Predicting first trimester pregnancy outcome: derivation of a multiple marker test

To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Case-control study. Three academic centers. Women with pain and bleeding in early pregnancy. Sera from women who were 5–12 weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IU...

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Published inFertility and sterility Vol. 106; no. 7; pp. 1725 - 1732.e3
Main Authors Senapati, Suneeta, Sammel, Mary D., Butts, Samantha F., Takacs, Peter, Chung, Karine, Barnhart, Kurt T.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.12.2016
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Online AccessGet full text
ISSN0015-0282
1556-5653
1556-5653
DOI10.1016/j.fertnstert.2016.08.044

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Abstract To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Case-control study. Three academic centers. Women with pain and bleeding in early pregnancy. Sera from women who were 5–12 weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage/spontaneous abortion (SAB) was analyzed by ELISA and immunoassay for activin A, inhibin A, P, A Disintegrin And Metalloprotease-12, pregnancy-associated plasma protein A (PAPP-A), pregnancy specific B1-glycoprotein (SP1), placental-like growth factor, vascular endothelial growth factor, glycodelin (Glyc), and hCG. Classification trees were developed to optimize sensitivity/specificity for pregnancy location and viability. Area under receiver operating characteristic curve, sensitivity, specificity, and accuracy of first trimester pregnancy outcome. In 230 pregnancies, the combination of trees to maximize sensitivity and specificity resulted in 73% specificity (95% confidence interval (CI) 0.65–0.80) and 31% sensitivity (95% CI 0.21–0.43) for viability. Similar methods had 21% sensitivity (95% CI 0.12–0.32) and 33% specificity (95% CI 0.26–0.41) for location. Activin A, Glyc, and A Disintegrin And Metalloprotease-12 definitively classified pregnancy location in 29% of the sample with 100% accuracy for EP. Progesterone and PAPP-A classified the viability in 61% of the sample with 94% accuracy. Multiple marker panels can distinguish pregnancy location and viability in a subset of women at risk for early pregnancy complications. This strategy of combining markers to maximize sensitivity and specificity results in high accuracy in a subset of subjects. Activin A, ADAM12, and Glyc are the most promising markers for pregnancy location; P and PAPP-A for viability.
AbstractList To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort.OBJECTIVETo predict first trimester pregnancy outcome using biomarkers in a multicenter cohort.Case-control study.DESIGNCase-control study.Three academic centers.SETTINGThree academic centers.Women with pain and bleeding in early pregnancy.PATIENT(S)Women with pain and bleeding in early pregnancy.Sera from women who were 5-12 weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage/spontaneous abortion (SAB) was analyzed by ELISA and immunoassay for activin A, inhibin A, P, A Disintegrin And Metalloprotease-12, pregnancy-associated plasma protein A (PAPP-A), pregnancy specific B1-glycoprotein (SP1), placental-like growth factor, vascular endothelial growth factor, glycodelin (Glyc), and hCG. Classification trees were developed to optimize sensitivity/specificity for pregnancy location and viability.INTERVENTION(S)Sera from women who were 5-12 weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage/spontaneous abortion (SAB) was analyzed by ELISA and immunoassay for activin A, inhibin A, P, A Disintegrin And Metalloprotease-12, pregnancy-associated plasma protein A (PAPP-A), pregnancy specific B1-glycoprotein (SP1), placental-like growth factor, vascular endothelial growth factor, glycodelin (Glyc), and hCG. Classification trees were developed to optimize sensitivity/specificity for pregnancy location and viability.Area under receiver operating characteristic curve, sensitivity, specificity, and accuracy of first trimester pregnancy outcome.MAIN OUTCOME MEASURE(S)Area under receiver operating characteristic curve, sensitivity, specificity, and accuracy of first trimester pregnancy outcome.In 230 pregnancies, the combination of trees to maximize sensitivity and specificity resulted in 73% specificity (95% confidence interval (CI) 0.65-0.80) and 31% sensitivity (95% CI 0.21-0.43) for viability. Similar methods had 21% sensitivity (95% CI 0.12-0.32) and 33% specificity (95% CI 0.26-0.41) for location. Activin A, Glyc, and A Disintegrin And Metalloprotease-12 definitively classified pregnancy location in 29% of the sample with 100% accuracy for EP. Progesterone and PAPP-A classified the viability in 61% of the sample with 94% accuracy.RESULT(S)In 230 pregnancies, the