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

Ovarian response to controlled stimulation and its predictors in a limited-resource setting

BACKGROUND

Infertility remains a serious health concern for Ethiopian women. Most of its treatment approaches entail controlled ovarian stimulation, the responses of which vary. However, there are no data on ovarian response to stimulation or its predictors in our situation. Thus, the current study aimed to assess the ovarian response to controlled stimulation and identify predictors.

METHODS

A retrospective follow-up study was undertaken from April 1, 2021, to March 31, 2022, among patients who had first-cycle controlled ovarian stimulation at St.Paul's Hospital Fertility Center in Addis Ababa, Ethiopia. Clinical data were extracted using a checklist. SPSS-26 for data analysis and Epidata-4.2 for data entry were employed. The binary logistic regression model was fitted. A p-value < 0.05 indicated a significant association. The ROC curve was used to determine cutoff values and identify accurate predictors.

RESULTS

A total of 412 study participants were included in the final analysis. The patients had a mean age of 32.3 ± 5.1 years (range: 20 - 4). The good ovarian response rate was 67% (95% CI: 62.2-71.5). An anti-Mullerian hormone (AMH) concentration < 1.2ng/ml (AOR = 0.19, 95% CI (0.06-0.57)), an antral follicle count (AFC) < 5 (AOR = 0.16, 95% CI (0.05-0.56)), and an induction length < 10 days (AOR = 0.23, 95% CI (0.06-0.93)) were significantly associated with ovarian response. The prediction accuracies for the AFC and AMH concentrations were 0.844 and 0.719, respectively. The optimal cutoff point for prediction was 5.5 AFC, which had a sensitivity of 77.2% and a specificity of 72.8%. However, its positive and negative predictive values were 85.2% and 61.1%, respectively. For AMH, the optimal cutoff value was 0.71ng/mL, with a corresponding sensitivity and specificity of 65.2% and 66%. At this value, the positive and negative predictive values were 63.8% and 67.3%, respectively.

CONCLUSION

Only two-thirds of our patients achieved a good ovarian response. Induction duration, AMH concentration, and AFC were found to be predictors, with the AFC being the strongest predictor. Therefore, the AFC should be performed on all of our patients, and the AMH is selectively employed. Future research must verify the best cutoff points and investigate additional factors affecting ovarian response.

Impact of mildly evaluated thyroid-stimulating hormone levels on in vitro fertilization or intracytoplasmic sperm injection outcomes in women with the first fresh embryo transfer: a large study from China

PURPOSE

This study aimed to investigate the association between mild elevation of thyroid-stimulating hormone (TSH) levels and pregnancy outcomes of in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatments in women with the first fresh embryo transfer.

METHODS

Large single-center retrospective cohort study of 15,728 patients from January 2018 to December 2022 were enrolled in the analyses. Clinical pregnancy rates, live birth rates, miscarriage rates, and ectopic pregnancy rates were compared between the TSH levels < 2.5 mIU/L group (N = 10,932) and TSH levels ≥ 2.5 mIU/L group (N = 4796). Subgroup analysis was performed for patients with TSH levels ≥ 2.5 mIU/L, dividing them into the thyroid peroxidase antibody (TPO)-negative group (N = 4524) and the TPO-positive group (N = 272).

RESULTS

There were no significant differences in the aforementioned pregnancy outcomes between the TSH levels < 2.5 mIU/L group and TSH levels ≥ 2.5 mIU/L group. Similarly, no significant differences were observed in the pregnancy outcomes between the TPO-negative group and the TPO-positive group.

CONCLUSION

Mildly elevated pre-conception TSH levels in thyroid-normal infertile patients did not have an impact on pregnancy outcomes of IVF/ICSI treatments.

A prediction model for high ovarian response in the GnRH antagonist protocol

Backgrounds

The present study was designed to establish and validate a prediction model for high ovarian response (HOR) in the GnRH antagonist protocol.

Methods

In this retrospective study, the data of 4160 cycles were analyzed following the in vitro fertilization (IVF) at our reproductive medical center from June 2018 to May 2022. The cycles were divided into a training cohort (n=3121) and a validation cohort (n=1039) using a random sampling method. Univariate and multivariate logistic regression analyses were used to screen out the risk factors for HOR, and the nomogram was established based on the regression coefficient of the relevant variables. The area under the receiver operating characteristic curve (AUC), the calibration curve, and the decision curve analysis were used to evaluate the performance of the prediction model.

Results

Multivariate logistic regression analysis revealed that age, body mass index (BMI), follicle-stimulating hormone (FSH), antral follicle count (AFC), and anti-mullerian hormone (AMH) were independent risk factors for HOR (all P< 0.05). The prediction model for HOR was constructed based on these factors. The AUC of the training cohort was 0.884 (95% CI: 0.869-0.899), and the AUC of the validation cohort was 0.884 (95% CI:0.863-0.905).

