The Clinical Study On The Relationship Between The Predictors Of Ovarian Reserve And Treatment Outcome Of In Vitro Fertilization And Embryo Transfer

Part Ⅰ Evaluation of ovarian response using the predictors of ovarian reserve OBJECTIVEThis study is to identify the predictors of ovarian response through analysis of relationship between the predictors of ovarian reserve including patient’s age, antral follicle count (AFC), serum anti-mullerian hormone level (AMH), serum follicle-stimulating hormone levels (FSH), basic E2level with ovarian response among the patients who undergone in vitro fertilization and embryo transfer. By exploring the predictive ability of them by ROC curve and analyzing the predictive value of the combination of indicators, we can work out an individualized ovarian stimulation method for patient, improve the clinical pregnancy rate. MATERIALS AND METHODSA total of656patients who conducted in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) were selected between2010October and2013January in Reproductive Medicine Center of Nan fang Hospital of Southern Medical University in this retrospectively analyzed study. We define the ovarian response according to the number of retrieved oocytes and poor ovarian response as the number of retrieved oocytes≤3and high ovarian response as the number of retrieved oocytes≥20. The patients were divided into poor ovarian response group, normal ovarian response group and high ovarian response group and compared the predictors among the three groups. On the day2-4of menses cycle, AFC was measured using transvaginal sonography and a total of2tube with3-4ml peripheral venous blood was collected in patients, one sent Nan Fang Hospital laboratory for the measurement of FSH, LH, E2level and another was saved to refrigerator of40℃for tested AMH levels by enzyme-linked immunosorbent assay (ELISA) in the future. Record the patient’s age, body mass index (BMI), the days of Gn, the total amount of Gn, E2levels on the day of HCG administed, the number of oocytes collected and good quality embryo and so on. All data were processed by SPSS16.0software, compare the basic characteristics and the treatment of the patients among the different groups using one-way ANOVA or Welch approximate variance analysis and Chi-Square test. Then compare the diagnostic utility of the predictors by receiver operating curve (ROC) and analyze the relationship between the predictors of ovarian reserve with ovarian response by Spearman correlation and Logistic Regression.RESULTS1. Clinical characteristics and treatment results of infertility patients among different ovarian response groupsWe have a total of75cycles in poor ovarian response group and525cycles in ovarian normal response group and56cycles in ovarian high ovarian response group. Body mass index (BMI), duration of infertility, basal E2level, the type of infertility in the different ovarian response groups were not significant difference (P>0.05). There was significant difference in the patient’s age, AFC, the level of serum AMH, FSH levels among the three groups (P<0.001). Gn total dose, E2on the HCG day, the number of follicles punctured, normal fertilized oocytes, good quality embryo and the number of embryos available for transfer and the number of embryo transfered, embryo implantation rate and clinical pregnancy rate in the different ovarian response groups were also significant difference (P<0.001).Age and basal FSH levels of poor ovarian response group were significantly higher than that of normal ovarian response group, while AFC and serum AMH level were significantly lower than that of normal ovarian response; age and basal FSH level in high ovarian response group were significantly lower than those of normal ovarian response group, while AFC and serum AMH levels were significantly higher in ovarian normal response group.2. Relationship between the predictors of ovarian reserve and ovarian responseSpearman correlation analysis showed that the level of serum AMH and AFC were positively associated with the number of retrieved oocytes, patient’s age and basal FSH levels were negatively correlated with the number of retrieved oocytes, the correlation coefficients (r) were0.566,0.566,-0.265,-0.322, P<0.001; E2levels had no significant correlation with retrieved oocytes, r=0.055, P=0.163.Logistic regression analysis showed that the patient’s age, AFC and serum FSH level were included into model to predict poor ovarian response. Combining the three parameters can improve the prediction efficiency. However, to predict high ovarian response combining those parameters did not reveal any significant improvement in the prediction efficiency.3. The evaluation of predictive value of ovarian response using indicators of ovarian reserve.ROC curve analysis showed that both AFC and serum AMH were good parameters to predict the ovarian response, followed by the basal FSH levels and patient age. For the prediction of poor ovarian response, the area under the ROC curve (AUC) were0.808(0.754-0.861)、0.784(0.727-0.840)、0.709(0.637-0.782) and0.671(0.604-0.737), respectively (all P<0.001). The cut-off value of AFC and serum AMH level for poor ovarian response were AFC≤9, AMH≤12.04pmol/l. And for the prediction of high response, the area under the ROC curves