J Infertil Reprod Biol, 2020, Volume 8, Issue 3, Pages: 33-37. https://doi.org/10.47277/JIRB/8(3)/33  
Prediction of Ovarian Response with Ovarian  
Response Prediction Index (Orpi) during  
Controlled Ovarian Stimulation in IVF  
1
2
3
4
Mannem Haritha. M , Agarwal Sonal. A , Nayak Chaitra , Pragnesh Gautham , Kamini A  
Rao.5  
1
MBBS, MS (OBG), FMAS, FRM (REP MED) Infertility Specialist, Department of reproductive medicine, Milann Fertility Centre, Bangalore Assisted  
Conception Centre, Bengaluru, India  
MBBS,MS (OBG),FMAS,MNAMS,DNB,FNB(RM) Infertility Specialist, Department of reproductive Medicine, Milann Fertility Centre, Bangalore  
2
Assisted Conception Centre, Bengaluru, India  
MBBS, MS (OBG), FNB (RM) Infertility Specialist, Department of Reproductive Medicine, Milann Fertility Centre, Bangalore Assisted Conception  
3
Centre, Bengaluru, India  
4
MBBS, MD, DNB, Chief Operating Officer, Department of Reproductive Medicine, Milann Fertility Centre, Bangalore Assisted conception Centre,  
Bengaluru, India  
5
DGO, Dch, FICOG, FRCOG, PGDMLE, FNAMS, Medical Director, Department of Reproductive Medicine, Milann Fertility Centre, Bangalore  
Assisted Conception Centre, Bengaluru, India  
Received: 13/06/2020  
Accepted: 03/07/2020  
Published: 20/09/2020  
Abstract  
(
Background): To evaluate ORPI as an index to predict the response to ovarian stimulation. (Methods): It is an observational  
prospective study of 734 patients who underwent controlled ovarian stimulation during period of 1.5 years (July 2017 to December  
018) .Inclusion and exclusion criteria were taken into consideration when patients were recruited. ORPI is calculated by  
2
multiplying AMH level (ng/ml) and AFC (n) and the result is divided by age (years) of the patient. The primary outcome measured  
was number of MII oocytes and secondary outcome was total number of oocytes retrieved. (Results): Positive correlation of ORPI  
with MII oocytes and total number of oocytes is seen. Regarding the probability of collecting ≥4 oocytes under the ROC curve, the  
AUC for ORPI is 0.68 (95%CI 0.65-0.72) with sensitivity of 78.4 and specificity of 51.4 for a cut off of >0.44. For collecting ≥ 15  
oocytes ROC curve had an AUC of 0.72 with sensitivity of 66.7 and specificity of 73.4 for a cut off of >1.28. ROC curve for the  
probability of collecting ≥4 MII oocytes depicted an AUC of 0.67 with cut off of >0.77. (Conclusion): The results of our study  
concluded that in a patient undergoing IVF treatment, ORPI has a poor ability to predict retrieval of ≥4 oocytes or ≥ 4 MII and fair  
ability for hyper response with ≥15 oocytes. ORPI can serve as a counselling tool for predicting ovarian response.  
Keywords: Antral follicle count, Anti-Mullerianhormone, Controlled ovarian stimulation  
Introduction1  
serve as predictor of ovarian response so biological age as  
1
predicted by hormonal and functional profiles should be taken  
into consideration (4). Antral follicle count which is measure  
of follicles of 2-9 mm in both ovaries on day 2/3 of menstrual  
cycle seen on trans-vaginal ultrasound is also being used as a  
predictor of ovarian response (5). Limitation to it is that there  
is subjective variation with cycle to cycle variability. AMH, a  
member of the transforming growth factor-beta superfamily,  
is secreted by granulosa cells of pre antral and small antral  
follicles (6). Anti-mullerian hormone is a direct indicator of  
ovarian reserve and is independent of follicle stimulating  
hormone (FSH). AMH has no cycle variability and decreases  
throughout reproductive life to become undetectable in post-  
menopausal period. Thus in a nutshell all markers have errors  
in their estimation. Systematic reviews of ovarian reserve tests  
have depicted modest accuracy of all ovarian reserve tests for  
prediction of both hyper ovarian response and poor ovarian  
response when calculated individually (7).  
Different protocols are present for multi follicular  
development in IVF so as to increase the number of embryos  
available and decrease time to pregnancy. Hypo response or  
hyper response cannot be predicted always. Supra  
physiological oestrogen levels result from large number of  
follicles which in turn has a negative effect on embryo quality  
and endometrium (1). Clinicians should individualise the  
gonadotropin dosage to reduce adverse effects of excessive  
ovarian response or poor response. Various predictors exist to  
predict ovarian response such as age, anti-mullerian hormone  
(AMH), antral follicle count (AFC), ovarian volume, day 2  
follicle stimulating hormone, estradiol, inhibin and dynamic  
tests. Out of these age, AMH and AFC have served in the  
most effective way (2).  