Conclusion

The prediction model can predict the probability of high ovarian response prior to IVF treatment, enabling clinicians to better predict the risk of HOR and guide treatment strategies.

Does Endometriosis Impact the Composition of Follicular Fluid in IL6 and AMH? A Case-Control Study

OBJECTIVE

The aim of this study was to compare follicular liquid levels of IL6 and AMH in women with and without endometriosis and to evaluate their potential impact on ICSI outcomes.

MATERIALS AND METHODS

It is a prospective case-control study conducted on 25 women with proven endometriosis and 50 patients diagnosed with other causes of infertility. All these patients were candidates for ICSI cycles. Their follicular fluid was collected at the time of oocyte retrieval and used to evaluate IL-6 and AMH titers by electro-chemiluminescent immunoassay (Cobas e411-Roche).

RESULTS

The IL-6 levels in follicular fluid were higher in the endometriosis group than in the control group (152.3 vs. 19.9 pg/mL; p = 0.02). The median level for AMH was 2.2 ± 1.88 ng/mL with no statistical difference between the two groups (2.2 vs. 2.7 ng/mL, p = 0.41). No significant correlation between the follicular IL6 and AMH levels was observed.

CONCLUSIONS

The oocyte quality seems to be preserved in patients with endometriosis with the adequate response to ovarian stimulation. High levels of follicular IL6 are in accordance with the inflammatory phenomenon of the disease; however, this increase has no impact on ICSI outcomes.

High anti-Müllerian hormone (AMH) is associated with increased risks of ectopic pregnancy in women undergoing fresh embryo transfer cycle, a cohort study

BACKGROUND

Ectopic pregnancy is more common amongst assisted reproduction cycles and is a cause of significant maternal morbidity. Few predictive markers exist to help identify and modify risk of ectopic pregnancy in preparing for embryo transfer. The relationship between serum and AMH and ectopic pregnancy rate is unknown.

METHODS

This was a retrospective cohort study investigating women who underwent fresh embryo transfer cycles from January 2017 to December 2019 in Peking University Third Hospital. The primary outcome was ectopic pregnancy. Restricted cubic splines with four knots for AMH concentration (0-3, 3-6, 6-12, 12-max) were used to map out the non-linear relationship between the predicted ectopic pregnancy rate and the serum AMH concentration. Log binomial regression was used to test the crude risk ratio (cRR) and the adjusted risk ratio (aRR) after adjustment for confounders with 95% confidence intervals (CI) to determine the difference across various groups.

RESULTS

A total of 13,718 cycles in women undergoing fresh embryo transfer were eligible for analysis. The ectopic pregnancy rate was 1.3% per embryo transfer cycle initiated and 3.3% per pregnancy. Serum AMH concentrations were higher amongst women with ectopic pregnancy than in women with a confirmed intrauterine pregnancy or heterotopic pregnancy or who did not become pregnant (Mean levels: 4.0 ng/ml vs 3.2 ng/ml, 1.7 ng/ml, and 2.8 ng/ml). An AMH concentration of 7 ng/ml represented the best cut-off value to predict ectopic pregnancy. The ectopic pregnancy rate was 3.4% per cycle and 7.5% per pregnancy in women with AMH levels ≥ 7 ng/ml; and 1.2% per cycle and 2.9% per pregnancy in women with AMH levels < 7 ng/ml. Serum AMH concentration ≥ 7 ng/ml was associated with an increased risk of ectopic pregnancy in all fresh embryo transfer cycles started (aRR = 2.35 (1.45, 3.58)) as well in women who became pregnant (aRR = 2.23 (1.49, 3.33).

CONCLUSIONS

Baseline AMH concentration ≥ 7 ng/ml is associated with an increased risk of ectopic pregnancy in fresh embryo transfer cycles.

An online tool for predicting ovarian responses in unselected patients using dynamic inhibin B and basal antimüllerian hormone levels

BACKGROUND

Reliable predictive models for predicting excessive and poor ovarian response in controlled ovarian stimulation (COS) is currently lacking. The dynamic (Δ) inhibin B, which refers to increment of inhibin B responding to exogenous gonadotropin, has been indicated as a potential predictor of ovarian response.

OBJECTIVE

To establish mathematical models to predict ovarian response at the early phase of COS using Δinhibin B and other biomarkers.

MATERIALS AND METHODS

Prospective cohort study in a tertiary teaching hospital, including 669 cycles underwent standard gonadotropin releasing hormone (GnRH) antagonist ovarian stimulation between April 2020 and September 2020. Early Δinhibin B was defined as an increment in inhibin B from menstrual day 2 to day 6 through to the day of COS. Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression with 5-fold cross-validation was applied to construct ovarian response prediction models. The area under the receiver operating characteristic curve (AUC), prevalence, sensitivity, and specificity were used for evaluating model performance.

