STUDY QUESTION: Can mixture survival models help distinguish infertility from subfertility in couples with an unexplained unfulfilled child wish? SUMMARY ANSWER: Mixture models estimated that 47% of the couples were infertile; female age and previous pregnancy were significantly related to infertility, whereas duration of child wish was associated with a longer time to pregnancy for subfertile couples. WHAT IS KNOWN ALREADY: To differentiate between couples who require assisted conception and couples who still have good chances of natural, i.e. unassisted, conception, several prediction models of natural conception have been developed. Prognostic factors in these models are usually assessed by Cox proportional hazard models that cannot differentiate between couples with an unfulfilled child wish who are subfertile, i.e. have reduced ability to conceive naturally, and couples who are really infertile, i.e. are completely unable to conceive naturally. We evaluated whether a mixture survival model can make such a distinction. STUDY DESIGN, SIZE, DURATION: Consecutive couples presenting at the fertility clinics of 38 centres in the Netherlands between January 2002 and February 2004 joined a prospective cohort study. Of the 7860 couples in the cohort, 3917 couples met our inclusion criteria. The median follow-up was 219 days, with a maximum of 5 years. PARTICIPANTS, SETTING, METHODS: Couples had to present with an unexplained cause of an unfulfilled child wish. A mixture model was used to estimate the proportion of couples who were infertile and the time to pregnancy for the subfertile couples. MAIN RESULTS AND THE ROLE OF CHANCE: During the follow-up, 794 couples conceived naturally. The mixture model estimated that 47% [95% confidence interval (CI): 33-56%] of couples were infertile, despite the absence of objective factors indicating a cause for infertility. Of the evaluated prognostic factors, female age, duration of child wish, previous pregnancy, semen quality, BMI and cycle length, female age [odds ratio (OR): 1.11, 95% CI: 1.03-1.19] and previous pregnancy (0.22, 95% CI: 0.07-0.67) were significant predictors of infertility. Among subfertile couples, a longer duration of a child wish (FFR: 0.72, 95% CI: 0.61-0.85) was a significant prognostic factor for time to pregnancy. In the Cox models, all variables except BMI were significant predictors of time to pregnancy. LIMITATIONS, REASONS FOR CAUTION: The mixture model had limited power due to a low number of couples at the end of the follow-up period. Mixture model analyses on external, long-term follow-up data are necessary to validate our results. WIDER IMPLICATIONS OF THE FINDINGS: Mixture models could be a useful tool in selecting couples who require assisted reproductive technology because the effects of prognostic factors can be subdivided into effects on the fraction of infertile couples and effects on the time to pregnancy for subfertile couples, which is not possible in conventional models. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by grant 945/12/002 from ZonMw, the Netherlands Organization for Health Research and Development, The Hague, the Netherlands.
STUDY QUESTION: Can mixture survival models help distinguish infertility from subfertility in couples with an unexplained unfulfilled child wish? SUMMARY ANSWER: Mixture models estimated that 47% of the couples were infertile; female age and previous pregnancy were significantly related to infertility, whereas duration of child wish was associated with a longer time to pregnancy for subfertile couples. WHAT IS KNOWN ALREADY: To differentiate between couples who require assisted conception and couples who still have good chances of natural, i.e. unassisted, conception, several prediction models of natural conception have been developed. Prognostic factors in these models are usually assessed by Cox proportional hazard models that cannot differentiate between couples with an unfulfilled child wish who are subfertile, i.e. have reduced ability to conceive naturally, and couples who are really infertile, i.e. are completely unable to conceive naturally. We evaluated whether a mixture survival model can make such a distinction. STUDY DESIGN, SIZE, DURATION: Consecutive couples presenting at the fertility clinics of 38 centres in the Netherlands between January 2002 and February 2004 joined a prospective cohort study. Of the 7860 couples in the cohort, 3917 couples met our inclusion criteria. The median follow-up was 219 days, with a maximum of 5 years. PARTICIPANTS, SETTING, METHODS: Couples had to present with an unexplained cause of an unfulfilled child wish. A mixture model was used to estimate the proportion of couples who were infertile and the time to pregnancy for the subfertile couples. MAIN RESULTS AND THE ROLE OF CHANCE: During the follow-up, 794 couples conceived naturally. The mixture model estimated that 47% [95% confidence interval (CI): 33-56%] of couples were infertile, despite the absence of objective factors indicating a cause for infertility. Of the evaluated prognostic factors, female age, duration of child wish, previous pregnancy, semen quality, BMI and cycle length, female age [odds ratio (OR): 1.11, 95% CI: 1.03-1.19] and previous pregnancy (0.22, 95% CI: 0.07-0.67) were significant predictors of infertility. Among subfertile couples, a longer duration of a child wish (FFR: 0.72, 95% CI: 0.61-0.85) was a significant prognostic factor for time to pregnancy. In the Cox models, all variables except BMI were significant predictors of time to pregnancy. LIMITATIONS, REASONS FOR CAUTION: The mixture model had limited power due to a low number of couples at the end of the follow-up period. Mixture model analyses on external, long-term follow-up data are necessary to validate our results. WIDER IMPLICATIONS OF THE FINDINGS: Mixture models could be a useful tool in selecting couples who require assisted reproductive technology because the effects of prognostic factors can be subdivided into effects on the fraction of infertile couples and effects on the time to pregnancy for subfertile couples, which is not possible in conventional models. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by grant 945/12/002 from ZonMw, the Netherlands Organization for Health Research and Development, The Hague, the Netherlands.