O-255 Ovarian Response Prediction Index (ORPI) as a predictor tool for ovarian response and clinical pregnancy in IVF/ICSI cycle : A Prospective Cohort Study
Authors: Arora S , Nayar K  D , Singh S , Sethi A , Sachdeva M , Kant G , Nayar K , Mishra S 
Published: July 2024

Study question

Can incorporation of the Ovarian Response Prediction Index (ORPI), integrating AMH, AFC and age, offer a reliable prognostication of ovarian stimulation response in ART cycles?

Summary answer

The study affirms that ORPI, a three-variable index, emerges as a robust predictor for both ovarian response and clinical pregnancy rates within IVF/ICSI cycles.

What is known already

In the realm of individualized Controlled Ovarian Stimulation, precision in forecasting ovarian response proves pivotal. Ovarian reserve, influenced by age, AMH, and AFC, exhibits considerable heterogeneity among women of analogous age. While AMH and AFC function as pivotal markers, a holistic approach, exemplified by ORPI, stands out as a more comprehensive tool for predicting ovarian response.

Study design, size, duration

This prospective cohort study enrolled 302 subjects undergoing IVF cycles at a tertiary infertility center spanning from 1st January 2022 to 31st December 2023. Rigorous inclusion criteria mandated age ≤38 years, a BMI between 20–25 kg/m2, regular menstrual cycles, intact bilateral ovaries, no history of ovarian surgeries, absence of severe endometriosis, and no evidence of endocrine disorders.

Participants/materials, setting, methods

Subjects adhering to the inclusion criteria underwent venous blood sampling for AMH measurement and transvaginal ultrasound for AFC assessment. The ORPI was meticulously computed as (AMH × AFC) / patient age. Key endpoints encompassed the total oocytes retrieved, mature MII oocytes, and occurrences of clinical pregnancy. Rigorous statistical methodologies were employed for robust analysis.

Main results and the role of chance

The mean values for age (years), AMH (ng/mL), ORPI, AFC, and fertilized oocytes were 31.75 ± 4, 3.75 ± 3.39, 1.06 ± 1.22, 7.1 ± 2.94, and 6.11 ± 3.26, respectively. A highly significant positive correlation (p-value &lt; 0.0001) was observed between ORPI and the numbers of oocytes and MII oocytes, with correlation coefficients of 0.714 and 0.746, respectively.

Interpretation of the area under the ROC curve revealed that ORPI was a significant predictor of obtaining ≥4 oocytes at a cutoff point of &gt; 0.2, with an area under the curve of 0.907. Similarly, for MII oocytes ≥4, ORPI was a significant predictor at a cutoff point of &gt; 0.2, with an area under the curve of 0.937. In the case of positive clinical pregnancy, ORPI emerged as a significant predictor at a cutoff point of &gt; 0.75, with an area under the curve of 0.822. The study underscored a substantial positive correlation between ORPI and both oocyte and MII oocyte counts, affirming ORPI’s pivotal role as a predictor for clinical pregnancy.

Limitations, reasons for caution

Limitations due to the constraint of sample size temper the generalizability of findings. The study did not account for live birth rates, and a comparative analysis with alternative markers was omitted. A more expansive, meticulously designed study is imperative.

Wider implications of the findings

ORPI, an innovative ovarian response biomarker, showcases considerable potential for predicting both ovarian response and clinical pregnancy rates. Its integration into individualized Controlled Ovarian Stimulation regimens holds promise for augmenting the counselling and prognostication process for patients embarking on IVF/ICSI cycles.

Trial registration number

MCDH/2023/28