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External validation and calibration of IVFpredict:A national prospective cohort study of 130,960 in vitro fertilisation Cycles

Smith, Andrew D. A. C.; Tilling, Kate; Lawlor, Debbie A.; Nelson, Scott M.

External validation and calibration of IVFpredict:A national prospective cohort study of 130,960 in vitro fertilisation Cycles Thumbnail


Kate Tilling

Debbie A. Lawlor

Scott M. Nelson


© 2015 Smith et al. Background Accurately predicting the probability of a live birth after in vitro fertilisation (IVF) is important for patients, healthcare providers and policy makers. Two prediction models (Templeton and IVFpredict) have been previously developed from UK data and are widely used internationally. The more recent of these, IVFpredict, was shown to have greater predictive power in the development dataset. The aim of this study was external validation of the two models and comparison of their predictive ability. Methods and Findings 130,960 IVF cycles undertaken in the UK in 2008-2010 were used to validate and compare the Templeton and IVFpredict models. Discriminatory power was calculated using the area under the receiver-operator curve and calibration assessed using a calibration plot and Hosmer-Lemeshow statistic. The scaled modified Brier score, with measures of reliability and resolution, were calculated to assess overall accuracy. Both models were compared after updating for current live birth rates to ensure that the average observed and predicted live birth rates were equal. The discriminative power of both methods was comparable: the area under the receiver-operator curve was 0.628 (95% confidence interval (CI): 0.625-0.631) for IVFpredict and 0.616 (95% CI: 0.613-0.620) for the Templeton model. IVFpredict had markedly better calibration and higher diagnostic accuracy, with calibration plot intercept of 0.040 (95% CI: 0.017-0.063) and slope of 0.932 (95% CI: 0.839 - 1.025) compared with 0.080 (95% CI: 0.044-0.117) and 1.419 (95% CI: 1.149-1.690) for the Templeton model. Both models underestimated the live birth rate, but this was particularly marked in the Templeton model. Updating the models to reflect improvements in live birth rates since the models were developed enhanced their performance, but IVFpredict remained superior. Conclusion External validation in a large population cohort confirms IVFpredict has superior discrimination and calibration for informing patients, clinicians and healthcare policy makers of the probability of live birth following IVF.

Journal Article Type Article
Acceptance Date Jan 30, 2015
Online Publication Date Apr 8, 2015
Publication Date Apr 8, 2015
Deposit Date Dec 2, 2015
Publicly Available Date Feb 19, 2016
Journal PLoS ONE
Electronic ISSN 1932-6203
Publisher Public Library of Science
Peer Reviewed Peer Reviewed
Volume 10
Issue 4
Article Number e0121357
Keywords IVF, in vitro fertilisation, infertility, birth rates
Public URL
Publisher URL
Contract Date Feb 19, 2016


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