Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK.
Warwick Clinical Trial Units, Warwick Medical School, University of Warwick, Coventry, UK.
Hum Reprod. 2022 Aug 25;37(9):2075-2086. doi: 10.1093/humrep/deac152.
Can we develop an IVF prediction model to estimate individualized chances of a live birth over multiple complete cycles of IVF in couples embarking on their second complete cycle of treatment?
Yes, our prediction model can estimate individualized chances of cumulative live birth over three additional complete cycles of IVF.
After the completion of a first complete cycle of IVF, couples who are unsuccessful may choose to undergo further treatment to have their first child, while those who have had a live birth may decide to have more children. Existing prediction models can estimate the overall chances of success in couples before commencing IVF but are unable to revise these chances on the basis of the couple's response to a first treatment cycle in terms of the number of eggs retrieved and pregnancy outcome. This makes it difficult for couples to plan and prepare emotionally and financially for the next step in their treatment.
STUDY DESIGN, SIZE, DURATION: For model development, a population-based cohort was used of 49 314 women who started their second cycle of IVF including ICSI in the UK from 1999 to 2008 using their own oocytes and their partners' sperm. External validation was performed on data from 39 442 women who underwent their second cycle from 2010 to 2016.
PARTICIPANTS/MATERIALS, SETTING, METHODS: Data about all UK IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA) database. Using a discrete time logistic regression model, we predicted the cumulative probability of live birth from the second up to and including the fourth complete cycles of IVF. Inverse probability weighting was used to account for treatment discontinuation. Discrimination was assessed using c-statistic and calibration was assessed using calibration-in-the-large and calibration slope.
Following exclusions, 49 314 women with 73 053 complete cycles were included. 12 408 (25.2%) had a live birth resulting from their second complete cycle. Cumulatively, 17 394 (35.3%) had a live birth over complete cycles two to four. The model showed moderate discriminative ability (c-statistic: 0.65, 95% CI: 0.64 to 0.65) and evidence of overprediction (calibration-in-the-large = -0.08) and overfitting (calibration slope 0.85, 95% CI: 0.81 to 0.88) in the validation cohort. However, after recalibration the fit was much improved. The recalibrated model identified the following key predictors of live birth: female age (38 versus 32 years-adjusted odds ratio: 0.59, 95% CI: 0.57 to 0.62), number of eggs retrieved in the first complete cycle (12 versus 4 eggs; 1.34, 1.30 to 1.37) and outcome of the first complete cycle (live birth versus no pregnancy; 1.78, 1.66 to 1.91; live birth versus pregnancy loss; 1.29, 1.23 to 1.36). As an example, a 32-year-old with 2 years of non-tubal infertility who had 12 eggs retrieved from her first stimulation and had a live birth during her first complete cycle has a 46% chance of having a further live birth from the second complete cycle of IVF and an 81% chance over a further three cycles.
LIMITATIONS, REASONS FOR CAUTION: The developed model was updated using validation data that was 6 to 12 years old. IVF practice continues to evolve over time, which may affect the accuracy of predictions from the model. We were unable to adjust for some potentially important predictors, e.g. BMI, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. These were not available in the linked HFEA dataset.
By appropriately adjusting for couples who discontinue treatment, our novel prediction model will provide more realistic chances of live birth in couples starting a second complete cycle of IVF. Clinicians can use these predictions to inform discussion with couples who wish to plan ahead. This prediction tool will enable couples to prepare emotionally, financially and logistically for IVF treatment.
STUDY FUNDING/COMPETING INTEREST(S): This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. The authors have no conflict of interest.
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我们能否制定一个体外受精（IVF）预测模型，以估计在开始第二次完整治疗周期的夫妇中，多次完整 IVF 周期的活产个体化几率？
是的，我们的预测模型可以估计在另外三个完整 IVF 周期中累积活产的几率。
在完成第一次完整 IVF 周期后，不成功的夫妇可能会选择进一步治疗以生育第一个孩子，而已经有活产的夫妇可能会决定生育更多孩子。现有的预测模型可以在开始 IVF 之前估计夫妇成功的总体几率，但无法根据夫妇在取卵数量和妊娠结局方面对第一次治疗周期的反应来修正这些几率。这使得夫妇难以在情感、经济和后勤方面为治疗的下一步做好准备。
研究设计、规模、持续时间：为了进行模型开发，使用了英国从 1999 年至 2008 年使用自身卵子和伴侣精子进行第二次 IVF 加卵胞浆内单精子注射（ICSI）周期的 49314 名妇女的基于人群的队列。从 2010 年至 2016 年进行第二次周期的 39442 名妇女的数据用于外部验证。
参与者/材料、设置、方法：从人类受精和胚胎管理局（HFEA）数据库中获得了所有英国 IVF 治疗的数据。使用离散时间逻辑回归模型，我们预测了从第二次到第四次完整 IVF 周期的累积活产几率。使用逆概率加权来考虑治疗中断的情况。使用 C 统计量评估判别能力，使用大样本校准和校准斜率评估校准。
排除后，纳入 49314 名妇女，共 73053 个完整周期。其中 12408 名（25.2%）在第二次完整周期中活产。累计有 17394 名（35.3%）在完成周期 2 至 4 时活产。该模型显示出中等的判别能力（C 统计量：0.65，95%置信区间：0.64 至 0.65），并存在过度预测（大样本校准=-0.08）和过度拟合（校准斜率 0.85，95%置信区间：0.81 至 0.88）的证据，在验证队列中。然而，经过重新校准后，拟合度得到了很大的改善。经重新校准的模型确定了活产的以下关键预测因素：女性年龄（38 岁与 32 岁；调整后的优势比：0.59，95%置信区间：0.57 至 0.62）、第一次完整周期中取卵数（12 个与 4 个卵子；1.34，1.30 至 1.37）和第一次完整周期的结果（活产与无妊娠；1.78，1.66 至 1.91；活产与妊娠丢失；1.29，1.23 至 1.36）。例如，一位 32 岁、非输卵管性不孕 2 年的患者，第一次刺激取卵 12 个，第一次完整周期活产，那么她从第二次完整周期 IVF 中再次活产的几率为 46%，从第三次完整周期中再次活产的几率为 81%。
局限性、谨慎的原因：开发的模型使用的验证数据为 6 至 12 年前的数据。随着时间的推移，IVF 实践继续发展，这可能会影响模型预测的准确性。我们无法调整一些潜在的重要预测因素，例如女性的 BMI、吸烟和饮酒量，以及卵巢储备的测量，如窦卵泡计数。这些都无法在相关的 HFEA 数据集中获得。
通过适当调整因治疗而中断的夫妇，我们的新预测模型将为开始第二次完整 IVF 周期的夫妇提供更现实的活产几率。临床医生可以使用这些预测结果与希望提前计划的夫妇进行讨论。该预测工具将使夫妇能够在情感、经济和后勤方面为 IVF 治疗做好准备。
研究资金/利益冲突：本研究得到阿伯丁大学和阿伯丁生育中心的 Elphinstone 奖学金计划和阿伯丁大学的支持。作者没有利益冲突。
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