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Evaluation of a proposed mixture model to specify the distributions of nuchal translucency measurements in antenatal screening for Down's syndrome.

Bestwick JP, Huttly WJ, Wald NJ - J Med Screen (2010)

Bottom Line: A mixture model of crown-rump length (CRL)-dependent and CRL-independent nuchal translucency (NT) measurements has been proposed for antenatal screening for Down's syndrome.Settings A routine antenatal screening programme for Down's syndrome comprising 104 affected and 22,284 unaffected pregnancies.Risk estimation was marginally (but not statistically significantly) more accurate using the standard MoM method.

View Article: PubMed Central - PubMed

Affiliation: Wolfson Institute of Preventive Medicine, Barts and the London Queen Marys School of Medicine and Dentistry, Charterhouse Square, London EC1M 6BQ, UK. j.p.bestwick@qmul.ac.uk

ABSTRACT

Objectives: A mixture model of crown-rump length (CRL)-dependent and CRL-independent nuchal translucency (NT) measurements has been proposed for antenatal screening for Down's syndrome. We here compare the efficacy of the mixture model method with the standard method, which uses NT multiple of the median (MoM) values in a single distribution. Settings A routine antenatal screening programme for Down's syndrome comprising 104 affected and 22,284 unaffected pregnancies.

Methods: The ability of NT to distinguish between affected and unaffected pregnancies was compared using the mixture model method and the standard MoM method by using published distribution parameters for the mixture model of NT and parameters derived from these for the standard MoM method. The accuracy of the two methods was compared for NT and maternal age by comparing the median estimated risk with the prevalence of Down's syndrome in different categories of estimated risk.

Results: Using NT alone observed estimates of discrimination using the two methods are similar; at a 70% detection rate the false-positive rates were 12% using the mixture model method and 10% using the MoM method. Risk estimation was marginally (but not statistically significantly) more accurate using the standard MoM method.

Conclusions: The mixture model method offers no advantage over the standard MoM method in antenatal screening for Down's syndrome, is more complicated and less generalizable to other data-sets. The standard MoM method remains the method of choice.

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Related in: MedlinePlus

Two Gaussian distribution curves of hypothetical screening marker x (a), mixture distribution curve (b) and histogram of the marker that might be observed in affected individuals (c)
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JMS-09108F2: Two Gaussian distribution curves of hypothetical screening marker x (a), mixture distribution curve (b) and histogram of the marker that might be observed in affected individuals (c)

Mentions: FigureĀ A1 shows two fitted Gaussian distribution curves of a hypothetical marker x in affected individuals (a), the mixture distribution (b) and what might be observed to justify the use of a mixture distribution, presented as a histogram (c). The five parameters are estimated simultaneously and this could be performed using maximum-likelihood estimation; the mixture distribution defined by the five parameters, which provides the best fit to the data maximizes the product of the likelihood (height of the curve) for each value of x. Methods such as the expectation maximization algorithm can be used to estimate the parameters or other methods, such as the Markov Chain Monte Carlo procedure can be used.


Evaluation of a proposed mixture model to specify the distributions of nuchal translucency measurements in antenatal screening for Down's syndrome.

Bestwick JP, Huttly WJ, Wald NJ - J Med Screen (2010)

Two Gaussian distribution curves of hypothetical screening marker x (a), mixture distribution curve (b) and histogram of the marker that might be observed in affected individuals (c)
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3104819&req=5

JMS-09108F2: Two Gaussian distribution curves of hypothetical screening marker x (a), mixture distribution curve (b) and histogram of the marker that might be observed in affected individuals (c)
Mentions: FigureĀ A1 shows two fitted Gaussian distribution curves of a hypothetical marker x in affected individuals (a), the mixture distribution (b) and what might be observed to justify the use of a mixture distribution, presented as a histogram (c). The five parameters are estimated simultaneously and this could be performed using maximum-likelihood estimation; the mixture distribution defined by the five parameters, which provides the best fit to the data maximizes the product of the likelihood (height of the curve) for each value of x. Methods such as the expectation maximization algorithm can be used to estimate the parameters or other methods, such as the Markov Chain Monte Carlo procedure can be used.

Bottom Line: A mixture model of crown-rump length (CRL)-dependent and CRL-independent nuchal translucency (NT) measurements has been proposed for antenatal screening for Down's syndrome.Settings A routine antenatal screening programme for Down's syndrome comprising 104 affected and 22,284 unaffected pregnancies.Risk estimation was marginally (but not statistically significantly) more accurate using the standard MoM method.

View Article: PubMed Central - PubMed

Affiliation: Wolfson Institute of Preventive Medicine, Barts and the London Queen Marys School of Medicine and Dentistry, Charterhouse Square, London EC1M 6BQ, UK. j.p.bestwick@qmul.ac.uk

ABSTRACT

Objectives: A mixture model of crown-rump length (CRL)-dependent and CRL-independent nuchal translucency (NT) measurements has been proposed for antenatal screening for Down's syndrome. We here compare the efficacy of the mixture model method with the standard method, which uses NT multiple of the median (MoM) values in a single distribution. Settings A routine antenatal screening programme for Down's syndrome comprising 104 affected and 22,284 unaffected pregnancies.

Methods: The ability of NT to distinguish between affected and unaffected pregnancies was compared using the mixture model method and the standard MoM method by using published distribution parameters for the mixture model of NT and parameters derived from these for the standard MoM method. The accuracy of the two methods was compared for NT and maternal age by comparing the median estimated risk with the prevalence of Down's syndrome in different categories of estimated risk.

Results: Using NT alone observed estimates of discrimination using the two methods are similar; at a 70% detection rate the false-positive rates were 12% using the mixture model method and 10% using the MoM method. Risk estimation was marginally (but not statistically significantly) more accurate using the standard MoM method.

Conclusions: The mixture model method offers no advantage over the standard MoM method in antenatal screening for Down's syndrome, is more complicated and less generalizable to other data-sets. The standard MoM method remains the method of choice.

Show MeSH
Related in: MedlinePlus