Oocyte number and quality decreases with age with  
dissimilarities in different races resulting in different  
responses to ovarian stimulation (3).Chronological age cannot  
Considering advantages like ability to calculate starting  
dose of gonadotropins, decreasing iatrogenic complications  
and cancellation rate and improving cost benefit ratio of  
ovarian stimulation protocols, our study has used a new  
ovarian response prediction index (ORPI) to assess the  
response to ovarian stimulation (8).  
*
(
Corresponding author: Haritha Mannem, 1MBBS, MS  
OBG), FMAS, FRM (REP MED) Infertility Specialist,  
Department of reproductive medicine, Milann Fertility Centre,  
Bangalore Assisted Conception Centre, Bengaluru, India. E-  
mail: : harithamannem88@gmail.com  
3
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J Infertil Reprod Biol, 2020, Volume 8, Issue 3, Pages: 33-37. https://doi.org/10.47277/JIRB/8(3)/33  
ORPI ((ovarian response prediction index) is based on  
Transvaginal oocyte retrieval was performed 34-36 hours post  
trigger under intravenous sedation. Number of oocytes  
retrieved and number of mature oocytes were noted.  
three ovarian reserve markers i.e. AMH, AFC and age to  
serve as a predictor for ovarian response during controlled  
ovarian stimulation in IVF. ORPI [AMH (ng/ml) x AFC (2-9  
mm)/ patient age] is being entitled to predict optimal ovarian  
response of ≥4 oocytes and hyper response i.e. ≥15 oocytes  
efficiently (9). ORPI has a cost benefit ratio in favour of  
benefit as it guides in individualising treatment and serves as a  
counselling tool for the couple regarding their predicted  
ovarian response.  
2.5 Endpoints  
The primary outcome measured was number of MII  
oocytes and secondary outcome was total number of oocytes  
retrieved. ORPI was calculated for retrieval of ≥4 oocytes  
(adequate response), ≥ 15 oocytes (hyper response) and  
number of MII oocytes.  
2
(
.6 Calculation of Ovarian Response Prediction Index  
ORPI)  
The ORPI value was calculated by multiplying the AMH  
ng/ml) level by the AFC, and the result was divided by the  
2
Materials and Methods  
2
.1 Population  
In the current study inclusion criteria were: age 35 years,  
(
body mass index (BMI) between 2030 kg/m2, regular  
menstrual cycles and both ovaries present. Exclusion criteria  
were: History of ovarian surgery, severe endometriosis,  
endocrine disorders, and presence of ovarian cysts assessed by  
trans-vaginal ultrasound.  
Total 734 patients undergoing autologous IVF cycles were  
recruited for the study in the duration of 18 months. The study  
was reviewed by local ethical committee and clearance  
obtained from Institutional Review Board. Written informed  
consent was taken from all recruited patients. ORPI was  
calculated by multiplying AMH level (ng/ml) and AFC (n)  
and dividing it by age (years) of the patient.  
age (years) of the patient: ORPI = (AMH×AFC)/patient age.  
This definition of ORPI was based on Oliveira et al. (2012)  
study. The cut-off value was calculated by statistical analysis.  
This equation is based on previous evaluations that found that  
ovarian response to stimulation had positive correlations with  
AMH levels and number of antral follicles and was negatively  
correlated with patient’s age (10). Notably, the calculated  
value of the ORPI in the study was not influenced by the  
protocol choice for the induction of ovulation or the doses of  
gonadotropin (11).  
2
.7 Statistical analysis  
Analysis was done using SPSS software .MannWhitney  
2
.2 AMH measurement  
test and chi-square test were used where appropriate.  
Correlations were performed using Pearson’s correlation test.  
P < 0.05 was considered statistically significant. Univariate  
logistic regression module was used to estimate the value in  
predicting the likelihood of collecting ≥4 oocytes, ≥ 4 MII  
oocytes and ≥ 15 oocytes. The odds ratio (OR) and 95%  
confidence interval (CI) constituted the descriptive analysis.  
Receiver operating characteristic (ROC) curves were  
constructed to examine the performance of the ORPI in  
predicting retrieval of ≥4 oocytes, ≥4 MII oocytes and ≥15  
oocytes. The discriminative performance of the model was  
assessed by the area under the curve (AUC) of the ROC  
curve.  
Venous blood was collected irrespective of day of  
menstrual cycle and AMH was measured using an  
enzymatically amplified 2-site immunoassay kit (AMH Gen II  
ELISA, Beckman Coulter Inc.). The lowest detection limit of  
this assay is 0.01ng/ml, whereas the maximum intra- and  
inter-assay coefficients of variation are 3.3% and 6.5%,  
respectively.  