combination of trees to maximize sensitivity and specificity resulted in 73% specificity (95% confidence interval (CI) 0.65-0.80) and 31% sensitivity (95% CI 0.21-0.43) for viability. Similar methods had 21% sensitivity (95% CI 0.12-0.32) and 33% specificity (95% CI 0.26-0.41) for location. Activin A, Glyc, and A Disintegrin And Metalloprotease-12 definitively classified pregnancy location in 29% of the sample with 100% accuracy for EP. Progesterone and PAPP-A classified the viability in 61% of the sample with 94% accuracy.Multiple marker panels can distinguish pregnancy location and viability in a subset of women at risk for early pregnancy complications. This strategy of combining markers to maximize sensitivity and specificity results in high accuracy in a subset of subjects. Activin A, ADAM12, and Glyc are the most promising markers for pregnancy location; P and PAPP-A for viability.CONCLUSION(S)Multiple marker panels can distinguish pregnancy location and viability in a subset of women at risk for early pregnancy complications. This strategy of combining markers to maximize sensitivity and specificity results in high accuracy in a subset of subjects. Activin A, ADAM12, and Glyc are the most promising markers for pregnancy location; P and PAPP-A for viability.
Objective To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Design Case-control study. Setting Three academic centers. Patient(s) Women with pain and bleeding in early pregnancy. Intervention(s) Sera from women who were 5–12 weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage/spontaneous abortion (SAB) was analyzed by ELISA and immunoassay for activin A, inhibin A, P, A Disintegrin And Metalloprotease-12, pregnancy-associated plasma protein A (PAPP-A), pregnancy specific B1 -glycoprotein (SP1 ), placental-like growth factor, vascular endothelial growth factor, glycodelin (Glyc), and hCG. Classification trees were developed to optimize sensitivity/specificity for pregnancy location and viability. Main Outcome Measure(s) Area under receiver operating characteristic curve, sensitivity, specificity, and accuracy of first trimester pregnancy outcome. Result(s) In 230 pregnancies, the combination of trees to maximize sensitivity and specificity resulted in 73% specificity (95% confidence interval (CI) 0.65–0.80) and 31% sensitivity (95% CI 0.21–0.43) for viability. Similar methods had 21% sensitivity (95% CI 0.12–0.32) and 33% specificity (95% CI 0.26–0.41) for location. Activin A, Glyc, and A Disintegrin And Metalloprotease-12 definitively classified pregnancy location in 29% of the sample with 100% accuracy for EP. Progesterone and PAPP-A classified the viability in 61% of the sample with 94% accuracy. Conclusion(s) Multiple marker panels can distinguish pregnancy location and viability in a subset of women at risk for early pregnancy complications. This strategy of combining markers to maximize sensitivity and specificity results in high accuracy in a subset of subjects. Activin A, ADAM12, and Glyc are the most promising markers for pregnancy location; P and PAPP-A for viability.
To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Case-control study. Three academic centers. Women with pain and bleeding in early pregnancy. Sera from women who were 5–12 weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage/spontaneous abortion (SAB) was analyzed by ELISA and immunoassay for activin A, inhibin A, P, A Disintegrin And Metalloprotease-12, pregnancy-associated plasma protein A (PAPP-A), pregnancy specific B1-glycoprotein (SP1), placental-like growth factor, vascular endothelial growth factor, glycodelin (Glyc), and hCG. Classification trees were developed to optimize sensitivity/specificity for pregnancy location and viability. Area under receiver operating characteristic curve, sensitivity, specificity, and accuracy of first trimester pregnancy outcome. In 230 pregnancies, the combination of trees to maximize sensitivity and specificity resulted in 73% specificity (95% confidence interval (CI) 0.65–0.80) and 31% sensitivity (95% CI 0.21–0.43) for viability. Similar methods had 21% sensitivity (95% CI 0.12–0.32) and 33% specificity (95% CI 0.26–0.41) for location. Activin A, Glyc, and A Disintegrin And Metalloprotease-12 definitively classified pregnancy location in 29% of the sample with 100% accuracy for EP. Progesterone and PAPP-A classified the viability in 61% of the sample with 94% accuracy. Multiple marker panels can distinguish pregnancy location and viability in a subset of women at risk for early pregnancy complications. This strategy of combining markers to maximize sensitivity and specificity results in high accuracy in a subset of subjects. Activin A, ADAM12, and Glyc are the most promising markers for pregnancy location; P and PAPP-A for viability.
