Beware of the 'implantation rate'! Why the outcome parameter 'implantation rate' should be abandoned from infertility research.

Since the early days of IVF, great research efforts have been undertaken to improve the viability of in vitro generated embryos and to improve the selection of embryos from a given pool of embryos for preferential transfer to the uterus. With these efforts came the question of what outcome parameter can best objectively quantify the impact of such interventions. A commonly used outcome parameter in IVF studies is the ‘implantation rate’ (IR). The IR is calculated as [IR 1⁄4 ngestational sacs/ntransferred embryos, where ngestational sacs is the number of gestational sacs observed at vaginal ultrasound 3–5 weeks after transfer and ntransferred embryos is the number of transferred embryos]. This calculation can be performed per patient or aggregated per group of patients: very often the latter approach is chosen and methodological havoc is destined to follow. The distortion of data by the misuse of the IR typically becomes apparent in studies in which, systematically, fewer embryos are transferred in one of the study groups. In studies on embryo selection methods (such as preimplantation genetic screening, blastocyst culture or ‘morphokinetics’), the phenomenon of fewer embryos transferred in the study group comes naturally with the nature of the procedure, for example less embryos are classified as transferable after the intervention. In such a scenario, less embryos being transferred combined with calculating the aggregated IR per group of patients necessarily distort the data towards a higher IR with the intervention, as outlined herein in a hypothetical example. In Fig. 1, 2000 patients are randomized 1:1 to either the study or intervention group. In the study group, in addition to the intervention (in our example preimplantation-genetic-screening by comprehensive chromosome screening: PGS-CCS), an elective single embryo transfer (eSET) is performed, while in the control group a double embryo transfer (DET) is performed. In both groups, the same number of patients is receptive as an effect of randomization. However, the pregnancy rate is, necessarily, statistically significantly higher in the DET group owing to a higher number of embryos being transferred per patient (in ourexample55 versus 45%). Furthermore, in the DET group, necessarily, a higher multiple pregnancy rate is observed (in our example 24 versus 0%). While the null hypothesis may well be true in this scenario (e.g. PGS-CCS being totally ineffective), the ‘implantation rate’ is statistically significantly higher in the studygroup. However, the observation of a higher IR can already be explained by the fact alone, that double the number of embryos has been transferred in the control group, also to all the women with zero conception, and that all these embryos went to the denominator of the calculation of the ‘implantation rate’. In our example, pregnancy rate and IR thereby show divergent effect directions, while both are ‘highly statistically significantly (P , 0.00001)’ different between groups. The example in Fig. 1 is an exaggeration, but the confusion introduced by the IR to the published literature is a reality. For example, in a number of RCTs comparing eSET with DET, pregnancy rate and IR show divergent effect directions as in our example in Fig. 1 (Martikainen et al., 2001; Lukassen et al., 2005; Moustafa et al., 2008). However, that obviously does not allow the conclusion to be reached that the ‘implantation potential’ of an embryo is getting better if that embryo is transferred alone. Another, more pertinent, practical example of the distortion of data by misuse of the IR is a recently conducted study on PGS-CCS (Forman et al., 2013). This study has entered systematic reviews (Dahdouh et al., 2015a; Lee et al., 2015) and has been classified as ‘class I evidence’ of the effectiveness of PGS-CCS in increasing IR (Scott et al., 2014; Dahdouh et al., 2015b). Since it is clear that transferring less embryos per embryo transfer reduces the chance of pregnancy, the authors (Forman et al., 2013) hypothesized that the embryo selection method PGS-CCS could level out the chance of pregnancy even if a single embryo is transferred (eSET) as compared with a control group of patients who receive a DET without PGS-CCS. In a nutshell, the study reported that ongoing pregnancy rate is similar between groups and the multiple pregnancy rate is less in the eSET group, while ‘. there