Predicting the chances of having a baby with or without treatment at different time points in couples with unexplained subfertility

McLernon, David J.; Lee, A. J.; Maheshwari, Abha; Eekelen, Rik van; Geloven, Nan van; Putter, Hein; Eijkemans, Marinus J.C.; Steeg, Jan Willem van der; Veen, Fulco van der; Mol, Ben Willem J.; Bhattacharya, Siladitya

doi:10.1093/humrep/dez049

Cited by 19 publications

(14 citation statements)

References 40 publications

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“…Elucidating impacts of volitional determinants of fecundability would be useful for those trying to conceive their child, because, unlike biological age, these factors can be modified by themselves. Efforts have been made to predict probability of giving birth using prediction models that targeted couples with unexplained subfertility (e.g., [21,22]). The present results showing heterogeneous fecundability within an age group supports the idea that considering not only a couple's ages, but also other factors that can impact their fecundability is important to judge how long a couple should wait to conceive naturally and when they had better start fertility treatment.…”

Section: Discussionmentioning

confidence: 99%

“…Age-related changes in fertility and fecundity, the biological ability to reproduce, have been an interest to demographers, clinical doctors, and those trying to conceive their child. Age-specific marital fertility rates of natural fertility populations showed a common age pattern for women: it is highest for the ages 20-24 years and declines at higher ages, while the absolute values of fertility varied across populations [1] (p. 22), [2] (p. 54). The age-specific marital fertility observed in natural fertility populations are believed to reflect the age pattern of fecundity.…”

Section: Introductionmentioning

confidence: 97%

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Fecundability and Sterility by Age: Estimates Using Time to Pregnancy Data of Japanese Couples Trying to Conceive Their First Child with and without Fertility Treatment

Konishi

Kariya

Hamasaki

et al. 2021

IJERPH

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Fecundability, the probability of conception in a month or in a menstrual cycle, varies across and within age groups for both women and men. Fertility treatment has become common in a number of countries including Japan, but its impact on the age pattern of fecundability is unknown. By utilizing the previously collected data on time to pregnancy (TTP) of Japanese couples trying to conceive their first child, the present study aimed to estimate fecundability and sterility by women’s age and to assess how the estimates may differ by including or excluding assisted conceptions. Duration between discontinuing contraception and conception (including both natural and assisted) resulted in a live birth was called TTP-all, and the duration ending with natural conception was called TTP-natural. TTP-natural was censored when a participant received fertility consultation or treatment. A zero-inflated beta distribution model was used to estimate a proportion of sterile (zero probability of conception) and a distribution of fecundability for each age group. Parameters of the distribution were estimated using the maximum likelihood method. When TTP-all and TTP-natural were used, the sterile proportion of the whole sample was, respectively, 2% and 14%, and the median (interquartile range) of fecundability was, respectively, 0.10 (0.04, 0.19) and 0.11 (0.05, 0.19). The median (interquartile range) of fecundability was 0.18 (0.10, 0.29) for women aged 24 years or younger and 0.05 (0.02, 0.13) for 35–39 years old when TTP-all was used, and the estimates were quite similar with those based on TTP-natural: it was 0.18 (0.10, 0.29) for women aged 24 years or younger and 0.06 (0.00, 0.15) for 35–39 years old. Exclusion of assisted conceptions resulted in larger proportions of sterility, but it had little impact on median or interquartile ranges of fecundability estimates. Fecundability is overall lower at higher ages, while interquartile ranges are overlapping, suggesting that inter-individual variability of fecundability within an age group is as large as the variability across age groups.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Fecundability and Sterility by Age: Estimates Using Time to Pregnancy Data of Japanese Couples Trying to Conceive Their First Child with and without Fertility Treatment

Konishi

Kariya

Hamasaki

et al. 2021

IJERPH

View full text Add to dashboard Cite

show abstract

“…Interview volunteers were contacted sequentially until data saturation was reached in two age-stratified groups (18-30, and 31-40). Age-stratification was done in recognition that women below and above age 30 may experience fertility differently [15]. Following qualitative research convention, the intention was to conduct 20-30 interviews [19].…”

Section: Recruitmentmentioning

confidence: 99%

“…Existing fertility prediction models can predict conception chances at different time-points such as when starting IVF [14] and diagnosed with unexplained infertility [15], but are limited to specific infertile groups. Such models are mathematical equations that use characteristics, such as age, length of time trying to conceive, and pregnancy history, to predict a personalised conception chance.…”