To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Case-control study. Three academic centers. Women with pain and bleeding in early pregnancy. Sera from women who were 5-12 weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage/spontaneous abortion (SAB) was analyzed by ELISA and immunoassay for activin A, inhibin A, P, A Disintegrin And Metalloprotease-12, pregnancy-associated plasma protein A (PAPP-A), pregnancy specific B -glycoprotein (SP ), placental-like growth factor, vascular endothelial growth factor, glycodelin (Glyc), and hCG. Classification trees were developed to optimize sensitivity/specificity for pregnancy location and viability. Area under receiver operating characteristic curve, sensitivity, specificity, and accuracy of first trimester pregnancy outcome. In 230 pregnancies, the combination of trees to maximize sensitivity and specificity resulted in 73% specificity (95% confidence interval (CI) 0.65-0.80) and 31% sensitivity (95% CI 0.21-0.43) for viability. Similar methods had 21% sensitivity (95% CI 0.12-0.32) and 33% specificity (95% CI 0.26-0.41) for location. Activin A, Glyc, and A Disintegrin And Metalloprotease-12 definitively classified pregnancy location in 29% of the sample with 100% accuracy for EP. Progesterone and PAPP-A classified the viability in 61% of the sample with 94% accuracy. Multiple marker panels can distinguish pregnancy location and viability in a subset of women at risk for early pregnancy complications. This strategy of combining markers to maximize sensitivity and specificity results in high accuracy in a subset of subjects. Activin A, ADAM12, and Glyc are the most promising markers for pregnancy location; P and PAPP-A for viability.
Author Butts, Samantha F.
Sammel, Mary D.
Chung, Karine
Barnhart, Kurt T.
Senapati, Suneeta
Takacs, Peter
AuthorAffiliation 2 Center for Epidemiology and Biostatistics, University of Pennsylvania
3 Department of Obstetrics and Gynecology, Eastern Virginia Medical School
1 Department Obstetrics and Gynecology, University of Pennsylvania
4 Reproductive Endocrinology & Infertility, University of Southern California
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Issue 7
Keywords early pregnancy failure
Ectopic pregnancy
biomarker
Language English
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Snippet To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Case-control study. Three academic centers. Women with pain and bleeding...
Objective To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Design Case-control study. Setting Three academic centers....
To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort.OBJECTIVETo predict first trimester pregnancy outcome using biomarkers in...
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StartPage 1725
SubjectTerms Abortion, Spontaneous - blood
Abortion, Spontaneous - diagnosis
Activins - blood
ADAM12 Protein - blood
Area Under Curve
biomarker
Biomarkers - blood
Case-Control Studies
early pregnancy failure
Ectopic pregnancy
Enzyme-Linked Immunosorbent Assay
Female
Glycodelin - blood
Humans
Immunoassay
Internal Medicine
Obstetrics and Gynecology
Predictive Value of Tests
Pregnancy
Pregnancy Outcome
Pregnancy Trimester, First - blood
Pregnancy, Ectopic - blood
Pregnancy, Ectopic - diagnosis
Pregnancy-Associated Plasma Protein-A - analysis
Progesterone - blood
Reproducibility of Results
Risk Factors
ROC Curve
United States
Title Predicting first trimester pregnancy outcome: derivation of a multiple marker test
URI https://www.clinicalkey.com/#!/content/1-s2.0-S001502821662770X
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https://dx.doi.org/10.1016/j.fertnstert.2016.08.044
https://www.ncbi.nlm.nih.gov/pubmed/28340932
https://www.proquest.com/docview/1881265963
https://pubmed.ncbi.nlm.nih.gov/PMC5373488
http://doi.org/10.1016/j.fertnstert.2016.08.044
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