Predicting live birth chances for women with multiple consecutive failing IVF cycles: a simple and accurate prediction f
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RESEARCH
Open Access
Predicting live birth chances for women with multiple consecutive failing IVF cycles: a simple and accurate prediction for routine medical practice Géraldine Porcu1, Philippe Lehert2,3*, Carolina Colella4 and Claude Giorgetti1
Abstract Background: Women having experienced several consecutive failing IVF cycles constitute a critical and particular subset of patients, for which growing perception of irremediable failure, increasing costs and IVF treatment related risks necessitate appropriate decision making when starting or not a new cycle. Predicting chances of LB might constitute a useful tool for discussion between the patient and the clinician. Our essential objective was to dispose of a simple and accurate prediction model for use in routine medical practice. The currently available predictive models applicable to general populations cannot be considered as accurate enough for this purpose. Methods: Patients with at least four consecutive Failing cycles (CFCs) were selected. We constructed a predictive model of LB occurrence during the last cycle, by using a stepwise logistic regression, using all the baseline patient characteristics and intermediate stage variables during the four first cycles. Results: On as set of 151 patients, we identified five determinant predictors: the number of previous cycles with at least one gestational sac (NGS), the mean number of good-quality embryos, age, male infertility (MI) aetiology and basal FSH. Our model was characterized by a much higher discrimination as the existing models (C-statistics=0.76), and an excellent calibration. Conclusions: Couples having experienced multiple IVF failures need precise and appropriate information to decide to resume or interrupt their fertility project. Our essential objective was to dispose of a simple and accurate prediction model to allow a routine practice use. Our model is adapted to this purpose: It is very simple, combines five easily collected variables in a short calculation; it is more accurate than existing models, with a fair discrimination and a well calibrated prediction. Keywords: IVF, ICSI, Predictive model
Background Methods to predict chances of live birth (LB) have recently attracted attention in assisted reproductive technology (ART) research. As ART techniques have potential side effects and are costly, before deciding on IVF (in vitro fertilisation), it remains essential to estimate the chances of success. In particular, it has been suggested that ART should only be used
* Correspondence: [email protected] 2 Faculty of Economics, University of Louvain, Mons B-7000, Belgium 3 Faculty of Medicine, University of Melbourne, Melbourne 3010, Australia Full list of author information is available at the end of the article
for couples with a prognosis that significantly exceeds the expected success rate in the absence of treatment [1]. The complex multi-factorial genesis of infertility prevents clinicians from offering an accurate, reliable prognosis [2]. Hence, researchers have developed pred
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