Working Towards a Risk Prediction Model for Neural Tube Defects
Supporting Files
-
3 2012 ; 3-2012
-
Available in CDC Stacks on 2015-09-14T00:00:00Z
File Language:
English
Details
-
Alternative Title:Birth Defects Res A Clin Mol Teratol
-
Personal Author:
-
Corporate Authors:
-
Description:BACKGROUND ; Several risk factors have been consistently associated with neural tube defects (NTDs). However, the predictive ability of these risk factors in combination has not been evaluated. ; METHODS ; To assess the predictive ability of established risk factors for NTDs, we built predictive models using data from the National Birth Defects Prevention Study, which is a large, population-based study of nonsyndromic birth defects. Cases with spina bifida or anencephaly, or both (n = 1239), and controls (n = 8494) were randomly divided into separate training (75% of cases and controls) and validation (remaining 25%) samples. Multivariable logistic regression models were constructed with the training samples. The predictive ability of these models was evaluated in the validation samples by assessing the area under the receiver operator characteristic curves. An ordinal predictive risk index was also constructed and evaluated. In addition, the ability of classification and regression tree (CART) analysis to identify subgroups of women at increased risk for NTDs in offspring was evaluated. ; RESULTS ; The predictive ability of the multivariable models was poor (area under the receiver operating curve: 0.55 for spina bifida only, 0.59 for anencephaly only, and 0.56 for anencephaly and spina bifida combined). The predictive abilities of the ordinal risk indexes and CART models were also low. ; CONCLUSION ; Current established risk factors for NTDs are insufficient for population-level prediction of a women’s risk for having affected offspring. Identification of genetic risk factors and novel nongenetic risk factors will be critical to establishing models, with good predictive ability, for NTDs.
-
Keywords:
-
Source:Birth Defects Res A Clin Mol Teratol. 94(3):141-146
-
Pubmed ID:22253139
-
Pubmed Central ID:PMC4569004
-
Document Type:
-
Funding:
-
Volume:94
-
Issue:3
-
Download URL:
-
File Type:
-
Collection(s):
-
Main Document Checksum:urn:sha256:68d3d6f67332e0bfcba6e0675e2a0e573a2507f25c0e7d6616ef1f04e63f18c0
Supporting Files
File Language:
English
CDC STACKS serves as an archival repository of CDC-published products including
scientific findings, journal articles, guidelines, recommendations, or other public health information authored or
co-authored by CDC or funded partners.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
You May Also Like
COLLECTION
CDC Public Access