Reproductive Medicine Center, Sichuan Provincial Women's and Children's Hospital, The Affiliated Women's and Children's Hospital of Chengdu Medical College, 290 Shayan West Second Street, Wuhou District, Chengdu 610045, Sichuan, China.
Reproductive Medicine Center, Sichuan Provincial Women's and Children's Hospital, The Affiliated Women's and Children's Hospital of Chengdu Medical College, 290 Shayan West Second Street, Wuhou District, Chengdu 610045, Sichuan, China.
Eur J Obstet Gynecol Reprod Biol. 2023 Sep;288:153-159. doi: 10.1016/j.ejogrb.2023.07.012. Epub 2023 Jul 24.
During the past decades, the number of elderly infertile women is obviously increasing in China, and more and more of them are likely to seek medical assisted reproductive technologies. As the in vitro fertilization/embryo transfer (IVF/ET) treatment presents special medical and psychological challenges to elderly infertile women, it is extremely helpful to perform the clinical evaluation and outcome prediction regarding IVF/ET outcomes. In this study, we retrospectively collected 12 clinical measurements in prior to the oocyte recovery for 689 elderly infertile patients (≥35 years of old), and used for predicting ovarian responses to the controlled ovarian hyperstimulation based on random forest regression models. Using different predictor sets and 10-fold cross validation approach, the Mean Square Error (±standard deviation) of prediction models varied from 7.56 ± 0.31 to 13.90 ± 0.37 in the training datasets, and the correlation coefficients between observed and predicted values ranged from 0.86 ± 0.02 to 0.72 ± 0.05 in the testing datasets. Among all clinical measurements involved in this study, the preovulatory follicle count (PFC), antral follicle count (AFC), and anti-Müllerian hormone (AMH) were revealed to be the most important features in prediction models. In conclusion, we successfully established the machine learning approach that could help the elderly infertile patients to better understand the most possible outcomes in subjecting to the controlled ovarian hyperstimulation.
在过去的几十年中，中国老年不孕女性的数量明显增加，越来越多的老年不孕女性可能会寻求医学辅助生殖技术。由于体外受精/胚胎移植（IVF/ET）治疗对老年不孕女性带来特殊的医学和心理挑战，因此对 IVF/ET 结果进行临床评估和预测极为有益。在这项研究中，我们回顾性地收集了 689 名老年不孕患者（≥35 岁）在取卵前的 12 项临床测量值，并使用随机森林回归模型来预测卵巢对控制性卵巢过度刺激的反应。使用不同的预测器集和 10 倍交叉验证方法，在训练数据集中，预测模型的均方误差（±标准偏差）从 7.56±0.31 变化到 13.90±0.37，在测试数据集中，观察值与预测值之间的相关系数从 0.86±0.02 变化到 0.72±0.05。在所涉及的所有临床测量值中，促排卵前卵泡计数（PFC）、窦卵泡计数（AFC）和抗苗勒氏管激素（AMH）被证明是预测模型中最重要的特征。总之，我们成功地建立了机器学习方法，可以帮助老年不孕患者更好地了解在接受控制性卵巢过度刺激时最可能的结果。
