Estimation of the day-specific probabilities of conception: current state of the knowledge and the relevance for...

Conception, as defined by the fertilisation of an ovum by a sperm, marks the beginning of human development. Currently, a biomarker of conception is not available; as conception occurs shortly after ovulation, the latter can be used as a proxy for the time of conception. In the absence of serial ultrasound examinations, ovulation cannot be readily visualised leaving researchers to rely on proxy measures of ovulation that are subject to error. The most commonly used proxy measures include: charting basal body temperature, monitoring cervical mucus, and measuring urinary metabolites of oestradiol and luteinising hormone. Establishing the timing of the ovulation and the fertile window has practical utility in that it will assist couples in appropriately timing intercourse to achieve or avoid pregnancy. Identifying the likely day of conception is clinically relevant because it has the potential to facilitate more accurate pregnancy dating, thereby reducing the iatrogenic risks associated with uncertain gestation. Using data from prospective studies of couples attempting to conceive, several researchers have developed models for estimating the day-specific probabilities of conception. Elucidating these will allow researchers to more accurately estimate the day of conception, thus spawning research initiatives that will expand our current limited knowledge about the effect of exposures at critical periconceptional windows. While basal body temperature charting and cervical mucus monitoring have been used with success in field-based studies for many years, recent advances in science and technology have made it possible for women to get instant feedback regarding their daily fertility status by monitoring urinary metabolites of reproductive hormones in the privacy of their own homes. Not only are innovations such as luteinising hormone test kits and digital fertility monitors likely to increase study compliance and participation rates, they provide valuable prospective data that can be used in epidemiological research. Although we have made great strides in estimating the timing and length of the fertile window, more work is needed to elucidate the day-specific probabilities of conception using proxy measures of ovulation that are inherently subject to error. Modelling approaches that incorporate the use of multiple markers of ovulation offer great promise to fill these important data gaps.