Fertility scoring index: CIMAR’S novel system to predict assisted reproductive technology success

Abstract

Background: About 15% of all couples are infertile and require fertility treatment. With constantly improving clinical and laboratory procedures, pregnancy rates of about 30% per transfer are routinely reported. In non-donor-oocyte cycles, the percentage of in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) cycles that result in pregnancy ranges from 18 to 45%, depending on several factors (Society for Assisted Reproductive Technology 2009). But a patients concern is about the success rate—‘What is my chance of getting pregnant’? For the success in IVF/ICSI—embryo transfer cycle there are many variables thought to be directly related to the implantation and successful outcome. Aims and objectives: 1. To identify independent predictors ICSI outcome. 2. To make a composite predictive scoring system—a. For patient selection and counseling for assisted reproductive technology (ART). b. That may prove critical in counseling poor prognosis patients, about their prognosis or against IVF treatment (e.g. patients with least benefits in undergoing IVF can opt for donor oocytes/surrogacy, etc. without wasting a cycle in trial and error). c. Optimizing treatment by developing more customized individually tailored treatment plan with consideration to predictive factors. Study design: The research was approved by the institutional review board. A retrospective ongoing study was performed, over a period of 3 years at a well established infertility institution. A sample size of 1020 patients was considered from two hospitals of the same institution. The patients were stimulated by different protocols specific to each patients age, AFC, etc [Polycystic ovarian syndrome (PCOS) patients showing hyperresponse in follicular study-antagonist protocol]; though a majority underwent long agonist protocol. They were evaluated and the outcome was assessed through logistic regression analysis. Several variables were taken into consideration—to name a few; age, previous pregnancy outcome, previous ART treatment if any, E2/LH/P4 [baseline values and on the day of human chorionic gonadotropin (hCG)], etc. A preferential scoring was derived to obtain a predictive scoring for pregnancy outcome. Results: A pregnancy predicting scoring was arrived at. On considering several variables, the cut off score represented a 50% success rate of IVF/ICSI cycle. Conclusion: Bearing in mind that fertility is independent of hospital protocols and primarily dependent on the individual woman, the derived predictive scoring can be applied to individual cohort of patients under infertility treatment and has excellent discrimination ability for assessing the likelihood of pregnancy outcome. Application of this scoring will allow individualized treatment decision-making for patients under infertility treatment.