RESULTS

Early Δinhibin B and basal antimüllerian hormone (AMH) levels were the best measures in building models for predicting ovarian hypo- or hyper-responses, with AUCs and ranges of 0.948 (0.887-0.976) and 0.904 (0.836-0.945) in the validation set, respectively. The contribution of the early Δinhibin B was 67.7% in the poor response prediction model and 56.4% in the excessive response prediction model. The basal AMH level contributed 16.0% in the poor response prediction model and 25.0% in the excessive response prediction model. An online website-based tool (http://121.43.113.123:8001/) has been developed to make these complex algorithms available in clinical practice.

CONCLUSION

Early Δinhibin B might be a novel biomarker for predicting ovarian response in IVF cycles. Limiting the two prediction models to the high and the very-low risk groups would achieve satisfactory performances and clinical significance. These novel models might help in counseling patients on their estimated ovarian response and reduce iatrogenic poor or excessive ovarian responses.

Anti-Müllerian hormone independently affect mtDNA copy number in human granulosa cells

BACKGROUND

Recently, as a delayed childbearing trend is emerging in modern women's adulthood, diminished reproductive potential due to age-related changes is more prevalent. Reduction in the abundance of mitochondrial DNA (mtDNA) copies and circulating anti-Müllerian hormone (AMH) have been separately reported with aging, contributing to the decrease in successful reproduction. However, there are limited reports on the impact of age on mtDNA and AMH in the same individual and whether mtDNA copy numbers are influenced by age and AMH.

METHODS

In the present study, we utilized a real-time quantitative PCR (RT-qPCR) to quantify the mtDNA copy number of granulosa cells obtained from 43 women undergoing an in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) program.

RESULTS

According to our analysis, a significant correlation was observed between age and mtDNA copy number (r = -0.54, P < 0.001) and between age and AMH level (r = -0.48, P < 0.001) of the same individual. There was also a positive correlation between mtDNA copy number and AMH (r = 0.88, P < 0.001) with AMH level falling as mtDNA decreases. In our regression, age and AMH were shown to have low collinearity (VIF = 1.297) but only AMH was correlated with mtDNA quantity (P < 0.001).

CONCLUSION

Our study suggests that both mtDNA and AMH abundance are influenced by age and that AMH levels independently affect mtDNA copy number regardless of age. Further research is required to understand the role of AMH on mitochondria bioenergetics.

Anti-Müllerian hormone in guiding the selection of a freeze-all versus a fresh embryo transfer strategy: a cohort study

PURPOSE

To explore an interaction effect between serum anti-Müllerian hormone (AMH) levels and the relative treatment effect of a freeze-all versus a fresh embryo transfer strategy on live birth.

METHODS

This was a retrospective cohort study investigating couples with infertility and eligible for both freeze-all and fresh embryo transfer between 2017 and 2019. Women with an absolute indication for a freeze-all strategy were excluded. Multivariable fractional polynomial interaction analysis within a logistic regression model was used to evaluate whether the treatment effect of a freeze-all versus a fresh transfer strategy varied at different AMH levels. Non-linear interactions were also considered. The primary outcome was the live birth after the first transfer.

RESULTS

A total of 13,503 women underwent a fresh embryo transfer and 2247 women underwent a freeze-all strategy. Live birth rates were slightly higher in the freeze-all group compared to those in the fresh embryo transfer group (35% vs 33%). There was a non-linear interaction between baseline serum AMH levels and the relative treatment effect of a freeze-all strategy versus a fresh transfer strategy on live birth (P = 0.0161). The benefit on live birth from a freeze-all embryo transfer strategy was greatest in women with a high serum level (> 7 ng/ml). The interaction remained valid when different imputation methods were used.

CONCLUSION

As serum AMH level increased, there was a nonlinear increase in relative treatment effect of a freeze-only transfer versus a fresh transfer strategy on live birth, and such an effect reaches its maximum in women with high AMH levels.

Antimullerian Hormone Levels and Association with Abortion and Preterm Delivery in Patients with Polycystic Ovary Syndrome Who Conceived with Assisted Reproductive Techniques

Background

Pregnant PCOS patients were found to suffer from many adverse outcomes of pregnancy. Prediction of the fate of pregnancy and labor in PCOS patients was highly needed. There were recently discovered roles of serum AMH in those patients who were seeking for pregnancy and who were conceiving with assisted reproductive techniques.

Aim

To analyze the predictive roles of measuring serum levels of AMH in patients with PCOS who became pregnant spontaneously or used assisted reproductive techniques regarding abortion and preterm delivery.

Patients and Study Design

A total of 100 females with PCOS were included in the study and they underwent assisted reproductive techniques were included in the study and underwent measurement of AMH levels regularly.

Results

We found that a total of 70 patients had a term delivery, and 30 patients had a preterm delivery. We found no statistically significant differences between both groups regarding their age or body mass index (BMI). We showed that serum AMH levels were higher in the group of PCOS patients who had preterm delivery than in the group of patients with term delivery (p < .0.001).

Conclusions

High serum AMH levels were found to be associated with higher risks of occurrence of preterm labor in patients with PCOS who underwent assisted reproductive techniques. Our results gave a clue to clinicians for better management of the pregnancy process in these patients.

