Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis.
BACKGROUND: Several biomarkers for predicting intrauterine growth restriction (IUGR) have been proposed in recent years. However, the predictive performance of these biomarkers has not been systematically evaluated. OBJECTIVE: To determine the predictive accuracy of novel biomarkers for IUGR in wom...
| Principais autores: | , , , |
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| Formato: | Journal article |
| Idioma: | English |
| Publicado em: |
2013
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| _version_ | 1826270276936007680 |
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| author | Conde-Agudelo, A Papageorghiou, A Kennedy, S Villar, J |
| author_facet | Conde-Agudelo, A Papageorghiou, A Kennedy, S Villar, J |
| author_sort | Conde-Agudelo, A |
| collection | OXFORD |
| description | BACKGROUND: Several biomarkers for predicting intrauterine growth restriction (IUGR) have been proposed in recent years. However, the predictive performance of these biomarkers has not been systematically evaluated. OBJECTIVE: To determine the predictive accuracy of novel biomarkers for IUGR in women with singleton gestations. SEARCH STRATEGY: Electronic databases, reference list checking and conference proceedings. SELECTION CRITERIA: Observational studies that evaluated the accuracy of novel biomarkers proposed for predicting IUGR. DATA COLLECTION AND ANALYSIS: Data were extracted on characteristics, quality and predictive accuracy from each study to construct 2×2 tables. Summary receiver operating characteristic curves, sensitivities, specificities and likelihood ratios (LRs) were generated. MAIN RESULTS: A total of 53 studies, including 39,974 women and evaluating 37 novel biomarkers, fulfilled the inclusion criteria. Overall, the predictive accuracy of angiogenic factors for IUGR was minimal (median pooled positive and negative LRs of 1.7, range 1.0-19.8; and 0.8, range 0.0-1.0, respectively). Two small case-control studies reported high predictive values for placental growth factor and angiopoietin-2 only when IUGR was defined as birthweight centile with clinical or pathological evidence of fetal growth restriction. Biomarkers related to endothelial function/oxidative stress, placental protein/hormone, and others such as serum levels of vitamin D, urinary albumin:creatinine ratio, thyroid function tests and metabolomic profile had low predictive accuracy. CONCLUSIONS: None of the novel biomarkers evaluated in this review are sufficiently accurate to recommend their use as predictors of IUGR in routine clinical practice. However, the use of biomarkers in combination with biophysical parameters and maternal characteristics could be more useful and merits further research. |
| first_indexed | 2024-03-06T21:38:19Z |
| format | Journal article |
| id | oxford-uuid:4708dbf6-aa6b-4bcc-8aa8-c54e3b76521d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T21:38:19Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:4708dbf6-aa6b-4bcc-8aa8-c54e3b76521d2022-03-26T15:17:32ZNovel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:4708dbf6-aa6b-4bcc-8aa8-c54e3b76521dEnglishSymplectic Elements at Oxford2013Conde-Agudelo, APapageorghiou, AKennedy, SVillar, J BACKGROUND: Several biomarkers for predicting intrauterine growth restriction (IUGR) have been proposed in recent years. However, the predictive performance of these biomarkers has not been systematically evaluated. OBJECTIVE: To determine the predictive accuracy of novel biomarkers for IUGR in women with singleton gestations. SEARCH STRATEGY: Electronic databases, reference list checking and conference proceedings. SELECTION CRITERIA: Observational studies that evaluated the accuracy of novel biomarkers proposed for predicting IUGR. DATA COLLECTION AND ANALYSIS: Data were extracted on characteristics, quality and predictive accuracy from each study to construct 2×2 tables. Summary receiver operating characteristic curves, sensitivities, specificities and likelihood ratios (LRs) were generated. MAIN RESULTS: A total of 53 studies, including 39,974 women and evaluating 37 novel biomarkers, fulfilled the inclusion criteria. Overall, the predictive accuracy of angiogenic factors for IUGR was minimal (median pooled positive and negative LRs of 1.7, range 1.0-19.8; and 0.8, range 0.0-1.0, respectively). Two small case-control studies reported high predictive values for placental growth factor and angiopoietin-2 only when IUGR was defined as birthweight centile with clinical or pathological evidence of fetal growth restriction. Biomarkers related to endothelial function/oxidative stress, placental protein/hormone, and others such as serum levels of vitamin D, urinary albumin:creatinine ratio, thyroid function tests and metabolomic profile had low predictive accuracy. CONCLUSIONS: None of the novel biomarkers evaluated in this review are sufficiently accurate to recommend their use as predictors of IUGR in routine clinical practice. However, the use of biomarkers in combination with biophysical parameters and maternal characteristics could be more useful and merits further research. |
| spellingShingle | Conde-Agudelo, A Papageorghiou, A Kennedy, S Villar, J Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis. |
| title | Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis. |
| title_full | Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis. |
| title_fullStr | Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis. |
| title_full_unstemmed | Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis. |
| title_short | Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis. |
| title_sort | novel biomarkers for predicting intrauterine growth restriction a systematic review and meta analysis |
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