Prediction of poor ovarian response during In vitro fertilization in Nigerian women: A comparison of basal antral follicle count and follicle-stimulating hormone

Background: Poor ovarian reserve has been shown to be associated with poor outcomes of in-vitro fertilization (IVF) treatment. Women who can be reliably identified as expected poor responders can be advised on chances of poor outcomes that may dissuade them from wasting resources on IVF using their own eggs; and offered donor eggs, especially in a resource-poor country like Nigeria. Many centres routinely perform basal follicle-stimulating hormone (FSH) assay before IVF; however, basal antral follicle count (AFC) has emerged as a more reliable test of ovarian reserve that can be provided at a reduced cost compared to FSH in an IVF clinic setting. The determined predictive values of basal AFC compared to FSH in Nigerian women can be used to predict poor ovarian response during IVF treatment; and also to influence local clinical practice in IVF by offering a more reliable and affordable test, thereby avoiding wastage due to duplicate and unnecessary investigations. Aim: The aim is to determine the diagnostic accuracy of basal AFC compared to basal FSH for the prediction of ovarian response during the IVF cycle in Nigerian women. Patients, Materials and Methods: This was a hospital-based prospective comparative study in two private fertility centres in Abuja. Consecutive 166 women that underwent IVF treatment cycles who met the inclusion criteria were recruited. On day 2 to day 4 of a normal cycle, FSH assay and AFC using the Broekmans' systematic process were done. They had controlled ovarian hyperstimulation by antagonist or agonist and occasionally long protocols. The poor response was defined as <4 follicles of >17 mm on the day of human chorionic gonadotropin trigger or ≤3 oocytes retrieved. Receiver operating characteristics (ROC) analysis was done to determine the level of the area under the curve (AUC) and optimum cut-off values of FSH and AFC in predicting poor ovarian response. Results: Twenty-eight (16.9%) had poor responses. ROC analysis demonstrated that AFC had the largest (AUC = 0.707, P = 0.001) relative to FSH (AUC = 0.591, P = 0.128). The ROC analysis showed that the optimum cut-off value for the prediction of poor response for AFC was ≤10, which had a higher accuracy of 67.5%, while for FSH was ≥8.15 mIU/ml with a lower accuracy of 61.5%. They both had the same sensitivity of 60.7%; however, AFC had better specificity, negative and positive predictive value, and higher odds ratio for the prediction of poor ovarian response. The positive and negative likelihood ratios of both cut-off values suggest that they may not be useful as diagnostic tests. Conclusion: ROC analysis estimated that AFC more accurately predicts poor ovarian response by its larger and more significant AUC compared to FSH in our population of women.