An Online Tool Using Basal or Activated Ovarian Reserve Markers to Predict the Number of Oocytes Retrieved Following Controlled Ovarian Stimulation: A Prospective Observational Cohort Study

BACKGROUND

Predicting the number of oocytes retrieved (NOR) following controlled ovarian stimulation (COS) is the only way to ensure effective and safe treatment in assisted reproductive technology (ART). To date, there have been limited studies about predicting specific NOR, which hinders the development of individualized treatment in ART.

OBJECTIVE

To establish an online tool for predicting NOR.

MATERIALS AND METHODS

In total, 621 prospective routine gonadotropin releasing hormone (GnRH) antagonist COS cycles were studied. Independent variables included age, body mass index, antral follicle counts, basal FSH, basal and increment of anti-mullerian hormone, Luteinizing hormon, estradiol, testosterone, androstenedione, and inhibin B. The outcome variable was NOR. The independent variables underwent appropriate transformation to achieve a better fit for a linear relationship with NOR. Pruned forward selection with holdback validation was then used to establish predictive models. Corrected Akaike's information criterion, Schwarz-Bayesian information criterion, scaled -log[likelihood], and the generalized coefficient of determination (R²) were used for model evaluation.

RESULTS

A multiple negative binomial regression model was used for predicting NOR because it fitted a negative binomial distribution. We established Model 1, using basal ovarian reserve markers, and Model 2, using both basal and early dynamic markers for predicting NOR following COS. The generalized R² values were 0.54 and 0.51 for Model 1 and 0.64 and 0.62 for Model 2 in the training and validation sets, respectively.

CONCLUSION

Models 1 and 2 could be applied to different scenarios. For directing the starting dose of recombinant follicle stimulation hormone (rFSH), Model 1 using basic predictors could be used prior to COS. Model 2 could be used for directing the adjustment of rFSH dosages during COS. An online tool (http://121.43.113.123:8002/) based on these two models is also developed. We anticipate that the clinical application of this tool could help the ART clinics to reduce iatrogenic ovarian under- or over-responses, and could reduce costs during COS for ART.

Moxibustion improves ovarian function based on the regulation of the androgen balance

The effect of androgens on follicular development and female reproduction has become an active research topic. Moxibustion is a Traditional Chinese Medicine therapy that has been reported to be able to prevent and treat numerous ovary-related problems. However, studies on the effect of moxibustion for diminished ovarian reserve (DOR) on androgen balance are still lacking. The present study aimed to assess the efficacy of moxibustion intervention prior to disease onset and at the early stage of disease in a rat model of DOR and explore the mechanisms of its effect on ovarian function. A total of 32 rats were randomly divided into four groups: Blank group, Model group (a drug-induced model of DOR), Moxibustion group 1 and Moxibustion group 2. Moxibustion was performed on the BL23 and RN4 acupoints of female rats daily for a total of 20 days (once a day, five times a week for a total of 4 weeks). The two moxibustion groups were established with different intervention times: One group was subjected to pre-disease intervention and the other group to early-disease intervention. The ovarian function was evaluated by detecting anti-Mullerian hormone (AMH), follicle-stimulating hormone (FSH), estradiol (E2), testosterone (T), dehydroepiandrosterone (DHEA), dihydrotestosterone (DHT) and androgen receptor (AR) levels in the serum or the ovary samples. To further investigate the downstream regulatory factors for AR after moxibustion treatment for pre-disease or early-disease intervention, FSH receptor (FSHR) and microRNA (miR)-125b expression in ovaries were also analyzed. The results indicated that AMH and DHT levels were reduced in the model group compared with those in the blank group, while FSH, T and DHEA levels were increased. AMH and DHT levels were increased in Moxibustion group 1 compared with those in the model group, while FSH, T and DHEA levels were reduced. There was no difference in E2 levels between Moxibustion group 1 and the model group. Compared with that in the model group, the AR content in the ovary was increased in Moxibustion group 1. There was no difference in FSHR mRNA in the ovaries between Moxibustion group 1 and the model group. miR-125b levels were significantly increased in Moxibustion group 1 as compared with those in the model group. Furthermore, AMH and DHT levels were increased in Moxibustion group 2 compared with those in the model group, while FSH, T and DHEA levels were reduced. E2 levels were significantly decreased in Moxibustion group 2 compared with those in the model group. The relative mRNA expression of AR, FSHR and miR-125b was decreased following establishment of the model. Compared with that in the model group, the AR content in the ovary was increased in Moxibustion group 2. In comparison with the blank and model groups, the FSHR content in the ovary of Moxibustion group 2 was significantly increased. miR-125b levels were not obviously altered in Moxibustion group 2 as compared with those in the model group. In addition, there was no significant difference in AMH, FSH, T and DHEA levels between the two moxibustion groups. E2 and DHT levels were higher in Moxibustion group 1 than in Moxibustion group 2. There was no difference in AR mRNA expression between the two moxibustion groups. FSHR mRNA levels were lower in Moxibustion group 1 than in Moxibustion group 2, while miR-125b mRNA levels were higher in Moxibustion group 1 than in Moxibustion group 2. In conclusion, the present study suggested that moxibustion intervention prior to disease onset and at the early disease stage was able to improve ovarian function via modulation of the AR-mediated stable equilibrium of androgens. However, the effects and mechanisms of moxibustion intervention for pre-disease and early-disease intervention of DOR appear to be different. The appropriate duration of treatment and the time-effect relationship require to be further studied.

