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Ovarian stimulation is applied in the clinic to restore mono-ovulatory cycles in anovulatory women (ovulation induction) or to induce the development of multiple dominant follicles for assisted reproduction. Ovarian response is the endocrine and follicular reaction of the ovaries to stimulation. Achieving an appropriate ovarian response to anti-estrogens or exogenous gonadotrophins is central to ovulation induction and ovarian stimulation protocols. However, achieving an adequate response, without cycle cancellation or adverse events related to under- or over-stimulation, is complicated by high intra- and inter-individual variability. To predict each patient's ovarian response to medication for ovarian stimulation and to individualize the starting dose of exogenous gonadotrophin or the need for exogenous luteinizing hormone, various clinical, endocrine, ovarian ultrasonographic and genetic characteristics have been explored. Some of these features have been incorporated into prediction models. In this review, the methodology behind predictive factors and prediction models and their potential clinical applicability across ovulation induction and ovarian stimulation are explored.

Overweight and obesity are an epidemic in Western society, and have a strong impact on fertility. We studied the consequences of overweight and obesity with respect to fecundity, costs of fertility treatment and pregnancy outcome in subfertile women.We searched the literature for systematic reviews and large studies reporting on the effect of weight on both fecundity and pregnancy outcome in subfertile women. We collected data on costs of treatment with ovulation induction, intrauterine insemination and in vitro fertilization, as well as costs of pregnancy complications. We calculated, for ovulatory and anovulatory women separately, the number of expected pregnancies, complications and costs in a hypothetical cohort of 1000 normal weight, overweight and obese women each.In our hypothetical cohort of 1000 women, compared with women with normal weight, live birth was decreased by 14 and 15% (from 806 live births to 692 and 687 live births) in overweight and obese anovulatory women, respectively, for ovulatory women it was decreased by 22 and 24% (from 698 live births to 546 and 531 live births), respectively. These outcomes were associated with an increase in the number of complications and associated costs leading to cost per live birth in anovulatory overweight and obese women were 54 and 100% higher than their normal weight counterparts, for ovulatory women they were 44 and 70% higher, respectively.Overweight and obese subfertile women have a reduced probability of successful fertility treatment and their pregnancies are associated with more complications and higher costs.

Ovarian stimulation is applied in the clinic to restore mono-ovulatory cycles in anovulatory women (ovulation induction) or to induce the development of multiple dominant follicles for assisted reproduction. Ovarian response is the endocrine and follicular reaction of the ovaries to stimulation. Achieving an appropriate ovarian response to anti-estrogens or exogenous gonadotrophins is central to ovulation induction and ovarian stimulation protocols. However, achieving an adequate response, without cycle cancellation or adverse events related to under- or over-stimulation, is complicated by high intra- and inter-individual variability. To predict each patient's ovarian response to medication for ovarian stimulation and to individualize the starting dose of exogenous gonadotrophin or the need for exogenous luteinizing hormone, various clinical, endocrine, ovarian ultrasonographic and genetic characteristics have been explored. Some of these features have been incorporated into prediction models. In this review, the methodology behind predictive factors and prediction models and their potential clinical applicability across ovulation induction and ovarian stimulation are explored.

We are currently witnessing a major shift in emphasis in clinical medicine from the “one size fits all” approach toward more patient-tailored treatment algorithms. Slowly, this approach is also being developed in infertilitytreatment,especiallyinrelationtoovarianstimulation (i.e. the treatment of anovulatory infertility and ovarian hyperstimulation for assisted reproductive technologies) (1). Improvements are much needed in this area because ovarian stimulation is still far from “controlled,” and intense monitoring of ovarian response is required to achieve a reasonable balance between efficacy and safety. Current efforts aim to adjust treatments (either dosing or the preferred drug) based on initial patient screening characteristics.Thisapproachmayeventuallyresultinimproved efficacy, safety, and health economics (2). The usual approach is to study whether initial patient characteristics are associated with outcomes of standard treatment. Initial findings should subsequently be validated in an independent data set. Thereafter, it should be prospectively assessed whether altered approaches in selected patient categories indeed result in improved outcomes compared with the standard of care. Individualized dosing of ovarian hyperstimulation based on predictive factors has