were0.842(0.796-0.889)、0.849(0.802-0.895)、0.689(0.618-0.760)and0.643(0.571-0.716), respectively (all P<0.001). The cut-off value of AFC and AMH level for high ovarian response were AFC≥18, AMH≥30.19pmol/l.CONCLUSIONS1. The level of serum AMH, AFC, serum FSH level and patient’s age are relate to ovarian response, all of them can predict ovarian response.2. As a single parameter, both serum AMH and AFC were good parameter to predict the ovarian response, which is better than serum FSH and patient age. The cut off value for AFC and serum AMH to predict poor ovarian response were9and12.04pmol/1respectively. And in order to predict the high ovarian response, the cut off value of the two parameters were18and30.19pmol/l respectively.3. Combining the three parameters (AFC, serum FSH and patient age) can improve the prediction efficiency of poor ovarian response. However, to predict high ovarian response combining those parameters did not reveal any significant improvement in the prediction efficiency. Part Ⅱ Evaluation of the embryo quality and pregnancy outcome using the predictors of ovarian reserveOBJECTIVEExplore the relationship between the five ovarian reserve assessment indicators including patient’s age, basal antral follicle number (AFC), serum anti-Mullerian hormone (AMH) levels, serum follicle stimulating hormone (FSH) levels, basic E2level with the embryo quality and the pregnancy outcome, and attain the predictors of embryo quality and pregnancy outcome and compared their predictive value.MATERIALS AND METHODSA total of656patients who conducted in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) were selected between2010October and2013January in Reproductive Medicine Center of Nan fang Hospital of Southern Medical University in this retrospectively analyzed study. Analysis the relationship of AFC, serum levels of AMH, basal FSH levels with embryo quality and compared their predictive value by using spearman correlation and ROC curve. Each divided into two groups based on the cut-off value of AFC, the serum levels of AMH, basal FSH level for predict poor ovarian response, the comparison of embryo implantation rate between two groups. Rule out patients cancelled fresh transplant due to various reasons, the remaining patients were divided into pregnant group (n=242) and non-pregnant group (n=294), compared the predictors between the two groups, Using ROC curve and logistic regression to analysis the relationship of ovarian reserve assessment indicators with pregnancy outcome and their predictive value.RESULT1. Spearman correlation analysis showed that there was a positive correlation between the AFC, the serum AMH level and the number of normal fertilization,2PN embryo cleavage number, the number of good quality embryos, the number of embryos available for transfer, the serum FSH level has a negative correlation with them, P<0.001.2. The predictive value of the serum AMH level, basal FSH level and AFC produce3good embryos by using ROC curve and results show that the AFC as a single indicator for the predictive value of embryo quality was best, The area under the curve was0.702(0.662-0.742), followed by the level of serum AMH, basal FSH level, the area under the curve were0.681(0.640-0.721),0.593(0.549-0.636), P< 0.001. The cut-off of AFC for predicts embryo quality is≥13.5.3. According to the cut-off value of AFC (9), the patients were divided into two groups:group AFC≥9and group AFC<9, the embryo implantation rates were32.0%and23.2%, respectively (P=0.003). Divided into the AMH≥12.04group and AMH<12.04group according to the cut-off point12.04pmol/L of AMH for predict poor ovarian response, the embryo implantation rates were30.9%,25.8%, respectively, P value was0.057.8.26IU/L, Divided into the FSH>8.26group and FSH≤8.26group according to the cut-off point8.26of FSH for predict poor ovarian response, the embryo implantation rates were29.2%,32.9%, respectively, P value was0.168.4. The comparison of clinical characteristics in infertile patients between the pregnant group and non-pregnant group shows that the patient’s age, body mass index, serum AMH levels, AFC, basal FSH level, basic E2level, E2levels on the HCG day, number of oocytes, the number of embryos available for transfer were not statistically different (P>0.05).5. The analysis of patients’ age, AFC, basal FSH level and serum AMH level for prediction of IVF pregnancy outcomes Using ROC curve showed no indicators can make a prediction of pregnancy outcome, the area under the curve were0.468,0.507,0.497,0.497,(P>0.05).6. The analysis of the relationship between the patient’s age, serum levels of AMH, basal FSH level, AFC, basal E2level with the IVF pregnancy outcomes by Logistic regression and results showed that the patient’s age, serum levels of AMH, AFC, basal E2level and basal FSH level of IVF had no effect on pregnancy outcome, without any predictor enter Logistic regression equation.CONCLUSION1. For the prediction of the embryo quality, the predictive value of AFC is superior to serum AMH level and FSH level, but predictive value of AFC for embryo quality is very low, the level of serum AMH and basal FSH levels have no predictive value of it.2. The patient’s age, serum AMH levels, AFC, basal FSH levels and basal E2level had no effect on IVF pregnancy outcome, without any indicators can predict IVF pregnancy outcome.