Investigation on the risk factors for late-onset OHSS: a retrospective case-control study

BACKGROUND

The pathophysiology of ovarian hyperstimulation syndrome (OHSS) is largely unknown. High ovarian response is acknowledged as a risk factor. However, in our clinical practice, the incidence of OHSS is not necessarily linked to the degree of such response among women. Here, we aimed to screen for potential risk factors other than those associated with ovarian response.

METHODS

A total of 21,222 ovarian stimulation cycles were collected among women undergoing assisted reproductive technology, among which 84 patients with late-onset OHSS were identified as cases; corresponding matched control cases were obtained from the remaining 21,138 cycles. A multivariable logistic regression with the best subset method was performed to screen for significant risk factors.

RESULTS

First, control samples were obtained with a case-to-control ratio of 1:4. The matching criteria were mainly ovarian response-related factors including age, body mass index, number of oocytes retrieved, standard or mild ovarian stimulation, and specific ovarian stimulation protocols. After matching the five ovarian response-related factors, 81 cases and 318 controls were obtained. The best model was selected after analysis as above. Basal serum low-density lipoprotein cholesterol (LDL-C), basal total cholesterol (TC), and estradiol (E₂) concentrations on the day of triggering ovulation were included in the model, with odds ratios of 0.3410 (95% confidence interval, CI, 0.1618-0.7186), 2.2008 (95% CI 1.1192-4.3275) and 1.0000 (95% CI 1.0000-1.0001), respectively.

CONCLUSION

Basal LDL-C was a risk factor negatively associated with late-onset OHSS, while basal TC and triggering E₂ levels during ovarian stimulation were positive risk factors.

Machine-intelligence for developing a potent signature to predict ovarian response to tailor assisted reproduction technology

The prediction of poor ovarian response (POR) for stratified interference is a critical clinical issue that has received an increasing amount of recent concern. Anthropogenic diagnostic modes remain too simple for the handling of actual clinical complexity. Therefore, this study conducted extensive selection using models that were derived from a variety of machine learning algorithms, including random forest (RF), decision trees, eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), and artificial neural networks (ANN) for the development of two models called the COS pre-launch model (CPLM) and the hCG pre-trigger model (HPTM) to assess POR based on different requirements. The results demonstrated that CPLM constructed using ANN achieved the highest AUC result of all the algorithms in COS pre-launch (AUC=0.859, C-index=0.87, good calibration), and HPTL constructed using random forest was found to be the most effective in hCG pre-trigger (AUC=0.903, C-index=0.90, good calibration). It is notable that CPLM and HPTM exhibited better performance than common clinical characteristics (0.895 [CPLM], and 0.903 [HPTM] in comparison to 0.824 [anti-Müllerian hormone (AMH)], and 0.799 [antral follicle count (AFC)]). Furthermore, variable importance figure elucidated the values of AMH, AFC, and E₂ level and follicle number on hCG day, which provides important theoretical guidance and experimental data for further application. Generally, the CPLM and HPTM can offer effective POR prediction for patients who are receiving assisted reproduction technology (ART), and has great potential for guiding the clinical treatment of infertility.

How fixed versus variable gonadotropin dose during controlled ovarian stimulation could influence the management of infertility patients undergoing IVF treatment: a national Delphi consensus

AIM

Define how and when fixed starting gonadotropin doses can be used in current clinical ART practices in Italy.

METHODS

A Delphi conference consisting of three rounds was performed in order to define the ideal clinical conditions in which fixed-gonadotropin-dose during COS should be applied. During the conference, 19 statements about the current ART practice were provided to a panel of twenty-nine national experts. Median score was 5 (IQ:4-6) in all Delphi rounds.

RESULTS

Eleven statements (57.9%) were classified as shareable with high-degree of convergence, 2 (10.5%) as shareable with low convergence and 6 (31.6%) as un-shareable with high convergence. The panel reached high consensus regarding some statements: (i) fixed FSH-dose in normoresponders and poor-responder, (ii) importance of predicting ovarian response before COS, considering multiple markers to select the right stimulation protocol for each patient, (iii) importance of therapy simplification and standardization to improve efficiency during COS. Moreover, a low-convergence was reached about use of GnRH antagonist as first treatment line and drug storage at room temperature. However from these findings, the debate remains open regarding some other statements: (a) usefulness of Bologna-criteria to define poor-responders; (b) efficacy to change always stimulation protocol after a failure IVF; (c) utility of AMH-dosed with standardized automatic mode to define normo-responder patients; (d) usefulness to modify the dosage of 12.5 IU/die during COS to improve stimulation effectiveness.

