Gonadotrophins or clomiphene citrate in couples with unexplained infertility undergoing intrauterine insemination: a cost-effectiveness analysis.

RESEARCH QUESTION: What is the cost-effectiveness of gonadotrophins compared with clomiphene citrate in couples with unexplained subfertility undergoing intrauterine insemination (IUI) with ovarian stimulation under strict cancellation criteria? DESIGN: A cost-effectiveness analysis alongside a randomized controlled trial (RCT). Between July 2013 and March 2016, 738 couples were randomized to gonadotrophins (369) or clomiphene citrate (369) in a multicentre RCT in the Netherlands. The direct medical costs of both strategies were compared. Direct medical costs included costs of medication, cycle monitoring, insemination and, if applicable, pregnancy monitoring. Non-parametric bootstrap resampling was used to investigate the effect of uncertainty in estimates. The cost-effectiveness analysis was performed according to intention-to-treat. The incremental cost-effectiveness ratio (ICER) between gonadotrophins and clomiphene citrate for ongoing pregnancy and live birth was assessed. RESULTS: The mean costs per couple were €1534 for gonadotrophins and €1067 for clomiphene citrate (mean difference of €468; 95% confidence interval [CI] €464-472). As ongoing pregnancy rates were 31% in women allocated to gonadotrophins and 26% in women allocated to clomiphene citrate (relative risk 1.16, 95% CI 0.93-1.47), the ICER was €21,804 (95% CI €11,628-31,980) per additional ongoing pregnancy with gonadotrophins and €17,044 (95% CI €8998-25,090) per additional live birth with gonadotrophins. CONCLUSIONS: Gonadotrophins are more expensive compared with clomiphene citrate in couples with unexplained subfertility undergoing IUI with adherence to strict cancellation criteria, without being significantly more effective.

The INeS study: prevention of multiple pregnancies: a randomised controlled trial comparing IUI COH versus IVF e SET versus MNC IVF in couples with unexplained or mild male subfertility.

BACKGROUND: Multiple pregnancies are high risk pregnancies with higher chances of maternal and neonatal mortality and morbidity. In the past decades the number of multiple pregnancies has increased. This trend is partly due to the fact that women start family planning at an increased age, but also due to the increased use of ART.Couples with unexplained or mild male subfertility generally receive intrauterine insemination IUI with controlled hormonal stimulation (IUI COH). The cumulative pregnancy rate is 40%, with a 10% multiple pregnancy rate.This study aims to reveal whether alternative treatments such as IVF elective Single Embryo Transfer (IVF e SET) or Modified Natural Cycle IVF (MNC IVF) can reduce the number of multiple pregnancy rates, but uphold similar pregnancy rates as IUI COH in couples with mild male or unexplained subfertility. Secondly, the aim is to perform a cost effective analyses and assess treatment preference of these couples. METHODS/DESIGN: We plan a multicentre randomised controlled clinical trial in the Netherlands comparing six cycles of intra-uterine insemination with controlled ovarian hyperstimulation or six cycles of Modified Natural Cycle (MNC) IVF or three cycles with IVF-elective Single Embryo Transfer (eSET) plus cryo-cycles within a time frame of 12 months.Couples with unexplained subfertility or mild male subfertility and a poor prognosis for treatment independent pregnancy will be included. Women with anovulatory cycles, severe endometriosis, double sided tubal pathology or serious endocrine illness will be excluded.Our primary outcome is the birth of a healthy singleton. Secondary outcomes are multiple pregnancy, treatment costs, and patient experiences in each treatment arm. The analysis will be performed according tot the intention to treat principle. We will test for non-inferiority of the three arms with respect to live birth. As we accept a 12.5% loss in pregnancy rate in one of the two IVF arms to prevent multiple pregnancies, we need 200 couples per arm (600 couples in total). DISCUSSION: Determining the safest and most cost-effective treatment will ensure optimal chances of pregnancy for subfertile couples with substantially diminished perinatal and maternal complications. Should patients find the most cost-effective treatment acceptable or even preferable, this could imply the need for a world wide shift in the primary treatment. TRIAL REGISTRATION: Current Controlled Trials ISRCTN 52843371.

A prediction model for ongoing pregnancy after in vitro fertilization in couples with male subfertility.

OBJECTIVE: To assess the predictive capacity of male and female characteristics on in vitro fertilization (IVF) outcome in couples with male subfertility and to construct an IVF prediction model. STUDY DESIGN: We performed a cohort study including all couples with male subfertility undergoing IVF. The main outcome measure was an ongoing pregnancy after IVF. The baseline characteristics from a couple including parameters of the semen-analysis were included in a univariable and multivariable analysis to construct a prediction model (model I). The addition of antisperm antibodies (ASA) and post-wash total motile count (TMC) to models I, II and III, respectively, were analyzed. RESULTS: We included 275 couples with male subfertility who underwent 473 IVF cycles with an ongoing pregnancy rate of 19% per cycle. A prediction model containing female age, secondary subfertility, percentage progressively motile sperm, percentage sperm with normal morphology, prewash total motile sperm count, bilateral tubal pathology, history of intrauterine insemination and cycle number was constructed (model I). Prediction with model I resulted in the selection of 95 couples, of whom 55 conceived (pregnancy rate of 28% per cycle). Use of the model with n ASA (Model II) resulted in the selection of 79 couples, of whom still 55 conceived (30% per cycle). CONCLUSION: In couples with male subfertility, the use of a prediction model including ASA improves the efficiency of IVF.

