Schouten Nienke, Wang Rui, Torrance Helen, Van Tilborg Theodora, Bastu Ercan, Bergh Christina, D'Hooghe Thomas, Friis Petersen Jesper, Jayaprakasan Kannamannadiar, Khalaf Yacoub, Klinkert Ellen, La Marca Antonio, Vuong Lan, Lapensée Louise, Lensen Sarah, Magnusson Åsa, Allegra Adolfo, Nyboe Andersen Anders, Oudshoorn Simone, Popovic-Todorovic Biljana, Mol Ben Willem, Eijkemans Marinus, Broekmans Frank
Division Woman and Baby, Reproductive Medicine, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
Department of Obstetrics and Gynaecology, Monash Medical Centre, Monash University, Clayton, VIC, Australia.
Hum Reprod Update. 2025 Mar 1;31(2):116-132. doi: 10.1093/humupd/dmae032.
The ovarian response to gonadotropin stimulation varies widely among women, and could impact the probability of live birth as well as treatment risks. Many studies have evaluated the impact of different gonadotropin starting doses, mainly based on predictive variables like ovarian reserve tests (ORT) including anti-Müllerian hormone (AMH), antral follicle count (AFC), and basal follicle-stimulating hormone (bFSH). A Cochrane systematic review revealed that individualizing the gonadotropin starting dose does not affect efficacy in terms of ongoing pregnancy/live birth rates, but may reduce treatment risks such as the development of ovarian hyperstimulation syndrome (OHSS). An individual patient data meta-analysis (IPD-MA) offers a unique opportunity to develop and validate a universal prediction model to help choose the optimal gonadotropin starting dose to minimize treatment risks without affecting efficacy.
The objective of this IPD-MA is to develop and validate a gonadotropin dose-selection model to guide the choice of a gonadotropin starting dose in IVF/ICSI, with the purpose of minimizing treatment risks without compromising live birth rates.
Electronic databases including MEDLINE, EMBASE, and CRSO were searched to identify eligible studies. The last search was performed on 13 July 2022. Randomized controlled trials (RCTs) were included if they compared different doses of gonadotropins in women undergoing IVF/ICSI, presented at least one type of ORT, and reported on live birth or ongoing pregnancy. Authors of eligible studies were contacted to share their individual participant data (IPD). IPD and information within publications were used to determine the risk of bias. Generalized linear mixed multilevel models were applied for predictor selection and model development.
A total of 14 RCTs with data of 3455 participants were included. After extensive modeling, women aged 39 years and over were excluded, which resulted in the definitive inclusion of 2907 women. The optimal prediction model for live birth included six predictors: age, gonadotropin starting dose, body mass index, AFC, IVF/ICSI, and AMH. This model had an area under the curve (AUC) of 0.557 (95% confidence interval (CI) from 0.536 to 0.577). The clinically feasible live birth model included age, starting dose, and AMH and had an AUC of 0.554 (95% CI from 0.530 to 0.578). Two models were selected as the optimal model for combined treatment risk, as their performance was equal. One included age, starting dose, AMH, and bFSH; the other also included gonadotropin-releasing hormone (GnRH) analog. The AUCs for both models were 0.769 (95% CI from 0.729 to 0.809). The clinically feasible model for combined treatment risk included age, starting dose, AMH, and GnRH analog, and had an AUC of 0.748 (95% CI from 0.709 to 0.787).
The aim of this study was to create a model including patient characteristics whereby gonadotropin starting dose was predictive of both live birth and treatment risks. The model performed poorly on predicting live birth by modifying the FSH starting dose. On the contrary, predicting treatment risks in terms of OHSS occurrence and management by modifying the gonadotropin starting dose was adequate. This dose-selection model, consisting of easily obtainable patient characteristics, aids in the choice of the optimal gonadotropin starting dose for each individual patient to lower treatment risks and potentially reduce treatment costs.
女性对促性腺激素刺激的卵巢反应差异很大，这可能会影响活产概率以及治疗风险。许多研究评估了不同促性腺激素起始剂量的影响，主要基于诸如卵巢储备测试（ORT）等预测变量，包括抗苗勒管激素（AMH）、窦卵泡计数（AFC）和基础卵泡刺激素（bFSH）。一项Cochrane系统评价显示，在持续妊娠/活产率方面，个体化促性腺激素起始剂量并不影响疗效，但可能会降低诸如卵巢过度刺激综合征（OHSS）发生等治疗风险。个体患者数据荟萃分析（IPD-MA）提供了一个独特的机会来开发和验证一个通用预测模型，以帮助选择最佳促性腺激素起始剂量，在不影响疗效的情况下将治疗风险降至最低。
本IPD-MA的目的是开发并验证一个促性腺激素剂量选择模型，以指导体外受精/卵胞浆内单精子注射（IVF/ICSI）中促性腺激素起始剂量的选择，目的是在不影响活产率的情况下将治疗风险降至最低。
检索了包括MEDLINE、EMBASE和CRSO在内的电子数据库，以确定符合条件的研究。最后一次检索于2022年7月13日进行。纳入的随机对照试验（RCT）需满足以下条件：比较接受IVF/ICSI的女性中不同剂量的促性腺激素，呈现至少一种ORT类型，并报告活产或持续妊娠情况。联系符合条件研究的作者以共享其个体参与者数据（IPD）。IPD和出版物中的信息用于确定偏倚风险。应用广义线性混合多水平模型进行预测变量选择和模型开发。
共纳入14项RCT，涉及3455名参与者的数据。经过广泛建模，排除了39岁及以上的女性，最终纳入2907名女性。活产的最佳预测模型包括六个预测变量：年龄、促性腺激素起始剂量、体重指数、AFC、IVF/ICSI和AMH。该模型的曲线下面积（AUC）为0.557（95%置信区间（CI）为0.536至0.577）。临床可行的活产模型包括年龄、起始剂量和AMH，AUC为0.554（95%CI为0.530至0.578）。两个模型被选为联合治疗风险的最佳模型，因为它们的表现相当。一个模型包括年龄、起始剂量、AMH和bFSH；另一个模型还包括促性腺激素释放激素（GnRH）类似物。两个模型的AUC均为0.769（95%CI为0.729至0.809）。临床可行的联合治疗风险模型包括年龄、起始剂量、AMH和GnRH类似物，AUC为0.748（95%CI为0.709至0.787）。
本研究的目的是创建一个包含患者特征的模型，据此促性腺激素起始剂量可预测活产和治疗风险。该模型在通过调整FSH起始剂量预测活产方面表现不佳。相反，通过调整促性腺激素起始剂量来预测OHSS发生和管理方面的治疗风险是足够的。这个由易于获得的患者特征组成的剂量选择模型有助于为每个个体患者选择最佳促性腺激素起始剂量，以降低治疗风险并可能降低治疗成本。