CONCLUSION

Controlled ovarian stimulation remains a challenging clinical step in Assisted Reproductive Technique, especially in some specific patient groups for which no clinical consensus is available. This study is the first attempt to describe the shared clinical opinion regarding the fixed versus variable gonadotropin dose in the real IVF practice.

Clinical Applications of Serum Anti-Müllerian Hormone Measurements in Both Males and Females: An Update

Infertility is one of the most common non-communicable diseases, affecting both men and women equally. Ovarian reserve, the number of primordial follicles in the ovaries is believed to be the most important determinants for female fertility. Anti-Müllerian hormone (AMH) secreted from granulosa cells of growing follicles is recognized as the most important biomarker for ovarian reserve. Ovarian reserve models have been developed using AMH and other hormonal indicators, thus childbearing plans and reproductive choices could be arranged by women. In assisted reproductive technology cycles, measurement of AMH helps to predict ovarian response and guide recombinant follicle-stimulating hormone dosing in women. Serum AMH level is increasingly being recognized as a potential surrogate marker for polycystic ovarian morphology, one of the criteria for diagnosis of polycystic ovarian syndrome. AMH is also secreted by Sertoli cells of testes in men, and AMH measurements in the prediction of surgical sperm recovery rate in men have also been investigated. AMH levels are significantly higher in boys than in girls before puberty. Therefore, serum levels of AMH in combination with testosterone is used for the differential diagnosis of disorders of sex development, anorchia, non-obstructive azoospermia, and persistent Müllerian duct syndrome. Recently, serum AMH measurements have also been used in fertility preservation programs in oncofertility, screening for granulosa cell tumors, and prediction of menopause applications. In this review, we will focus on clinical application of AMH in fertility assessments for healthy men and women, as well as for cancer patients.

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Anti-Müllerian hormone (AMH) plays a key role in models assessing ovarian reserve

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AMH is used for the differential diagnosis of disorders of sex development

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AMH provides a molecular marker for related fertility and infertility disorders

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An international standard will aid in the development of various AMH assays

An Ovarian Reserve Assessment Model Based on Anti-Müllerian Hormone Levels, Follicle-Stimulating Hormone Levels, and Age: Retrospective Cohort Study

BACKGROUND

Previously, we reported a model for assessing ovarian reserves using 4 predictors: anti-Müllerian hormone (AMH) level, antral follicle count (AFC), follicle-stimulating hormone (FSH) level, and female age. This model is referred as the AAFA (anti-Müllerian hormone level-antral follicle count-follicle-stimulating hormone level-age) model.

OBJECTIVE

This study aims to explore the possibility of establishing a model for predicting ovarian reserves using only 3 factors: AMH level, FSH level, and age. The proposed model is referred to as the AFA (anti-Müllerian hormone level-follicle-stimulating hormone level-age) model.

METHODS

Oocytes from ovarian cycles stimulated by gonadotropin-releasing hormone antagonist were collected retrospectively at our reproductive center. Poor ovarian response (<5 oocytes retrieved) was defined as an outcome variable. The AFA model was built using a multivariable logistic regression analysis on data from 2017; data from 2018 were used to validate the performance of AFA model. Measurements of the area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predicative value were used to evaluate the performance of the model. To rank the ovarian reserves of the whole population, we ranked the subgroups according to the predicted probability of poor ovarian response and further divided the 60 subgroups into 4 clusters, A-D, according to cut-off values consistent with the AAFA model.

RESULTS

The AUCs of the AFA and AAFA models were similar for the same validation set, with values of 0.853 (95% CI 0.841-0.865) and 0.850 (95% CI 0.838-0.862), respectively. We further ranked the ovarian reserves according to their predicted probability of poor ovarian response, which was calculated using our AFA model. The actual incidences of poor ovarian response in groups from A-D in the AFA model were 0.037 (95% CI 0.029-0.046), 0.128 (95% CI 0.099-0.165), 0.294 (95% CI 0.250-0.341), and 0.624 (95% CI 0.577-0.669), respectively. The order of ovarian reserve from adequate to poor followed the order from A to D. The clinical pregnancy rate, live-birth rate, and specific differences in groups A-D were similar when predicted using the AFA and AAFA models.

CONCLUSIONS

This AFA model for assessing the true ovarian reserve was more convenient, cost-effective, and objective than our original AAFA model.