2
.3 antral follicle count  
Transvaginal ultrasound (5.5-7 MHz) was done on day 2/3  
of menstrual cycle by clinician who was blinded to the AMH  
value and other hormonal parameters. Follicles of 2-9 mm  
size were measured in both ovaries and total count was  
labelled as antral follicle count.  
3
Results  
2
.4. Controlled ovarian stimulation  
Prior to starting ovarian stimulation, baseline scan by  
The general characteristics of the study population are  
summarised in Table 1.Of all 734 women , mean age was  
30.9±4.1 years , mean BMI 24.06±2.8, mean AMH level  
2.6±2.0 ng/mL and mean AFC was 11.5±5.6 . Mean ORPI  
calculated was 1.2±1.3. The Pearson correlation analysis  
demonstrated significant (P<0.05) positive correlations  
between the ORPI and the total number of oocytes collected  
and total number of MII oocytes collected. Additionally, other  
variables of ovarian response i.e. age, AMH and AFC showed  
statistically significant correlation with the variables analysed.  
However, age and BMI are negatively correlated as depicted  
in table 2. The performance of the ORPI as a prognostic test  
was observed using ROC curves. Regarding the probability of  
collecting 4 oocytes, the ROC curve showed an area under  
the curve of 0.68 (95% CI: 0.65-0.71), indicating that the  
ORPI had a poor prognostic potency for this point. Setting the  
threshold of 0.44, it offered a specificity (51.4%) and  
sensitivity (78.4%) as illustrated in Figure 1.  
trans-vaginal ultrasound (Voluson P6) using vaginal probe  
was performed and follicle stimulating hormone (FSH),  
luteinizing hormone (LH), estradiol (E2), progesterone (P4),  
anti-mullerian hormone (AMH) were done on day  
2
2
hormone (R-FSH), (Recagon, Organon; Gonal F, Merck) with  
or without human menopausal gonadotropin (hMG; Menopur;  
Ferring Pharmaceuticals, Parsippany, NJ). Starting dose was  
calculated based on age, BMI, AFC, AMH and baseline FSH  
level. Ovarian response to stimulation was monitored during  
IVF cycle with trans-vaginal ultrasound and serum E2, LH  
and P4 measurements. Dose of gonadotropins was adjusted  
accordingly. Antagonist (Cetrotide, Merck) 0.25 mg  
subcutaneously by flexible antagonist protocol was added  
when leading follicle was ≥13-14 mm in diameter or serum  
E2 > 350-400 pg/mL and was continued until trigger day.  
Patient was given hCG trigger injection when criteria of  
atleast 3 follicles ≥17 mm as mean diameter was attained.  
.Controlled ovarian stimulation (COS) was started on day  
/3 of cycle with either recombinant Follicle stimulating  
In regards to the probability of collecting 15 oocytes,  
ROC curve had an area under the curve of 0.72 (95% CI:  
0
.68-0.75), indicating that the ORPI had a fair prognostic  
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J Infertil Reprod Biol, 2020, Volume 8, Issue 3, Pages: 33-37. https://doi.org/10.47277/JIRB/8(3)/33  
potency. Setting the threshold at 1.28 led to specificity  
73.3%) and sensitivity (66.6%) as shown in Figure 2.  
Similarly, figure demonstrates ROC curve for the  
probability of collecting 4 mature oocytes which gave an  
area under the curve of 0.67 (95% CI: 0.64-0.70), indicating  
that the ORPI values in this situation had a poor prognostic  
potency. Setting the threshold at 0.77 depicted specificity of  
Indeed, the results showed significant correlations (P<0.001)  
between the ORPI values and number of oocytes and number  
of MII oocytes. Our study has shown that ORPI and AFC both  
have similar predictive value for prediction of ovarian  
response. Oehninger et al in 2015 concluded similar findings.  
Contrary to these findings, Nelson et al. (2015) found a better  
predictive value of AMH versus AFC for oocyte yield. It  
should be noted that in the Nelson study, 19 assisted  
reproductive technology centres participated. Because AFC  
has been shown to have important inter-observer variations,  
this discrepancy could be explained by the fact that our study  
was performed in a single centre with only a few operators  
(16). Despite this test not being universally available and  
recent alterations in the methods, determination of AMH can  
be performed irrespective of day of menstrual cycle with no  
consistent fluctuation patterns (17).  
(
3
6
9% and sensitivity of 59%. When the ROC curves for all  
other factors (Age, AMH and AFC) are analysed for their  
predicting ability for retrieval of ≥4oocytes , ≥ 15 oocytes  
and ≥ 4 mature oocytes the AUC presented by the ORPI was  
always higher than age and AMH and similar to the AUC  
presented by AFC as depicted in figure 4.  