Patients' preferences for intrauterine insemination or in-vitro fertilization.

Patients' preferences for intrauterine insemination (IUI) relative to IVF were assessed using trade-off interviews, and the number of IUI cycles they would undergo before changing to IVF. A total of 73 couples undergoing IUI with a total of 111 interviews were included. Scenarios were offered where pregnancy chance after IUI was varied against a fixed pregnancy rate after IVF. The impact of multiple pregnancy risk on the couple's preference was also investigated. Interviews were held before starting IUI, after three or four IUI cycles and after six IUI cycles. With decreasing probability of ongoing pregnancy after IUI, an increasing number of couples switched their preference from IUI to IVF. This switch occurred after six cycles at a significantly higher (P = 0.01) mean cumulative pregnancy rate (53%) compared with other groups (31%). With increasing risk of multiple pregnancy, preference for IUI declined only slightly, with mean risks of 73, 78 and 83% of a multiple pregnancy for the three groups respectively. In conclusion, at baseline and after three cycles of IUI the majority of couples undergoing IUI preferred continuation of IUI over IVF. A clear shift in preference towards IVF occurred after six cycles. Risk of multiple pregnancy did not affect preference for IUI with ovarian stimulation.

IUI in male subfertility: are we able to select the proper patients?

There is at this time no indication as to which semen parameters from the fertility work-up discriminate between couples with male subfertility who will and will not benefit from intrauterine insemination (IUI). This study evaluated the predictive capacity of semen parameters (both pre- and post-wash) and antisperm antibodies (ASA) obtained during the fertility workup on IUI outcome in couples with male subfertility in a retrospective cohort study. It included 290 couples, who underwent 722 IUI cycles. The overall ongoing pregnancy rate was 9% per cycle. Model I, with female age, duration of subfertility, secondary subfertility, the presence of anovulation, cervical hostility and cycle number had an area under the curve (AUC) of 0.59. Adding the presence of ASA to this model improved the AUC to 0.65 (model II). Further addition of the post-wash total motile count (TMC) to the model with ASA (model III) improved the AUC to 0.67. Using the models to exclude couples from IUI due to low expected pregnancy rates would increase the pregnancy rate to 11% per cycle with model I, and to 14% per cycle for model II and for model III. In conclusion, in the selection of patients with male subfertility for IUI, the use of prediction models including ASA can increase the efficiency of IUI.

Performance of the postwash total motile sperm count as a predictor of pregnancy at the time of intrauterine insemination: a meta-analysis.

OBJECTIVE: To assess the performance and clinical value of the postwash total motile sperm count (postwash TMC) as a test to predict intrauterine insemination (IUI) outcome. DESIGN: Meta-analysis of diagnostic tests. SETTING: Tertiary fertility center. PATIENT(S): Patients undergoing IUI. INTERVENTION(S): None. RESULT(S): We detected 16 studies that reported on postwash TMC at insemination and IUI outcome. Summary receiver operating characteristics (ROC) curves indicated a reasonable predictive performance toward IUI outcome, and, at cut-off levels between 0.8 to 5 million motile spermatozoa, the postwash TMC provided a substantial discriminative performance. At these cut-off levels, the specificity of the postwash TMC, defined as the ability to predict failure to become pregnant, was as high as 100%; the sensitivity of the test, defined as the ability to predict pregnancy, was limited. CONCLUSION(S): The postwash TMC at insemination could potentially be used in counseling patients for either IUI or IVF. However, to enable patient counseling before the start of treatment, further studies are needed to establish the accuracy of a postwash TMC during the fertility workup rather than at insemination.

Use of the total motile sperm count to predict total fertilization failure in in vitro fertilization.

OBJECTIVE: To evaluate the capacity of baseline characteristics and total motile sperm count (TMC) to predict total fertilization failure (TFF) in patients undergoing IVF. DESIGN: Retrospective cohort study. SETTING: University hospital. PATIENT(S): Eight hundred ninety-two couples with a total of 1,569 consecutive IVF cycles. INTERVENTION(S): Prewash and postwash TMC during fertility workup and at the time of ovum pickup (OPU). MAIN OUTCOME MEASURE(S): Analysis of logistic regression and the receiver operating characteristic curve were used to determine which variables could be used to predict TFF. RESULT(S): The area under the curve (AUC) for prewash TMC during fertility workup was 0.72, similar to a combination of pre- and postwash TMC. At the time of OPU, both pre- and postwash TMC had an AUC of 0.73. A model based on selected baseline characteristics (male age, number of IVF cycles, indication for IVF, and prewash TMC during fertility workup) had an AUC of 0.75. A model at the time of OPU, including the number of oocytes, had an AUC of 0.80. CONCLUSION(S): The use of both models, one before start of the IVF cycle and one at the time of OPU, allows an accurate prediction of the chance of TFF and is useful in counseling patients on whether to opt for IVF or ICSI.