The comparison of evaluative effectiveness between antral follicle count/age ratio and ovarian response prediction index for the ovarian reserve and response functions in infertile women

Aim of the present study was to explore the evaluative effectiveness of age, ovarian volume (OV), antral follicle count (AFC), serum follicle-stimulating hormone (FSH), anti-Müllerian hormone (AMH), AFC/Age ratio, AMH/Age ratio, FSH/luteinizing hormone (LH) ratio, and ovarian response prediction index (ORPI) to determine which could more advantageously assess ovarian reserve and response.This research enrolled 319 consecutive infertile women who had undergone in vitro fertilization-ET/intracytoplasmic sperm injection (IVF-ET/ICSI) treatments. Abovementioned variables were measured and calculated. Receiver operating characteristic (ROC) curve analysis was used to analyze the predictive accuracy of variables and to calculate cut-off values and corresponding sensitivity and specificity.Our study revealed that the significant variables for evaluating a decline in ovarian reserve include age, OV, FSH, AFC/Age ratio, AMH/Age ratio, and ORPI. Moreover, the area under the curve (AUC) of AFC/Age ratio was higher than other 5 variables (AUC = 1.000), and the cut-off value of AFC/Age ratio was 0.111 (sensitivity 100.00%, specificity 100.00%). The significant variables forecasting excessive ovarian response were age, AFC, AMH, FSH, AFC/Age ratio, AMH/Age ratio, FSH/LH ratio, and ORPI, and the significant variables forecasting poor ovarian response were AMH, LH, OV, AFC/Age ratio, AMH/Age ratio, and FSH/LH ratio. When ORPI was used to predict excessive response, the cut-off value of ORPI was 0.880 (sensitivity 84.72%, specificity 67.32%) and ORPI presented better effectiveness. When used to predict poor response, the evaluative effectiveness of 6 variables was almost similar, although the AUC of AFC/Age ratio presented the largest value.Regarding the infertile women, AFC/Age ratio performed better than did the other variables in evaluating ovarian reserve, and it offered excellent effectiveness in predicting poor ovarian response, however, ORPI presented better effectiveness in predicting excessive ovarian response.

A novel mathematical model of true ovarian reserve assessment based on predicted probability of poor ovarian response: a retrospective cohort study

PURPOSE

To establish a mathematical model for assessing the true ovarian reserve based on the predicted probability of poor ovarian response (POR).

METHODS

In this retrospective cohort study, a total of 1523 GnRH-antagonist cycles in 2017 were firstly analyzed. The ovarian responses were calculated based on the number of retrieved oocytes. The continuous variables were converted into categorical variables according to cutoff values generated by the decision tree method. The optimal model was identified using forward stepwise multiple logistic regression with 5-fold cross-validation and further verified its performances using outer validation data.

RESULTS

The predictors in our model were anti-Müllerian hormone (AMH), antral follicle counts (AFC), basal follicle-stimulating hormone (FSH), and age, in order of their significance, named AAFA model. The AUC, sensitivity, specificity, positive predictive value, and negative predictive value of AAFA model in inner validation and outer validation data were 0.861 and 0.850, 0.603 and 0.519, 0.917 and 0.930, 0.655 and 0.570, and 0.899 and 0.915. Ovarian reserve of 16 subgroups was further ranked according to the predicted probability of POR and further divided into 4 groups of A-D using clustering analysis. The incidence of POR in the four groups was 0.038 (0.030-0.046), 0.139 (0.101-0.177), 0.362 (0.308-0.415), and 0.571 (0.525-0.616), respectively. The order of ovarian reserve from adequate to poor followed the order of A to D.

CONCLUSION

We have established an easy applicable AAFA model for assessing true ovarian reserve and may have important implications in both infertile women and general reproductive women in Chinese or Asian population.

Association of serum anti-Müllerian hormone and other factors with cumulative live birth rate following IVF

RESEARCH QUESTION

What are the optimal values of maternal age and body mass index (BMI), paternal age and BMI, number of oocytes retrieved, and serum AMH concentrations for cumulative live birth rate (CLBR) in IVF and embryo transfer (IVF-ET)?

DESIGN

This retrospective cohort study included 9494 women who underwent their first IVF-ET cycle between January 2017 and July 2018. The primary outcome was the CLBR within one complete cycle. Cox regression analysis was used to test the hazard ratio, with 95% confidence intervals.

RESULTS

CLBR was significantly lower when maternal age was over 35 (adjusted P < 0.01 for age 36-38 years, adjusted P < 0.00001 for all age groups above 38 years). CBLR increased with increasing serum AMH concentrations and number of retrieved oocytes up to peak values at 5-7 ng/ml AMH and 16-20 oocytes in all women. CLBR was significantly increased when serum AMH concentrations were 3-7 ng/ml (adjusted P < 0.001) and number of oocytes retrieved was more than five (adjusted P < 0.00001). Overweight had a negative effect on CLBR compared with normal BMI in women under 35 years of age (adjusted P = 0.037). In women aged over 35 years, paternal overweight had a negative effect on CLBR compared with normal paternal BMI (adjusted P < 0.01).

CONCLUSIONS

Maternal age had an impact on optimal serum AMH concentrations and number of oocytes retrieved. Maternal overweight negatively affected CLBR in women under 35 years of age, and paternal overweight negatively affected CLBR in women over 35 years.

