个性化选择性卵子冷保存:在多个刺激周期中预测卵子产量的新型模型
Jack Tighe1, Efstathios Theodorou2, Nicholas Anson1,2
1Department of Gynaecology, Imperial College Healthcare NHS Trust, London, Hammersmith Hospital, London, UK.
Human reproduction (Oxford, England)
|September 5, 2025
概括
通过使用患者年龄,囊数 (AFC),抗穆勒激素 (AMH) 和FSH水平的模型,预测选择性卵细胞冷保存 (EOC) 的产量得到了改善. 这有助于保育辅导.
科学领域:
- 生殖内分泌学
- 不孕症研究
- 医学中的生物统计学
背景情况:
- 延迟生育的趋势越来越多, 需要选择性卵子冷保存 (EOC) 等生育保护策略.
- 卵巢储备随着年龄的增长而自然减少,影响卵细胞的质量和数量,增加与年龄相关的生育能力下降的风险.
- 目前用于卵细胞产量预测的模型通常集中在单个周期或亚肥沃种群上,限制了对经过EOC的肥沃个体的适用性.
研究的目的:
- 在接受EOC的患者中开发和验证冷藏卵细胞产量的预测模型.
- 评估结合患者年龄和卵巢储备标记 (AFC,AMH,FSH) 的模型的预测准确性.
- 加强临床医生与患者的咨询,以了解EOC周期的卵细胞产量.
主要方法:
- 在579名接受一个或多个EOC周期的患者中进行了回顾性队列研究.
- 收集的基线数据包括年龄,BMI,毛囊数 (AFC),抗Müllerian激素 (AMH) 和FSH水平.
- 使用负二项回归与概括估计方程和接收器运行特征 (ROC) 曲线分析来评估模型性能.
主要成果:
- 结合年龄,AFC,AMH和FSH的模型显示出最高的预测准确度 (AUC为0. 7922的良好反应;0. 7917的充分反应).
- 结合年龄和卵巢储备标记的模型显示出对良好的 (≥10个卵子细胞) 和充足的 (≥5个卵子细胞) 结冷保存结果的显著预测能力.
- 年龄和AMH的组合单独提供了测试模型中最低的预测准确性.
结论:
- 一个整合患者年龄和卵巢储备测试 (AFC,AMH,FSH) 的预测模型为估计EOC中的卵细胞产量提供了强大的准确性.
- 这些模型可以显著改善考虑使用EOC来保护生育能力的人的咨询过程.
- 未来的研究可以通过在多中心研究中包括种族和先前的EOC结果来提高模型的精度.
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