Ovarian reserve can be altered or reduced due to age, disease, pelvic operation, chemotherapy or radiotherapy, among other factors, and it is beneficial to create treatment regimes, survey treatment effects and forecast prognoses for infertile women by evaluating ovarian reserve or response. Our results indicated that the AFC, serum AMH levels, ORPI and retrieved oocyte numbers were significantly different among the four subgroups and that there were negative correlations between age and AFC, AMH, ORPI and retrieved oocyte numbers. Thus, we discovered that AFC and ORPI decreased gradually with age. Lee et al.  and Raeissi et al.  observed increased FSH levels and decreased AMH levels with increasing age in women. Bozkurt et al.  reported that AMH was inversely correlated with age; however, AFC revealed a stronger correlation with age in both the fertile and infertile populations compared with basal FSH and AMH; the decrease in ovarian reserve in infertile patients was directly related to age, not infertility.
AFC on day 2-4 of the menstrual cycle, evaluated by transvaginal ultrasound, is commonly used to determine ovarian reserve, but AFC measurement is prone to error because of different sonographers. To explore the evaluative effectiveness of various variables, we analyzed the correlation of AFC with other variables and found that AFC showed a positive correlation with total volume of bilateral ovary, AMH and ORPI; however, AFC showed a negative correlation with age and serum FSH level. However, Somigliana et al.  insisted that low serum AMH is not associated with female subfertility.
The literature has reported that BMI is not associated with the AMH levels in the general population of infertile women or in patients without polycystic ovary syndrome (PCOS); however, BMI is significantly and inversely correlated with AMH in women with PCOS . Another study found that age is negatively correlated with AMH and AFC across all races (P < 0.05) and that elevated BMI is negatively correlated with AMH in Caucasian women but not in African-American, Hispanic, or Asian women . The results from our research showed that BMI was inversely correlated with FSH and FSH/LH ratio but did not correlate with AMH or AFC. In brief, debate still exists regarding the influence of BMI on ovarian function and AMH levels.
The ROC analysis results in our study revealed that the significant variables for evaluating ovarian reserve decrease included age, total volume of bilateral ovary, FSH, and ORPI. Moreover, the AUC of ORPI was higher than those of the other three variables, and the diagnostic accuracy reached a “high” grade; the cut-off value of ORPI from ROC analysis was 0.245 (sensitivity 90.1%, specificity 73.9%). Assessments of the AMH and FSH levels in combination with female age could be helpful in predicting ovarian reserve in infertile women .
Many studies [17-21] have discussed how AFC and AMH could be used to assess ovarian reserve. However, our research did not find that these two variables acted as a single variable to significantly assess ovarian function. Serum AMH and AFC begin to decline in women between 34 and 35 years old, and AMH predicts biological age earlier than FSH or AFC do, and AFC does so earlier than FSH does . By age 32, over 50% of women with subfertility had AMH levels categorized as "low fertility" (AMH ≤ 19.5 pmol/liter), a figure that increased to 75% by age 39, with a decrease in mean AMH of 1.72 pmol/liter/year . The serum AMH cut-off value for the normal ovarian reserve was calculated as 0.37 ng/ml (sensitivity 71.43%, specificity 66.67%, positive prediction 83.33%, negative prediction 50%) . AMH should be considered a more reliable ovarian reserve assessment test compared to FSH because there was a strong positive correlation between the serum AMH level and AFC; further, the use of AMH combined with AFC may improve ovarian reserve evaluation . The present findings suggest the applicability of AMH determination as a marker for actual fertility in subfertile women with elevated basal FSH levels, as AMH was significantly associated with the timing of reproductive stages (i.e., the occurrence of menopausal transition or menopause during follow-up) . Our results showed that the cut-off value of age was 36.50 for predicting ovarian reserve decline and that the corresponding sensitivity and specificity were 88.0% and 40.8%, respectively.
We found that the significant variables forecasting excessive ovarian response included age, AFC, AMH, ORPI, FSH and FSH/LH ratio, and that the significant variables forecasting low ovarian response included AMH and FSH/LH ratio. Interestingly, ORPI and FSH/LH ratio demonstrated better effectiveness in evaluating ovarian response. When used to predict excessive response, the cut-off value of ORPI from ROC analysis was 0.886 (sensitivity 84.7%, specificity 67.3%), and the cut-off value of FSH/LH ratio was 1.753 (sensitivity 56.2%, specificity 67.6%). When used to predict low response, the cut-off value of FSH/LH ratio was 2.983 (sensitivity 75.0%, specificity 83.8%).
