Prognostic value of serum CA-125 measurements on stimulation day 1 and on the day of oocyte pickup in the prediction of IVF treatment outcome

An in silico model using prognostic genetic factors for ovarian response in controlled ovarian stimulation: A systematic review

PURPOSE

To study the use of in silica model to better understand and propose new markers of ovarian response to controlled ovarian stimulation before IVF.

METHODS

A systematic review and in silica model using bioinformatics. After the selection of 103 papers from a systematic review process, we performed a GRADE qualification of all included papers for evidence-based quality evaluation. We included 57 genes in the silica model using a functional protein network interaction. Moreover, the construction of protein-protein interaction network was done importing these results to Cytoscape. Therefore, a cluster analysis using MCODE was done, which was exported to a plugin BINGO to determine Gene Ontology. A p value of < 0.05 was considered significant, using a Bonferroni correction test.

RESULTS

In silica model was robust, presenting an ovulation-related gene network with 87 nodes (genes) and 348 edges (interactions between the genes). Related to the network centralities, the network has a betweenness mean value = 102.54; closeness mean = 0.007; and degree mean = 8.0. Moreover, the gene with a higher betweenness was PTPN1. Genes with the higher closeness were SRD5A1 and HSD17B3, and the gene with the lowest closeness was GDF9. Finally, the gene with a higher degree value was UBB; this gene participates in the regulation of TP53 activity pathway.

CONCLUSIONS

This systematic review demonstrated that we cannot use any genetic marker before controlled ovarian stimulation for IVF. Moreover, in silica model is a useful tool for understanding and finding new markers for an IVF individualization.

PROSPERO

CRD42020197185.

Value of Post-transfer Day-12 Beta Human Chorionic Gonadotropin Levels for Pregnancy Outcome Prediction of Intracytoplasmic Sperm Injection Cycles

BACKGROUND

Several markers were studied previously in order to predict the pregnancy outcome of assisted reproductive techniques; however, serum beta human chorionic gonadotropin was found to be the most predictive marker.

AIMS

To evaluate the value of serum beta human chorionic gonadotropin levels in discriminating biochemical and clinical pregnancies 12 days after embryo transfer, while determining the factors predicting ongoing pregnancy was established as the secondary aim.

STUDY DESIGN

Retrospective cross-sectional study.

METHODS

A total of 445 pregnant cycles were retrospectively analysed in 2359 embryo transfer cycles. Patients were divided into two groups according to the outcome of pregnancy: biochemical and clinical.

RESULTS

The cut-off value of beta human chorionic gonadotropin levels on day 12 in predicting clinical pregnancies was 86.8 IU/mL with 65.1% sensitivity and 74.7% specificity [CI: 0.76 (0.71-0.81). Receiver operating characteristic curve analysis revealed different cut-off values for embryo transfer days (57 mIU/mL for day 3 embryo transfer CI: 0.59-0.79 and 87 mIU/mL for day 5 embryo transfer, CI: 0.74-0.86). Subgroup analysis of clinical pregnancies revealed a significant difference between ongoing pregnancies and early fetal losses regarding duration of infertility (81.3±54.4 vs. 100.2±62.2 months), serum oestradiol on hCG day (2667.4±1276.4 vs. 2094.6±1260.5 pg/mL), number of transferred embryos (1.9±0.8 vs. 1.5±0.7) and the prevalence of diminished ovarian reserve as an indication (2.3% vs 12.2%).

CONCLUSION

Beta human chorionic gonadotropin levels on day 12 following embryo transfer provide an important parameter for the prediction of clinical pregnancy; however, other stimulation parameters are indicated in the prediction of ongoing pregnancies.