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

2020 ◽  
Author(s):  
Huiyu Xu ◽  
Li Shi ◽  
Guoshuang Feng ◽  
Zhen Xiao ◽  
Lixue Chen ◽  
...  
Keyword(s):  
Ovarian Reserve ◽  
Hormone Level ◽  
Follicle Stimulating Hormone ◽  
Ovarian Response ◽  
Antral Follicle ◽  
Antral Follicle Count ◽  
Poor Ovarian Response ◽  
Predicted Probability ◽  
Age Model ◽  
Stimulating Hormone

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.

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

10.2196/19096 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e19096 ◽  
Author(s):  
Huiyu Xu ◽  
Li Shi ◽  
Guoshuang Feng ◽  
Zhen Xiao ◽  
Lixue Chen ◽  
...  
Keyword(s):  
Ovarian Reserve ◽  
Hormone Level ◽  
Follicle Stimulating Hormone ◽  
Ovarian Response ◽  
Antral Follicle ◽  
Antral Follicle Count ◽  
Poor Ovarian Response ◽  
Predicted Probability ◽  
Age Model ◽  
Stimulating Hormone

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.

Antral Follicle Diameter Variance Within Each Ovary May Be A Predictor For Poor Response In Cases With Normal Ovarian Reserve

2018 ◽  
Vol 126 (08) ◽  
pp. 521-527
Author(s):  
Ilhan Sanverdi ◽  
Enis Ozkaya ◽  
Suna Kucur ◽  
Dilsat Bilen ◽  
Meryem Eken ◽  
...  
Keyword(s):  
Ovarian Reserve ◽  
Poor Response ◽  
Ovarian Response ◽  
Antral Follicle ◽  
Multivariate Regression Analysis ◽  
Antral Follicle Count ◽  
Estradiol Level ◽  
Poor Ovarian Response ◽  
Follicle Diameter ◽  
The Right

Abstract Objectives To determine the predictive value of antral follicle diameter variance within each ovary for ovarian response in cases with normal ovarian reserve tests. Methods This is a prospective observational study. One hundred and thirty nine infertile women who underwent ART in IVF-ICSI unit of Zeynep Kamil women and children’s Health Training and research hospital between January 2017 to June 2017 were recruited. Blood samples were collected on day 2/day 3 for assessment of serum FSH and estradiol. Trans-vaginal sonography was done for antral follicle count. During antral follicle count, in order to determine antral follicle diameter variance, diameters of the largest and smallest follicles were recorded. Variance was calculated by subtracting the smallest diameter from the largest one. Following ovarian stimulation with antagonist protocol, poor response was determined in cases with total oocyte number≤3. Ovarian reserve tests and antral follicle diameter variance were utilized to predict cases with poor response in women with normal ovarian reserve. Results Antral follicle diameter variance both in right (AUC=0.737, P<0.001) and left (AUC=0.651, P<0.05) ovaries significantly predicted poor ovarian response. Variance>3.5 mm was found to have 75% sensitivity to predict poor response. Basal serum FSH with estradiol levels and AFC failed to predict poor response (P>0.05). Other significant predictors for poor response were day 5 estradiol level and estradiol level at trigger day (P<0.05). In multivariate regression analysis, both AFC and antral follicle diameter variance in the right ovary were found to be significantly associated with clinical pregnancy, on the other hand peak estradiol concentration and antral follicle diameter variance in the right ovary were significantly associated with poor response. Conclusion Antral follicle diameter variance may be utilized to predict poor ovarian response in cases with normal ovarian reserve.

scholarly journals Assessment of Serum Anti-mullerian Hormone Level, Antral Follicle Count and Age as Indicators of Ovarian Reserve Response in Women Diagnosed with Infertility in Abia State, South Eastern Nigeria

2020 ◽  
pp. 1-11
Author(s):  
Ebirien-Agana S. Bartimaeus ◽  
Chukwuma E. J. Obi ◽  
Felix O. Igwe ◽  
Edna O. Nwachuku
Keyword(s):  
Ovarian Reserve ◽  
Hormone Level ◽  
Ovarian Response ◽  
Antral Follicle ◽  
Antral Follicle Count ◽  
Group 3 ◽  
Group 2 ◽  
And Control ◽  
Experimental Group ◽  
Group 1

