Hum Reprod. 2014 Jul;29(7):1360-7. doi: 10.1093/humrep/deu082. Epub 2014 May 2.
Do two semen analyses predict natural conception better than a single semen analysis and will adding the results of repeated semen analyses to a prediction model for natural pregnancy improve predictions?
A second semen analysis does not add helpful information for predicting natural conception compared with using the results of a single semen analysis and addition of the second analysis to a prediction model for natural conception did not improve predictions.
A major problem with semen analyses is the large variability of results within an individual. High-quality evidence is lacking on how many semen analyses need to be performed during the fertility workup to achieve an accurate prediction of conception.
STUDY DESIGN, SIZE, DURATION: We conducted a prospective cohort study of 897 consecutive couples presenting with subfertility in two university hospitals in the period 2002-2004 in the Netherlands.
PARTICIPANTS/MATERIALS, SETTING, AND METHODS: The laboratories scored sperm parameters according to the 1999 WHO criteria. Sperm concentration was counted and motility was assessed in a Makler counting chamber at a magnification of ×200. All assessments were performed by trained laboratory technicians. Follow-up started at the completion of the infertility workup and ended after 12 months. Primary end-point was natural conception resulting in an ongoing pregnancy. We constructed models for three strategies for the prediction of natural conception, using univariable and multivariable Cox hazard regression analyses. We evaluated the performance of the three strategies by comparing goodness-of-fit, discrimination and calibration. First, we analysed the semen parameters only. Secondly, we analysed the semen parameters in addition to the multivariable Hunault prediction model.
Of the 897 couples, 132 (15%) achieved a pregnancy by natural conception. Using the results of a single semen analysis only, the calculated probabilities of natural conception within 12 months across the study population ranged from 0.12 to 0.38, with a median of 0.16 (IQR: 0.16-0.17). Using the results of two semen analyses did not lead to a better goodness-of-fit. Discriminative capacity was rather poor, with an area under the ROC curve (AUC) ranging from 0.51 to 0.56. Using the Hosmer-Lemeshow test statistic we found no signs of poor calibration. Using the results of two semen analyses in combination with the Hunault model did not significantly increase goodness-of-fit compared with using a single semen analysis. The Hunault model with the addition of the semen parameters fitted the data significantly better than the Hunault model itself (difference in -2 Log likelihood: 13; 3 df; P = 0.002). Using the Hosmer-Lemeshow test statistic we found no signs of poor calibration.
LIMITATIONS, REASONS FOR CAUTION: The academic setting possibly explains the relatively low natural conception rates, with only 15% achieving a natural conception within 1 year. Men with azoospermia were excluded.
Performing more than one semen analysis will not increase the prognostic power of the test in clinical practice. Adding the first semen analysis to the Hunault model for the prediction of natural conception improved performance significantly compared with using the Hunault model alone. External validation, in other populations, should follow to confirm our conclusions, and to evaluate the generalizability or transportability of the extended Hunault model.
STUDY FUNDING/COMPETING INTEREST(S): No external funding was involved in this study. None of the authors has any conflict of interest to declare.
两次精液分析是否比单次精液分析更能预测自然受孕,并且将多次精液分析的结果添加到自然妊娠预测模型中是否会改善预测?
与使用单次精液分析结果相比,第二次精液分析并不能提供有助于预测自然受孕的信息,并且将第二次分析添加到自然受孕预测模型中并不能改善预测。
精液分析的一个主要问题是个体内结果的可变性很大。缺乏高质量的证据来证明在生育检查期间需要进行多少次精液分析才能准确预测受孕。
研究设计、大小和持续时间:我们在荷兰的两所大学医院进行了一项前瞻性队列研究,纳入了 2002-2004 年期间因不育就诊的 897 对夫妇。
参与者/材料、设置和方法:实验室根据 1999 年世界卫生组织标准对精子参数进行评分。精子浓度在 Makler 计数室中用 ×200 倍的放大倍数进行计数,精子活力在 Makler 计数室中用 ×200 倍的放大倍数进行评估。所有评估均由经过培训的实验室技术人员进行。随访从完成不育检查开始,持续 12 个月。主要终点是自然受孕导致的妊娠。我们构建了三种预测自然受孕的策略模型,使用单变量和多变量 Cox 风险回归分析。我们通过比较拟合优度、区分度和校准来评估三种策略的性能。首先,我们分析了精液参数。其次,我们分析了精液参数以及 Hunault 多变量预测模型。
在 897 对夫妇中,有 132 对(15%)通过自然受孕实现了妊娠。使用单次精液分析的结果,研究人群中 12 个月内自然受孕的概率范围为 0.12 至 0.38,中位数为 0.16(IQR:0.16-0.17)。使用两次精液分析并不能导致更好的拟合优度。区分能力相当差,ROC 曲线下面积(AUC)范围为 0.51 至 0.56。使用 Hosmer-Lemeshow 检验统计量,我们没有发现校准不良的迹象。使用两次精液分析的结果与 Hunault 模型结合使用,与使用单次精液分析相比,并没有显著提高拟合优度。与 Hunault 模型本身相比,添加精液参数的 Hunault 模型拟合数据的效果明显更好(对数似然差:13;3 个自由度;P=0.002)。使用 Hosmer-Lemeshow 检验统计量,我们没有发现校准不良的迹象。
局限性、谨慎的原因:学术环境可能解释了相对较低的自然受孕率,只有 15%的夫妇在 1 年内自然受孕。排除了无精子症的男性。
进行多次精液分析不会增加该检测在临床实践中的预测能力。将第一次精液分析添加到 Hunault 模型中,可显著提高自然受孕预测的性能,与单独使用 Hunault 模型相比。应进行外部验证,以确认我们的结论,并评估扩展的 Hunault 模型的普遍性或可转移性。
研究资金/利益冲突:本研究无外部资金支持。作者均无利益冲突声明。