In recent years, many studies have focused on the value of a single parameter. For example, AMH was strongly associated with oocyte yield after ovarian stimulation and may therefore predicted ovarian response and the quality of oocytes and embryos [2, 19,22], and AMH had a higher predictive value for the responders and AFC than for FSH, E2 and chronological age, moreover, could predict the risk of ovarian hyperstimulation syndrome (OHSS) among patients [23,24]. Vembu et al.  reported ROC curve was plotted to predict the hyper response (OHSS), which showed a serum AMH cut-off value of 6.85 ng/ml with a sensitivity of 66.7% and a specificity of 68.7% for PCOS group and 4.85 ng/ml with a sensitivity of 85.7% and a specificity of 89.7% in non-PCOS group. AFC is superior to AMH in predicting poor ovarian response. The cut-off point for mean AMH and AFC in discriminating between poor and normal ovarian response cycles was 0.94 ng/ml (with a sensitivity of 70% and a specificity of 86%) and 5.5 (with a sensitivity of 91% and a specificity of 91%), respectively . Iranian women with a basal AMH level > 6.95 ng/ml are at a high risk of developing OHSS, and those with AMH level < 1.65 ng/ml are poor responders .Our results showed that the AMH cut-off value for excessive ovarian response and low response was 3.955 ng/ml (sensitivity 59.7%, specificity 79.1%) and 1.405 ng/ml (sensitivity 70.8%, specificity 77.8%), AFC cut-off value for excessive ovarian response was 14.50 (sensitivity 77.8%, specificity 77.1%), respectively.
Currently, two popular combined indexes, ORPI and FSH/LH ratio, are used to assess ovarian function. Regarding the probability of collecting greater than or equal to 4 oocytes, ORPI showed an AUC of 0.91 and an efficacy of 88% at a cut-off of 0.2, but for the probability of collecting greater than or equal to 15 oocytes, ORPI showed an AUC of 0.89 and an efficacy of 82% at a cut-off of 0.9 . The cut-off value reported by that study approximated our results. Oliveira et al.  reported the ORPI offered excellent ovarian response prediction (AUC = 0.91), and good predictions for the possibility of collecting > 4 MII oocytes (AUC = 0.84) and excessive ovarian response (AUC = 0.89) in infertile women, and ORPI value (≥1.7) was the benchmark that indicated high risk for OHSS. Selcuk et al. found that the level of association between the ovarian response tests and poor ovarian response data was (in descending order): ovarian sensitivity index (OSI), ORPI, AFC, AMH, and age (AUC = 0.976, 0.905, 0.899, 0.864, 0.617, respectively), and OSI and ORPI could be superior to other ovarian responsiveness markers for poor and high ovarian responses on cycles with agonist or antagonist protocols. However, ORPI was more convenient than OSI, because OSI could be calculated after informed of the number of retrieved oocytes. In addition, opposing views on ORPI effectiveness continue to exist. Another study showed that both AMH and AFC were good predictors of ovarian response with an AUC > 0.75 but that combining these variables was necessary as ORPI would not improve the prediction value . Using the cut-off value derived from ROC analysis, cycles with an FSH/LH ratio > or =3 produced fewer mature oocytes (8.25 vs. 11.74) and a higher percentage of poor ovarian response cycles (32.5% vs. 14.3%). Additionally, the serum FSH level and FSH/LH ratio at the commencement of gonadotropin stimulation were inversely correlated to the number of mature oocytes . According to our results and previous reports in the literature, the abovementioned combined indexes had excellent performances in evaluating ovarian reserve and response.
Some shortcomings still exist in our research. First, there were no comparison data on ovarian function between fertile and infertile women. Second, we did not focus on predicting the influence of stimulation protocols and cycle cancellations. Previous research has shown that an elevated FSH/LH ratio >3 is more likely to result in the cancellation of the individual’s cycle (15% vs 5.24%, p = 0.0001) and that the total gonadotropin dosage was greater in the higher-ratio group than in lower-ratio group (2636 vs 2242 IU; significant) . Finally, we did not collect data on embryo quality and pregnancy outcome associated with parameters in this research. Several studies have paid close attention to treatment outcomes. An FSH/LH ratio less than 1.26 is associated with good oocyte parameters, high-quality embryos and implantation after ICSI .