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Type: Journal article
Title: Prioritising IVF treatment in the post-COVID 19 era: a predictive modelling study based on UK national data
Author: Bhattacharya, S.
Maheshwari, A.
Ratna, M.B.
van Eekelen, R.
Mol, B.W.
McLernon, D.J.
Citation: Human Reproduction, 2021; 36(3):666-675
Publisher: Oxford University Press
Issue Date: 2021
ISSN: 0268-1161
Statement of
Siladitya Bhattacharya, Abha Maheshwari, Mariam Begum Ratna, Rik van Eekelen, Ben Willem Mol, and David J. McLernon
Abstract: Study Question: Can we use prediction modelling to estimate the impact of coronavirus disease 2019 (COVID 19) related delay in starting IVF or ICSI in different groups of women? Summary Answer: Yes, using a combination of three different models we can predict the impact of delaying access to treatment by 6 and 12 months on the probability of conception leading to live birth in women of different age groups with different categories of infertility. What Is Known Already: Increased age and duration of infertility can prejudice the chances of success following IVF, but couples with unexplained infertility have a chance of conceiving naturally without treatment whilst waiting for IVF. The worldwide suspension of IVF could lead to worse outcomes in couples awaiting treatment, but it is unclear to what extent this could affect individual couples based on age and cause of infertility. Study Design, Size, Duration: A population based cohort study based on national data from all licensed clinics in the UK obtained from the Human Fertilisation and Embryology Authority Register. Linked data from 9589 women who underwent their first IVF or ICSI treatment in 2017 and consented to the use of their data for research were used to predict livebirth numbers. Participants/Materials, Setting, Methods: Three prediction models were used to estimate the chances of livebirth associated with immediate treatment versus a delay of 6 and 12 months in couples about to embark on IVF or ICSI. Main Results and Role of Chance: We estimated that a 6-month delay would reduce livebirths by 0.4%, 2.4%, 5.7%, 9.5% and 11.8% in women aged <30, 30-35, 36-37, 38-39 and 40-42 years, respectively, while corresponding values associated with a delay of 12 months were 0.9%, 4.9%, 11.9%, 18.8% and 22.4%, respectively. In women with known causes of infertility, worst case (best case) predicted chances of livebirth after a delay of 6 months in women aged <30, 30-35, 36-37, 38-39 and 40-42 years varied between 31.6% (35.0%), 29.0% (31.6%), 23.1% (25.2%), 17.2% (19.4%) and 10.3% (12.3%) for tubal infertility and 34.3% (39.2%), 31.6% (35.3%) 25.2%(28.5%) 18.3% (21.3%), and 11.3% (14.1%) for male factor infertility. The corresponding values in those treated immediately were 31.7%, 29.8%, 24.5%, 19.0% and 11.7% for tubal factor and 34.4%, 32.4%, 26.7%, 20.2% and 12.8% in male factor infertility. In women with unexplained infertility the predicted chances of livebirth after a delay of 6 months followed by one complete IVF cycle were 41.0%, 36.6%, 29.4%, 22.4% and 15.1% in women aged <30, 30-35, 36-37, 38-39 and 40-42 years, respectively, compared to 34.9%, 32.5%, 26.9%, 20.7% and 13.2% in similar groups of women treated without any delay. The additional waiting period, which provided more time for spontaneous conception, was predicted to increase the relative number of babies born by 17.5%, 12.6%, 9.1%, 8.4% and 13.8%, in women aged <30, 30-35, 36-37, 38-39 and 40-42 years, respectively. A 12-month delay showed a similar pattern in all subgroups. Limitations, Reasons for Caution: Major sources of uncertainty include the use of prediction models generated in different populations and the need for a number of assumptions. Although the models are validated and the bases for the assumptions are robust, it is impossible to eliminate the possibility of imprecision in our predictions. Therefore, our predicted live birth rates need to be validated in prospective studies to confirm their accuracy. Wider Implications of the Findings: A delay in starting IVF reduces success rates in all couples. For the first time, we have shown that while this results in fewer babies in older women and those with a known cause of infertility, it has a less detrimental effect on couples with unexplained infertility, some of whom conceive naturally whilst waiting for treatment. Post COVID 19, clinics planning a phased return to normal clinical services should prioritise older women and those with a known cause of infertility.
Keywords: COVID 19; prediction models; live birth; unexplained infertility; infertility; IVF
Rights: © The Author(s) 2020. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please email:
DOI: 10.1093/humrep/deaa339
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Obstetrics and Gynaecology publications

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