Predicting Live Birth Probability in Young Women Undergoing IVF
Author Information
Author(s): Liu Chang, Pan Peipei, Li Beihai, Teng Yili
Primary Institution: Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University
Hypothesis
Can a nomogram model accurately predict the risk of lower live birth probability in young women undergoing their first IVF cycle?
Conclusion
The developed nomogram effectively predicts the risk of retrieving fewer than 10 oocytes in women ≤ 35 years of age, aiding in clinical decision-making.
Supporting Evidence
- The nomogram was validated with an AUC of 0.82 in the validation cohort.
- Five independent predictors were identified: age, AFC, AMH, FSH, and FSH/LH ratio.
- The model demonstrated good calibration and discrimination in both training and validation groups.
- The study included a large sample size of 9265 women.
Takeaway
This study created a tool to help doctors predict how many eggs young women might get during IVF, which can help them make better treatment choices.
Methodology
A retrospective study using LASSO regression to identify predictors and develop a nomogram based on data from 9265 women undergoing their first IVF cycle.
Potential Biases
Potential selection bias due to loss of follow-up and inability to account for all confounding factors.
Limitations
The study is retrospective and data were collected from a single center, which may limit generalizability.
Participant Demographics
Women ≤ 35 years of age undergoing their first IVF/ICSI cycle.
Statistical Information
P-Value
p<0.001
Confidence Interval
95% CI: 0.80-0.82
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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