Department of Obstetrics and Gynecology, Clinique La Sagesse, Rennes, France.
Department de Medecine de La Reproduction, Centre Medico-Chirurgical Et Obstetrical (CMCO), 19 rue Louis Pasteur, 67300 Schiltigheim, Strasbourg, France.
J Assist Reprod Genet. 2024 Jan;41(1):213-222. doi: 10.1007/s10815-023-02975-w. Epub 2023 Nov 3.
To improve the reliability of prediction models for ovarian response to stimulation in ART.
A multicenter retrospective cohort study.
Twelve reproductive centers.
A total of 25,854 controlled ovarian stimulations between 2005 and 2016, including cycles cancelled for inadequate response, were included.
INTERVENTION(S): None.
MAIN OUTCOME MEASURE(S): Precision of the prediction of the number of oocytes at ovarian pickup and of cancellation rate for poor ovarian response.
Both AMH and antral follicle count exhibit a non-linear effect on the oocyte yield, with a linear relationship after log-transformation. After adjustment for age, BMI, and center, ovarian response observed in a previous stimulation was found to be the best predictor, followed by AMH and AFC. The zero-inflated binomial negative model showed that predictors of cycle cancellation and number of oocytes at retrieval were different, and assimilating cancellation to zero oocyte greatly reduces the determination of the model. Our model was characterized by the best ever reached determination (R=0.505 for non-naïve women, 0.313 for all the women) and provided evidence of a very strong difference among centers. The results can be easily converted in the prediction of response levels (poor-medium-good-high). Finally, in case of partial report of the above predictors, we show that the univariate prediction based on the best predictor provides a good approximation.
CONCLUSION(S): A substantial improvement of the ovarian response prediction is possible in modelling the possible cancellation decision, followed by the oocyte retrieval itself, according to an appropriate model based on previous stimulation and non-linear effects of AMH and AFC.
提高辅助生殖技术中卵巢刺激反应预测模型的可靠性。
多中心回顾性队列研究。
12 个生殖中心。
共纳入 2005 年至 2016 年期间 25854 例控制性卵巢刺激周期，包括因反应不足而取消的周期。
无。
预测卵巢取卵时获卵数和取消率的准确性。
AMH 和窦卵泡计数均对卵母细胞产量呈非线性影响，对数转换后呈线性关系。调整年龄、BMI 和中心后，发现前一次刺激中观察到的卵巢反应是最佳预测因素，其次是 AMH 和 AFC。零膨胀二项负模型表明，周期取消和取卵时卵母细胞数的预测因素不同，将取消率归为零卵母细胞会大大降低模型的确定度。我们的模型具有最佳的确定度（非初次刺激的女性为 0.505，所有女性为 0.313），并证明了中心之间存在很大差异。结果可以很容易地转换为反应水平的预测（差-中-好-高）。最后，在上述预测因子部分报告的情况下，我们表明基于最佳预测因子的单变量预测提供了很好的近似值。
根据基于既往刺激和 AMH 和 AFC 非线性效应的适当模型，对可能的取消决策以及随后的取卵本身进行建模，可以显著提高卵巢反应预测的准确性。