Aim: This study aimed at assessing serum anti-mullerian hormone level, antral follicle count and age as indicators of ovarian reserve response in women diagnosed with infertilility. Methodology: Subjects comprised of 200 females: 150 subjects and 50 controls, aged < 20  and up to 49 years, stratified into age < 20 years (control), age 20-29 years  (group 1), age 30-39 years (group 2) and age 40-49 years (group 3). About 5 ml of blood sample for AMH determination was collected on day 2-3 of spontaneous menstrual cycle from all groups and control and serum anti-mullerian hormone analyzed using enzyme linked immunosorbent assay. Baseline transvaginal ultrasound scanning was carried out on the subjects in experimental groups and control on day 2-3 of un-stimulated menstrual cycle for the measurement of antral follicle count, using the 2-dimensional plane. Results: The means±SEM of serum anti-mullerian hormone by experimental groups was 1602.44 ± 54.42 pg/ml for control, 848.06±23.04 pg/ml for group 1, 26.74±1.28 pg/ml for group 2, while group 3 is 10.37±1.26 pg/ml. The means were significantly different (P<0.0001). The mean±SEM of AFC by experimental groups was control; 7.82±0.14, group 1; 5.46±0.18, 1.78±0.10 for group 2, and 0.70±0.08 for group 3. The means of antral follicle count by experimental groups showed significant difference (p<0.0001). Results showed that anti-mullerian hormone level and antral follicle count decreased significantly (p<0.05) as the age of the subjects increases. Subjects in the control and experimental group 1 showed 100% high anti-mullerian hormone level indicating 100% potential of good ovarian response. The antral follicle count result also indicate that 100% and 75% of the control group and experimental group 1 respectively show good ovarian reserve. The ovarian response and reserve in the subjects decreased substantially as the age of the subjects increased. Positive correlations were also observed between the AMH and AFC across the ages of the population studied. Conclusion: The study reveals that good ovarian response and reserve in the population is related to the age of the subjects.

scholarly journals Antral Follicles Count and Anti-Müllerian Hormone Levels after Gonadotoxic Chemotherapy in Patients with Breast Cancer: Cohort Study

2017 ◽  
Vol 39 (04) ◽  
pp. 162-168 ◽  
Author(s):  
Ângela D'Avila ◽  
Edison Capp ◽  
Helena Corleta
Keyword(s):  
Breast Cancer ◽  
Cohort Study ◽  
Ovarian Reserve ◽  
Follicle Stimulating Hormone ◽  
Antral Follicle ◽  
Antral Follicle Count ◽  
Antral Follicles ◽  
Breast Cancer Cohort ◽  
Estradiol Levels ◽  
Stimulating Hormone

Aim To assess ovarian reserve (OVR) by means of follicle-stimulating hormone (FSH), anti-Müllerian hormone (AMH), and antral follicle count (AFC) measurement in eumenorrheic women with breast cancer, exposed to gonadotoxic chemotherapy. Method Fifty-two women (35.3 ± 3.8 years old) with breast cancer and undergoing cyclophosphamide-containing chemotherapy were enrolled. The assessment was performed before chemotherapy (T1) and after 2 (T2) and 6 months (T3). Results Six months after chemotherapy, the prevalence of regular cycles was 60%. Anti-Müllerian hormone decreased down to undetectable levels at T2 and T3 (T1: 2.53 [1.00–5.31]; T2 < 0.08; T3: < 0.08 [< 0.08–1.07] ng/mL), (p < 0.0001). Antral follicle count was 11 [8.0–13.5] follicles at T1 and lower at T2 (5.50 [3.75–8.0] and T3 (5.0 [2.5–7.0]) (p < 0.0001). In patients who remained with regular cycles during chemotherapy or resumed normal menses, FSH and estradiol levels remained unchanged. Conclusion Anti-Müllerian hormone and AFC are useful as markers of OVR decline in women exposed to chemotherapy. Follicle-stimulating hormone is only adequate in women who become amenorrheic.

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