.01, specificity of 0.91 ± 0.01, and accuracy of 0.85 ± 0.01 for the prediction of IUI outcome.

Conclusions

The most important predictors for predicting IUI outcome are semen parameters (sperm motility and concentration) as well as female body mass index (BMI).

Clinical Application of AMH Measurement in Assisted Reproduction

Anti-Müllerian hormone reflects the continuum of the functional ovarian reserve, and as such can predict ovarian response to gonadotropin stimulation and be used to individualize treatment pathways to improve efficacy and safety. However, consistent with other biomarkers and age-based prediction models it has limited ability to predict live birth and should not be used to refuse treatment, but rather to inform counselling and shared decision making. The use of absolute clinical thresholds to stratify patient phenotypes, assess discordance and individualize treatment protocols in non-validated algorithms combined with the lack of standardization of assays may result in inappropriate classification and sub-optimal clinical decision making. We propose that holistic baseline phenotyping, incorporating antral follicle count and other patient characteristics is critical. Treatment decisions driven by validated algorithms that use ovarian reserve biomarkers as continuous measures, reducing the risk of misclassification, are likely to improve overall outcomes for our patients.

Age-specific anti-Mullerian hormone (AMH) levels poorly affects cumulative live birth rate after intra-uterine insemination

Objective

To evaluate the impact of age-specific anti-Mullerian (AMH) levels on the cumulative live birth rate after 4 intra uterine inseminations (IUI).

Study Design

The retrospective study study involved 509 couples who underwent their first IUI between January 2011 and July 2017 in the Toulouse University Hospital. All IUI were performed after an ovarian stimulation combining recombinant FSH and GnRH antagonist. The main measure outcome was the cumulative live birth rate (LBR) defined as the number of deliveries with at least one live birth resulting from a maximum of 4 IUI attempts.

Results

When compared to normal or high levels, low age-specific AMH (<25th of the AMH in each age group) was associated to a non-significant lower live birth rate (31%, 38% and 42% respectively for low, normal and high age-specific groups; P = 0.170) and non-significant higher miscarriage rate (26%; 19% and 14% respectively for low, normal and high age-specific groups; P = 0.209). However, it must be pointed out that in low age-specific AMH the initial FSH doses used for stimulation were higher than in the other groups.

Conclusion

This study shows that the age-specific levels of AMH have only a slight effect on IUI outcome when adapting the stimulation protocols to their level.

The role of anti-Müllerian hormone in prediction of pregnancy in young and older women with unexplained infertility undergoing intrauterine insemination

BACKGROUND

Serum anti-Müllerian hormone (AMH) level is considered to be a reliable marker of ovarian reserve. However, there are conflicting reports on the role of AMH level in predicting pregnancy after intrauterine insemination (IUI) cycles. The aim of this study is to investigate the clinical value of AMH in predicting pregnancy in younger and older women with unexplained infertility undergoing gonadotropin stimulation and IUI.

METHODS

The medical records of 84 women who underwent first gonadotropin-stimulated IUI cycle owing to unexplained infertility were retrospectively evaluated. The relation of AMH levels with clinical pregnancy rate was analyzed.

RESULTS

The overall clinical pregnancy rate was 19%. There was no significant difference in AMH levels between the pregnant and nonpregnant women (2.0 ± 1.0 vs 2.8 ± 2.0 ng/mL, respectively, p = 0.250). A further analysis according to age also failed to reveal significant differences in AMH levels between pregnant and nonpregnant women for both the younger (<35 years, n = 61) and the older (≥35 years, n = 23) subgroups (p = 0.714 and 0.532, respectively). Post-hoc power analysis showed a power of 0.80 with a 5% level of significance and a 0.8 effect size.

CONCLUSION

These findings indicate that AMH levels cannot predict pregnancy in women with unexplained infertility undergoing gonadotropin-stimulated IUI cycle. In addition, AMH is not a strong predictive factor for pregnancy either in younger or older women.

The Value of Anti-Müllerian Hormone in Predicting Clinical Pregnancy After Intrauterine Insemination

OBJECTIVES

To evaluate the utility of anti-Müllerian hormone (AMH) in predicting clinical pregnancy with intrauterine insemination (IUI) and compare it to other markers of quantitative ovarian reserve.

METHODS

Retrospective cohort study of women undergoing natural and stimulated IUI cycles. All patients achieved a clinical pregnancy within three IUI cycles or completed three IUI cycles without pregnancy. Receiver operating curves were generated to determine the ability of AMH, antral follicle count, age, BMI, and day 3 FSH to predict clinical pregnancy with IUI. Characteristics of those with and without pregnancy were compared using Mann-Whitney U, chi-square, and Fisher exact tests.

RESULTS

Of 209 women included, 49% achieved clinical pregnancy. Pregnant patients were more likely to have a higher AMH (2.76 vs. 1.55 ng/mL, P = 0.0004). The area under the curve was 0.642 in predicting clinical pregnancy within three IUI cycles using AMH (0.608 if excluding polycystic ovarian syndrome patients); 0.639 using antral follicle count; 0.549 using age; 0.599 using day 3 FSH; and 0.639 using BMI.

CONCLUSION

Although serum AMH appears significantly higher in women achieving clinical pregnancy, the predictive value of AMH alone was no better than that for other markers of quantitative ovarian reserve in a patient who clinically qualifies for IUI.

Retrospective cohort study: AMH is the best ovarian reserve markers in predicting ovarian response but has unfavorable value in predicting clinical pregnancy in GnRH antagonist protocol

BACKGROUND

Various ovarian reserve markers have been used to predict ovarian response and pregnancy. However, concerning Chinese population, fewer trials have been performed using the combined ovarian reserve markers to predict ovarian response and pregnancy in GnRH antagonist protocols.

METHODS

Data from a total of 373 patients' in vitro fertilization cycles using GnRH antagonist protocol was retrospectively included. According to our center's daily practice, circulating follicle-stimulating hormone, luteinizing hormone, and estradiol (E2) were tested on menstrual cycle day 2-4 or hCG trigger day, and the concentration of AMH was determined despite of menstrual cycle. The antral follicle count (AFC) was assessed by transvaginal ultrasound on day 2-4 of menstrual cycle. Different ovarian response was defined as 0-4 and 5-15 and >15 oocyte retrieved for low and normal and high ovarian response, respectively. Gestational sac with fetal heartbeat detected by ultrasound was considered as clinical pregnancy.

RESULTS

Serum AMH levels was the most accurate marker in predicting ovarian response [area under the receiver operating characteristic (ROC) curve = 0.767]. Significant difference was found in age between non-clinical pregnancy and clinical pregnancy groups (p < 0.001).

CONCLUSIONS

Our data demonstrated that the circulating AMH despite of menstrual cycle was preferable in prediction of oocyte retrieved outcome during GnRH antagonist protocol than age, AFC and the other currently used hormone markers. Furthermore, age is the only marker in predicting clinical pregnancy.