A new decision-support tool in a multi-center randomized trial for personalized, optimized, and simplified fertility treatment in non-PCOS patients.

Abstract

This study aimed to evaluate the effectiveness of a clinical decision support tool, Opt-IVF, in achieving the following outcomes: reducing the total cumulative dosage of Gonadotropins (Gns) used during controlled ovarian stimulation cycles and reducing the repeated ultrasonograms (USG) for monitoring follicular growth without compromising the number of good quality blastocysts obtained. The study design employed a multi-center randomized trial. The study enrolled 115 women aged 25-45 years undergoing IVF. Among the participants, 55 were randomly assigned to the intervention group (Opt-IVF), and 60 were randomly assigned to the control group. The intervention involved using a clinical decision support tool, Opt-IVF, to guide Gn dosing and trigger dates. The participants in the intervention group required significantly lower cumulative Gn dosage. The intervention group had higher numbers of oocytes retrieved and M2 retrieved than the control group. The number of good-quality blastocysts, the good-quality blastocyst rate, the ovarian sensitivity index (OSI), and the pregnancy rate in the intervention group were significantly higher than in the control group. The utilization of the clinical decision support tool led to several positive outcomes, including eliminating the need for ultrasound exams after day 5, reducing the dosage of Gn required, and yielding significantly higher numbers of high-quality blastocysts and higher pregnancy rates. Thus, Opt-IVF can successfully provide a personalized, optimized, and simplified approach to superovulation. Opt-IVF consistently outperformed the clinical teams in most of the outcomes. Clinical trials registration: ClinicalTrials.gov (ID - NCT05811065). Date of Registration: 15 March 2023. Date of enrollment of the first subject: 20 March 2023. The high cost of IVF is a result of costly drugs, fixed prices for infrastructure, extensive testing required, and labor costs for physicians and other healthcare personnel. Superovulation, which involves the drug-induced release of multiple eggs needed for IVF, accounts for a significant share of these costs. Current approaches to superovulation involve almost daily monitoring of follicle development using ultrasound and/or blood tests. The daily dosage of stimulatory hormones is then prescribed by physicians based on empirical data and clinical experience. However, the dose is not optimized for each patient, and overstimulation complications can occur. The cost of testing and drugs makes this stage very expensive. To overcome the shortcomings of this system, we have developed a decision support tool (Opt-IVF) that can provide a personalized model-optimized dosage profile for each patient. The clinical results show that Opt-IVF optimizes and personalizes dosage, reduces testing, and provides better outcomes for patients.