Table 1: baseline and stimulation characteristics of study  
population  
Cour Freiesleben et al. found that the best prognostic  
model to predict a low response included AFC and age. It can  
be further improved by including serum AMH levels into the  
calculation of the ORPI (18). In four previous studies, AMH  
was reported as a stronger predictor than AFC (23, 24, 25, 26,  
Mean  
Std. Deviation  
No. of Oocytes  
6.48  
3.504  
2.714  
4.117  
2.8522  
2.01711  
5.6009  
1.34358  
Matured Oocytes 4.94  
Age  
30.94  
BMI  
AMH  
AFC  
ORPI  
24.060  
2.6058  
11.551  
1.1633  
2
7, 28). However, our result was in agreement with four  
studies that found AFC was superior to AMH for  
discrimination of ovarian response (29, 30, 31, 32)  
This prospective study demonstrated that AMH, AFC and  
ORPI were good predictors for high ovarian response and  
ORPI and AFC were similar (33,34). The addition of age and  
AMH did not improve the accuracy of AFC. ROC analysis  
also revealed that AUC for AMH was lower than AFC and  
ORPI, but better than basal FSH and age. In contrast to  
Oliveira et al. study, we found that the new index (ORPI) had  
no superiority to AFC for prediction of ovarian response (35).  
On the basis of our knowledge and considering the limited  
studies in this regard, more well-designed studies are needed  
for suggesting the potential role of ORPI in the clinical  
practice for counselling and choosing individual stimulation  
protocols.  
4
Discussion  
ORPI serves as a perfect tool for having a precise estimate  
of patient’s ovarian response after controlled ovarian  
stimulation in autologous IVF cycles and optimising  
treatment. An estimate based only on age is not always  
sufficient to accurately predict the ovarian response to  
gonadotropin stimulation, considering that the ovarian  
response is highly variable even among women of same age  
group (12). This inter-individual variation is influenced by  
genetic and environmental factors that primarily determine the  
size of the pool of primordial follicles at birth and the rate of  
the pool’s decline throughout the reproductive life (13). An  
ultrasound evaluation of the antral follicle count has gained  
acceptance as a good predictor of the ovarian response with  
low intra- and inter-observer variations (14). Based on these  
observations, a joint analysis of age and the AFC might  
combine their advantages and compensate for their  
disadvantages, thus improving the assessment of ovarian  
function (15).  
5 Conclusion  
As no single ovarian reserve marker has 100% sensitivity  
and specificity, a combined index of three variables depicted  
by ovarian reserve prediction index can improve ovarian  
reserve prediction (36). ORPI serves an excellent counselling  
tool and key to knowledge enabling proper management of  
individualized treatment (37).  
The combination of different variables of ORPI have  
resulted in a more precise index to predict ovarian response.  
Table 2: Illustration of correlation between different variables  
Matured Ocytes Age  
BMI  
-0.020  
0.596  
734  
AMH  
0.284  
0.000  
734  
AFC  
0.399  
0.000  
734  
ORPI  
0.295  
0.000  
734  
Pearson Correlation  
Sig. (2-tailed)  
N
0.898  
0.000  
734  
-0.141  
No. of Oocytes  
0.000  
734  
Matured Oocytes Pearson Correlation  
-0.149  
-0.004  
0.276  
0.379  
0.285  
Sig. (2-tailed)  
N
0.000  
734  
0.913  
734  
0.000  
734  
0.000  
734  
0.000  
734  
3
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J Infertil Reprod Biol, 2020, Volume 8, Issue 3, Pages: 33-37. https://doi.org/10.47277/JIRB/8(3)/33  
with oocyte quality in stimulated cycles. Hum Reprod 2006,  
Limitations  
2
1:20222026.  
We have not taken pregnancy outcome into consideration.  
1
6. Riggs RM, Duran EH, Baker MW, Kimble TD, Hobeika E, Yin L,  
Matos-Bodden L, Leader B, Stadtmauer L: Assessment of  
ovarian reserve with anti- Mullerian hormone: a comparison of  
the predictive value of anti- Mullerian hormone, follicle-  
stimulating hormone, inhibin B, and age. Am J Obstet Gynecol  
Acknowledgment  
We thank the consulatants of reproductive medicine  
2
008, 199:202 e201208.  
Financial Support  
No financial support was required for the completion of this  
study.  
1
7. Aflatoonian A, Oskouian H, Ahmadi S, Oskouian L: Prediction of  
high ovarian response to controlled ovarian hyperstimulation:  
anti-Mullerian hormone versus small antral follicle count (26  
mm). J Assist Reprod Genet 2009, 26:319325.  
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1
2
8. La Marca A, Stabile G, Artenisio AC, Volpe A: Serum anti-  
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9.CemFicicioglu, Tayfun Kutlu, Elif Baglam:Early follicular  
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and sterility 2006.85(3):592-6.  
Conflict of Interest  
The authors declare no conflict of interest in the study  
topic.  
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