Prognosticating ovarian reserve by the new ovarian response prediction index

Apoorva Tak, Madhubala Chauhan, Bharti Tak


Background: Knowledge of patient's potential ovarian response can help individualise the medication dosage and thus prevent adverse effect of excessive ovarian response and, decrease the rates of cancelled cycles, overall it will help to improve the cost benefit ratio of ovarian stimulation regimes. In addition to age, several clinical, endocrine and USG markers and dynamic tests have been proposed for the prediction of ovarian response to stimulation. Among these use of AMH levels and AFC are of particular interest However, despite the predictive power that each marker for the ovarian response may individually have, all these markers have errors associated with their estimation. So, prediction of ovarian response using a single biomarker may not be sufficient for formulation of a precise treatment plan.

Methods: This study includes 50 patients undergoing ivf cycle. All patients satisfied the following criteria; age <or equal to 39 yrs, BMI between 20-30, regular menstrual cycles, both ovaries present, no history of ovarian surgery, no severe endometriosis and no evidence of endocrine disorders. The only exclusion criteria was the presence of ovarian cysts as assessed by TVS.

Results: The results showed significant correlation between the number of obtained follicles and the number and maturity of collected oocytes. In addition, the results using the ORPI were always better than those obtained using other predictive factors (AFC, AGE and AMH) separately.

Conclusions: The present study reinforces the ORPI, which is a simple 3 variable index that exhibits an excellent ability to predict low and excessive ovarian response. ORPI might be used to improve the cost benefit ratio of ovarian stimulation regimens by guiding the selection of medication and by tailoring the doses and regimens to the actual needs of patients.


Individualised controlled ovarian stimulation, Ovarian response prediction index, Ovarian response, AMH levels

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