Section: Introductionmentioning

confidence: 99%

Women’s perspectives on smartphone apps for fertility tracking and predicting conception: a mixed methods study

Blair

Morgan

McLernon

2021

The European Journal of Contraception & Reproductive Health

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Background: Women use fertility tracking apps (FTAs) for conception purposes, but user perspectives on FTA use for conception are largely unknown. In collaboration with SPD Clearblue, this study explored: how women trying to conceive use FTAs; women's knowledge of their conception chances; and women's feelings towards a potential natural conception prediction app (NCPA). Methods: A mixed methods design was used (online survey and phone interviews). Participants were women 18-40 years old actively trying to conceive. Results: The survey received 154 responses and 24 interviews were conducted. Thematic analysis of interviews found that women consider several factors before trying to conceive (ex. age, financial and job security, stability of relationship, etc.) and may adopt lifestyle and behaviour changes when trying (ex. increasing exercise, smoking cessation, diet changes, etc.). Survey results indicated that nearly all respondents were aware of FTAs (n ¼ 146, 94.8%), however, several other fertility and conception information sources were also used (ex. health care providers, online sources, family and friends, etc.). Nearly all respondents reported they would use an NCPA (n ¼ 153, 99.4%). During interviews women had positive feelings towards such an app due to it offering new and individualised information, but worried the app could provide upsetting information. Conclusion: This research elaborates on women's uses of and interest in FTAs. Stakeholders should use this research to reflect on current conception experiences and possibilities for improvement through development of an NCPA. Future research should seek opinions from a more diverse sample of women to inform the development of an inclusive NCPA.

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“…At the beginning of the stimulation, it could be too early to detect the pregnancy, which would only demonstrate itself near the end of the cycle. It is not unheard of to have fertility patients conceive spontaneously while awaiting IVF or after cycles, with most physicians having experienced such a situation [10,11]. In the least, consents of random start subjects should have such a possibility listed, and all subjects should have a serum beta-hCG level drawn.…”

mentioning

confidence: 99%

IVF stimulation in pregnancy: lessons to be learned with implications for the luteal phase start IVF cycle

Mamari

Son

Pansera

et al. 2020

J Assist Reprod Genet

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In vitro fertilization (IVF) has been widely used to treat infertile couples. Standardly, IVF protocols start stimulation in the early follicular phase [1]. Centers routinely perform ultrasound on cycle day 2 to 3 to evaluate the endometrial lining, rule out pregnancy, and verify a lack of functional ovarian cysts before starting controlled ovarian stimulation. However, the role of early follicular start is being questioned, with random and luteal phase stimulations being investigated, particularly in centers practicing freeze all protocols to favor implantation [1][2][3]. This is done for both convenience and in cancer patients desiring pre-chemotherapy fertility preservation, who must start urgently [4,5]. In a recent study, patients were divided into three groups based on menstrual cycle phase for commencement of stimulation: the conventional early follicular, late follicular phase, and luteal phase starts. All three groups were comparable in terms of the number of mature oocytes (MII), quantity of embryos and oocytes retrieved, implantation rates, and clinical pregnancy rates [2]. Clearly, a random start for IVF stimulation is interesting in that it will minimize time to initiate stimulation, particularly if the center will perform pre-implantation genetic testing type A or for implantation benefit, freeze all embryos, a trend, which is increasing, particularly in the USA.However, when luteal phase starts, one complication that may arise is that the patient could be unknowingly pregnant. The role of pregnancy on stimulation outcomes has not been investigated. However, we would anticipate that the body has mechanisms in place to prevent double fecundation at different time periods, which would result in two pregnancies of different gestational ages developing concurrently. The role of

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Predicting the chances of having a baby with or without treatment at different time points in couples with unexplained subfertility

Cited by 19 publications

References 40 publications

Fecundability and Sterility by Age: Estimates Using Time to Pregnancy Data of Japanese Couples Trying to Conceive Their First Child with and without Fertility Treatment

Fecundability and Sterility by Age: Estimates Using Time to Pregnancy Data of Japanese Couples Trying to Conceive Their First Child with and without Fertility Treatment

Women’s perspectives on smartphone apps for fertility tracking and predicting conception: a mixed methods study

IVF stimulation in pregnancy: lessons to be learned with implications for the luteal phase start IVF cycle

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