Anti-müllerian Hormone for the Prediction of Ovarian Response in Progestin-Primed Ovarian Stimulation Protocol for IVF

Background: The ability of anti-Müllerian hormone (AMH) to predict ovarian response has been studied extensively in gonadotropin-releasing hormone agonist and antagonist treatments, but no information is available regarding its value in progestin-primed ovarian stimulation (PPOS) protocol. Methods: This retrospective data analysis included 523 patients without polycystic ovary syndrome who underwent their first in vitro fertilization/intracytoplasmic sperm injection cycle with PPOS protocol at our center between Jan. 2015 and Jul. 2018. Serum AMH measurements were acquired within 12 months prior to ovarian stimulation using the automated Access AMH assay. Results: AMH exhibited a significantly positive correlation with the number of retrieved oocytes (r = 0.744, P < 0.001). For the prediction of poor (<4 oocytes) and high (>15 oocytes) response, AMH had an area under the receiver operating characteristic curve (AUC) of 0.861 and 0.773, corresponding with an optimal cutoff point of 1.26 and 4.34 ng/mL, respectively. When stratified according to the dose of medroxyprogesterone acetate (MPA) (4 mg vs. 10 mg per day), AMH retained its similarly high predictive value for poor (AUC = 0.829 and 0.886, respectively) and high response (AUC = 0.770 and 0.814, respectively) in both groups. Amongst the 314 women who received their first frozen embryo transfer (FET) following PPOS protocol, no significant differences were observed on the rates of biochemical pregnancy, clinical pregnancy, implantation, early miscarriage, multiple pregnancy and ectopic pregnancy (all P > 0.05) across AMH quartiles (≤1.43, 1.44-2.55, 2.56-4.35, >4.35 ng/mL). In a multivariable logistic regression model, age was suggested to be the only independent risk factor for clinical pregnancy (P = 0.011). Conclusions: Our data demonstrated that AMH is an adequate predictor of both high and poor ovarian response in PPOS protocol regardless of MPA dose, but it does not associate with pregnancy outcomes in the first FET cycles in a freeze-all strategy.

Prospective observational cohort study: Computational models for early prediction of ongoing pregnancy in fresh IVF/ICSI-ET protocols

PURPOSE

This study sought to identify the significant factors related to ongoing pregnancy (OP) and to discover the most reliable model to distinguish OP from non-OP in early gestational age.

METHODS

A total of 1650 cycles were enrolled in this study. Univariate Logistic Regression was used to identify the predictors included in multivariable analysis. The dataset was then randomly split into training set and test set with proportion of 70% and 30%. Forward stepwise multivariable logistic regression with 5-fold cross validation was used to build the final mathematic model. The performance of the model was determined by the arguments of test set. The area under receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and misclassification rate (MR) were then calculated for model evaluation.

RESULTS

Seven predictors were related to OP by univariate analysis. The serum hCG level on 14th day post-embryo-transfer (hCG₁₄) and 21th day post-embryo-transfer (hCG₂₁) were linear correlated. Therefore, different multivariate regression models were built using hCG₁₄ or hCG₂₁, respectively. After multivariate regression with 5-fold validation, the final indicators in model-1 were age_group, hCG₂₁ and hCG₂₁/hCG₁₄, while age_group, hCG₁₄, and calculated 48-hour-rising-ratio of hCG were the significant predictors in model-2. Model-2 showed better sensitivity and NPV, lower MR, and similar specificity and PPV.

CONCLUSION

This study provided an effective mathematic model for early prediction of OP. The model could be of better clinical significance, especially for clinical counseling to manage patients' stress and anxiety, and for early warning of threatened miscarriage.

Genetic Architecture and Candidate Genes Identified for Follicle Number in Chicken

Follicular development has a major impact on reproductive performance. Most previous researchers focused on molecular mechanisms of follicular development. The genetic architecture underlying the number of follicle, however, has yet not to be thoroughly defined in chicken. Here we report a genome-wide association study for the genetic architecture determining the numbers of follicles in a large F₂ resource population. The results showed heritability were low to moderate (0.05-0.28) for number of pre-ovulatory follicles (POF), small yellow follicles (SYF) and atresia follicles (AF). The highly significant SNPs associated with SYF were mainly located on GGA17 and GGA28. Only four significant SNPs were identified for POF on GGA1. The variance partitioned across chromosomes and chromosome lengths had a linear relationship for SYF (R² = 0.58). The enriched genes created by the closest correspondent significant SNPs were found to be involved in biological pathways related to cell proliferation, cell cycle and cell survival. Two promising candidate genes, AMH and RGS3, were suggested to be prognostic biomarkers for SYF. In conclusion, this study offers the first evidence of genetic variance and positional candidate genes which influence the number of SYF in chicken. These identified informative SNPs may facilitate selection for an improved reproductive performance of laying hens.