Statistical Modelling Outcome of In Vitro Fertilization and Intracytoplasmic Sperm Injection: A Single Centre Study

Assisted reproductive techniques (ART) have been extensively used to treat infertility. Inaccurate prediction of a couple's fertility often leads to lowered self-esteem for patients seeking ART treatment and causes fertility distress.

This prospective study aimed to statistically analyze patient data from a single reproductive medical center over a period of 18 months, and to establish mathematical models that might facilitate accurate prediction of successful pregnancy when ART are used.

In the present study, we analyzed clinical data prospectively collected from 760 infertile patients visiting the second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University between June 1, 2016 and December 31, 2017. Various advanced statistical methods, including broken-line regression, were employed to analyze the data.

Age remained the most important factor affecting the outcome of IVF/ICSI. Using the broken-line regression model, the fastest clinical pregnancy declining age was between 25 and 32. Female infertility type was found to be a key predictor for the number of good-quality embryos and successful pregnancy, along with the antral follicle count (AFC), total number of embryos, recombinant follicle stimulating hormones (rFSH) dosage, estradiol (E2) on the trigger day, and total number of oocytes retrieved. rFSH dosage was also significantly associated with the number of oocytes retrieved and the number of frozen embryos.

The fastest clinical pregnancy declining age is ranged between 25 and 32, and female infertility type is evidenced as another key predictive factor for the cumulative outcome of ART.