Eijkemans M J C, Habbema J D F, Fauser B C J M
Department of Public Health, Erasmus Medical Center, Rotterdam, The Netherlands.
Semin Reprod Med. 2003 Feb;21(1):39-47. doi: 10.1055/s-2003-39993.
The standard first-line treatment for normogonadotropic anovulatory infertile patients [referred to as World Health Organization group 2 (WHO 2)] is ovulation induction using clomiphene citrate (CC) in incremental doses. Twenty to 25% of women show clomiphene-resistant anovulation (CRA), that is, they remain anovulatory even after multiple attempts with increased doses of CC. About 50% of the ovulatory CC patients conceive within six CC-induced cycles. Given the heterogeneous nature of the group, the individual prognosis (i.e., the chance of success) will vary considerably between patients. In the event an individual prognosis of each patient would be available before the start of the treatment, the overall efficiency of ovulation induction could be improved. Prognostic evidence at an individual level should use multiple patient variables, including results from previous treatments (if any). When variables are interdependent, a statistical model can be used to relate individual characteristics with the predicted outcome. Such a model will provide estimates of prognosis for individualized patient profiles, allowing new patients to profit from the experience of the cohort of previous patients used to build the model. This paper discusses the prediction of time to pregnancy following induction of ovulation with CC. This prediction was broken down in two steps, leading to two separate prognostic models. The first model predicts an intermediate outcome, the chance that the patient will be CRA (i.e., no ovulation in response to CC medication); the second model predicts the final outcome (time until pregnancy) in women who do ovulate. The CRA model was based on a prospective cohort study of 201 patients with normogonadotropic oligoamenorrheic infertility, 45 of whom were CRA (22%). It contained four predictor variables all related to the diagnosis of PCOS within the group of WHO 2: Increased free androgen index (FAI; hyperandrogenemia), elevated body mass index (BMI; obesity), greater mean ovarian volume (as an ultrasound feature of polycystic ovaries), and amenorrhea were all predictive for CRA. The second model was based on the non-CRA patients and contained two prognostic variables: increased age and oligomenorrhea were predictive for longer time to pregnancy after first ovulation with CC. Using the example of the prediction of time to pregnancy following induction of ovulation with CC, we present and discuss characteristics of good prognostic evidence for clinical use, focusing on study design, statistical analysis, evaluation, and presentation of results.
对于促性腺激素正常的无排卵性不孕患者(即世界卫生组织分类中的2组患者,简称WHO 2),标准的一线治疗方法是使用递增剂量的枸橼酸氯米芬(CC)诱导排卵。20%至25%的女性表现为氯米芬抵抗性无排卵(CRA),即即便多次尝试增加CC剂量,她们仍无法排卵。约50%的能对CC产生排卵反应的患者会在6个由CC诱导的周期内受孕。鉴于该组患者情况各异,个体预后(即成功几率)在患者之间会有很大差异。如果在治疗开始前就能得知每位患者的个体预后,那么诱导排卵的总体效率将会提高。个体水平的预后证据应采用多个患者变量,包括既往治疗结果(如有)。当变量相互依存时,可使用统计模型将个体特征与预测结果关联起来。这样的模型将为个体化患者概况提供预后估计,使新患者能够从用于构建模型的既往患者队列的经验中获益。本文讨论了用CC诱导排卵后至妊娠时间的预测。该预测分为两个步骤,得出两个独立的预后模型。第一个模型预测一个中间结果,即患者出现CRA的几率(即对CC药物无排卵反应);第二个模型预测有排卵的女性的最终结果(直至妊娠的时间)。CRA模型基于一项对201例促性腺激素正常的稀发月经性不孕患者的前瞻性队列研究,其中45例为CRA患者(22%)。该模型包含四个预测变量,均与WHO 2组内的多囊卵巢综合征(PCOS)诊断相关:游离雄激素指数升高(FAI;高雄激素血症)、体重指数升高(BMI;肥胖)、平均卵巢体积增大(作为多囊卵巢的超声特征)以及闭经均为CRA的预测因素。第二个模型基于非CRA患者,包含两个预后变量:年龄增加和月经稀发是CC首次诱导排卵后至妊娠时间延长的预测因素。我们以用CC诱导排卵后至妊娠时间预测为例,展示并讨论临床使用的良好预后证据的特征,重点关注研究设计、统计分析、评估及结果呈现。