Cargando…
A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy
To establish a risk prediction model and the clinical value of trisomy 21 using alpha-fetoprotein variants L2 (AFP-L2) combined with maternal serum biomarkers and nuchal translucency (NT) thickness in early pregnancy. A retrospective case–control study was conducted. The subjects were divided into t...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907085/ https://www.ncbi.nlm.nih.gov/pubmed/34750768 http://dx.doi.org/10.1007/s43032-021-00762-5 |
_version_ | 1784665556316585984 |
---|---|
author | Chen, Yiming Wu, Bin Chen, Yijie Ning, Wenwen Zhang, Huimin |
author_facet | Chen, Yiming Wu, Bin Chen, Yijie Ning, Wenwen Zhang, Huimin |
author_sort | Chen, Yiming |
collection | PubMed |
description | To establish a risk prediction model and the clinical value of trisomy 21 using alpha-fetoprotein variants L2 (AFP-L2) combined with maternal serum biomarkers and nuchal translucency (NT) thickness in early pregnancy. A retrospective case–control study was conducted. The subjects were divided into the case group (n = 40) or the control group (n = 40). An enzyme-linked immunosorbent assay was used to measure the maternal serum AFP-L2 level in both groups. The AFP-L2 single-index or multi-index combined risk model was used to predict the efficiency of trisomy 21. The best cut-off value and area under the curve (AUC) were determined to evaluate the predictive efficacy of different risk models constructed by AFP-L2. The maternal serum AFP-L2 level in the case group was 1.59 (0.61–3.61) Multiple of medium (MoM), which was higher than 1.00 (0.39–2.12) MoM in the control group (P < 0.001). The free beta-human chorionic gonadotropin (free β-hCG) level and NT in the case group were significantly higher than those in the control group (P < 0.001). The pregnancy-associated plasma protein A (PAPP-A) level in the case group was lower than that in the control group (P < 0.001). The AUC of AFP-L2 in predicting trisomy 21 was 0.797. After considering the maternal serum AFP-L2 level, the AUC, detection rate (DR), positive predictive value (PPV), negative predictive value (NPV), falsepositive rate (FPR), false negative rate (FNR), positive likelihood ratio (+LR), and negative likelihood ratio (-LR) were significantly improved. In this study, PAPP-A + free β-hCG + NT + AFP-L2 and PAPP-A + free β-hCG + AFP-L2 increased the integrated discrimination improvement (IDI) and net classification improvement (NRI) of predicting fetuses with trisomy 21 (1.10% and 5.27%; 11.07% and 2.78%) (1.10% and 5.27%; 11.07% and 2.78%), respectively, after considering the maternal serum AFP-L2 level. The maternal serum AFP-L2 level in early pregnancy had high sensitivity and specificity, and it was a good biomarker to predict fetuses with trisomy 21. |
format | Online Article Text |
id | pubmed-8907085 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-89070852022-03-15 A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy Chen, Yiming Wu, Bin Chen, Yijie Ning, Wenwen Zhang, Huimin Reprod Sci Maternal Fetal Medicine/Biology: Original Article To establish a risk prediction model and the clinical value of trisomy 21 using alpha-fetoprotein variants L2 (AFP-L2) combined with maternal serum biomarkers and nuchal translucency (NT) thickness in early pregnancy. A retrospective case–control study was conducted. The subjects were divided into the case group (n = 40) or the control group (n = 40). An enzyme-linked immunosorbent assay was used to measure the maternal serum AFP-L2 level in both groups. The AFP-L2 single-index or multi-index combined risk model was used to predict the efficiency of trisomy 21. The best cut-off value and area under the curve (AUC) were determined to evaluate the predictive efficacy of different risk models constructed by AFP-L2. The maternal serum AFP-L2 level in the case group was 1.59 (0.61–3.61) Multiple of medium (MoM), which was higher than 1.00 (0.39–2.12) MoM in the control group (P < 0.001). The free beta-human chorionic gonadotropin (free β-hCG) level and NT in the case group were significantly higher than those in the control group (P < 0.001). The pregnancy-associated plasma protein A (PAPP-A) level in the case group was lower than that in the control group (P < 0.001). The AUC of AFP-L2 in predicting trisomy 21 was 0.797. After considering the maternal serum AFP-L2 level, the AUC, detection rate (DR), positive predictive value (PPV), negative predictive value (NPV), falsepositive rate (FPR), false negative rate (FNR), positive likelihood ratio (+LR), and negative likelihood ratio (-LR) were significantly improved. In this study, PAPP-A + free β-hCG + NT + AFP-L2 and PAPP-A + free β-hCG + AFP-L2 increased the integrated discrimination improvement (IDI) and net classification improvement (NRI) of predicting fetuses with trisomy 21 (1.10% and 5.27%; 11.07% and 2.78%) (1.10% and 5.27%; 11.07% and 2.78%), respectively, after considering the maternal serum AFP-L2 level. The maternal serum AFP-L2 level in early pregnancy had high sensitivity and specificity, and it was a good biomarker to predict fetuses with trisomy 21. Springer International Publishing 2021-11-08 /pmc/articles/PMC8907085/ /pubmed/34750768 http://dx.doi.org/10.1007/s43032-021-00762-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Maternal Fetal Medicine/Biology: Original Article Chen, Yiming Wu, Bin Chen, Yijie Ning, Wenwen Zhang, Huimin A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy |
title | A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy |
title_full | A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy |
title_fullStr | A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy |
title_full_unstemmed | A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy |
title_short | A Risk Model for Predicting Fetuses with Trisomy 21 Using Alpha-Fetoprotein Variants L2 Combined with Maternal Serum Biomarkers in Early Pregnancy |
title_sort | risk model for predicting fetuses with trisomy 21 using alpha-fetoprotein variants l2 combined with maternal serum biomarkers in early pregnancy |
topic | Maternal Fetal Medicine/Biology: Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907085/ https://www.ncbi.nlm.nih.gov/pubmed/34750768 http://dx.doi.org/10.1007/s43032-021-00762-5 |
work_keys_str_mv | AT chenyiming ariskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT wubin ariskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT chenyijie ariskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT ningwenwen ariskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT zhanghuimin ariskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT chenyiming riskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT wubin riskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT chenyijie riskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT ningwenwen riskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy AT zhanghuimin riskmodelforpredictingfetuseswithtrisomy21usingalphafetoproteinvariantsl2combinedwithmaternalserumbiomarkersinearlypregnancy |