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Researchers predict IVF success from previous cycles

26 July 2010

By Dr Charlotte Maden

Appeared in BioNews 568

A mathematical model for predicting a couple's chances of a successful pregnancy by IVF after one failed attempt has been developed by US researchers. The model is 1000 times more accurate at predicting a positive outcome than standard methods, which are mainly based on a woman's age. The model may help clinics give more personalised and reliable advice to couples.

In the new study, Prajna Banerjee and colleagues at California's Stanford University looked at existing data collected on the outcomes of over 1600 first-time IVF cycles.

The researchers developed a predictive model for assessing whether a second IVF treatment would lead to a live birth based on 52 clinical characteristics for each couple. These included hormone levels, the number of embryos created from eggs and sperm and how fast they developed, as well as the woman's age and body mass index. They validated their model against a second dataset from more than 600 cycles of IVF.

The most important factor predicting success after the second cycle is the rate the embryos developed during the first cycle of IVF. The researchers found this was four times more important than the woman's age. Dr Mylene Yao, assistant professor of obstetrics and gynaecology at Stanford and lead author of the study, said: 'while age is a major driving force towards decreased fertility, it does not have the highest importance once you have the embryo data'.

The team hope their approach will be used in IVF clinics to provide a more accurate and personalised estimate of birth probabilities in second cycles of IVF. This will help each couple decide whether to continue with IVF after a failed first attempt. 'Understanding their probability of having a live birth, based on their very own clinical data, may serve to support that decision', says Dr Yao.

Since the model is based on data from first cycles, however, it could not be used to predict initial IVF success.

Dr Allan Pacey, senior lecturer at the University of Sheffield and fertility expert, told the BBC: 'to have universal appeal the model must work well in lots of different clinics. IVF is not an exact science, so we've got to be careful not to give people false hope'.

The study was published last week in the journal Proceedings of the National Academy of Sciences.

SOURCES & REFERENCES
Better way of predicting IVF success
Guardian | 20 July 2010
 
PNAS | 16 July 2010
 
Test predicts IVF success levels
Press Association | 19 July 2010
 
BBC News | 19 July 2010
 
New Scientist | 21 July 2010
 

RELATED ARTICLES FROM THE BIONEWS ARCHIVE

11 October 2010 - by Dr Lux Fatimathas 
US researchers have developed a means to predict which human embryos produced through IVF are most likely to result in healthy births. Researchers filmed 242 one-cell embryos and predicted, with more than 93 percent accuracy, those that would survive up to five days. These findings may improve the success rate of IVF....
20 September 2010 - by Gozde Zorlu 
Higher fertilisation rates have been found in women undergoing IVF in spring, according to new research presented at the World Congress of Fertility and Sterility last week...

19 July 2010 - by Sarah Pritchard 
Women given acupuncture during IVF treatment are no more likely to become pregnant than their counterparts who undergo needle stimulation to body areas not used in acupuncture, a US study has shown...
05 July 2010 - by Rosemary Paxman 
The National Institute for Health and Clinical Excellence (NICE) is considering lifting its age limit for free IVF on the National Health Service (NHS), as part of a full review of its guidelines. Instead, women would be offered free IVF on the NHS if they had enough viable eggs...
19 April 2010 - by Ruth Pidsley 
A team of researchers at Newcastle University in the UK has been successful in attempts to transfer genetic material from one newly fertilised human egg to another without carrying over the egg's mitochondria (the energy-producing structures of a cell)...

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