Royston P
Department of Medical Physics, Royal Postgraduate Medical School, London, U.K.
Stat Med. 1991 Feb;10(2):221-40. doi: 10.1002/sim.4780100207.
The identification of the human fertile phase as the time during which a woman or a couple may conceive is elusive. The fertile time depends on many factors in each individual menstrual cycle and may be said to be more of a statistical than a physiological entity. This paper reviews the application of statistical methods to three areas related to conception and the fertile phase. The first is the prediction and detection of ovulation from serial measurements, such as hormones, basal body temperature and cervical mucus, throughout the menstrual cycle. Typically, such variables increase from some baseline level to a peak around ovulation (the most fertile time), then subside to low levels in the postovulatory phase. The statistical challenge is to detect the rise (signalling the onset of potential fertility) and subsequent fall. Analytic methods considered include thresholds, Bayesian change-point models and particularly the cumulative sum (cusum) technique which is both simple to apply and understand, and effective. The second area comprises appropriate methods of analysing and interpreting data from clinical studies of the fertile phase, especially in so-called natural family planning (NFP) where it is usual for women to observe several indices of potential fertility. Such studies usually try to establish the temporal relationships between markers of the fertile phase and examine the success of different combinations of markers in delineating the fertile time in comparison with a standard 'defined' phase, for example, the interval from three days before to two days after the peak of luteinizing hormone. The third area is the assessment of the probability of conception on certain days of the cycle, which is vital to the understanding of the fertile phase and its application to NFP. Direct estimation of such probabilities is impractical; instead, resort must be made to estimation by maximum likelihood of the parameters of specially constructed models. Suitable models are described. Finally, the need for a new prospective study of the probability of conception in relation to the markers of the fertile phase used in the symptothermal method of NFP is discussed.
将人类的可育期确定为女性或夫妻可能受孕的时间段并非易事。可育时间取决于每个月经周期中的许多因素，可以说它更多是一个统计学概念，而非生理学实体。本文回顾了统计方法在与受孕和可育期相关的三个领域的应用。第一个领域是通过在整个月经周期中对激素、基础体温和宫颈黏液等进行连续测量来预测和检测排卵。通常，这些变量会从某个基线水平上升至排卵前后（最易受孕时间）的峰值，然后在排卵后期降至低水平。统计上的挑战在于检测这种上升（标志着潜在生育能力的开始）以及随后的下降。所考虑的分析方法包括阈值法、贝叶斯变化点模型，尤其是累积和（cusum）技术，该技术既易于应用和理解，又很有效。第二个领域包括分析和解释可育期临床研究数据的适当方法，特别是在所谓的自然计划生育（NFP）中，女性通常会观察多个潜在生育能力指标。此类研究通常试图确定可育期标志物之间的时间关系，并与标准的“定义”阶段（例如，从促黄体生成素峰值前三天到峰值后两天的时间段）相比，检验不同标志物组合在界定可育时间方面的成功率。第三个领域是评估周期中特定日子受孕的概率，这对于理解可育期及其在NFP中的应用至关重要。直接估计此类概率不切实际；相反，必须借助对专门构建模型的参数进行最大似然估计。文中描述了合适的模型。最后，讨论了针对NFP症状体温法中使用的可育期标志物开展关于受孕概率的新前瞻性研究的必要性。
