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 in | Fertility and sterility Vol. 106; no. 7; pp. 1725 - 1732.e3 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.12.2016
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Subjects | |
Online Access | Get full text |
ISSN | 0015-0282 1556-5653 1556-5653 |
DOI | 10.1016/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. |
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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 |
AuthorAffiliation_xml | – name: 1 Department Obstetrics and Gynecology, University of Pennsylvania – name: 2 Center for Epidemiology and Biostatistics, University of Pennsylvania – name: 3 Department of Obstetrics and Gynecology, Eastern Virginia Medical School – name: 4 Reproductive Endocrinology & Infertility, University of Southern California |
Author_xml | – sequence: 1 givenname: Suneeta surname: Senapati fullname: Senapati, Suneeta email: Suneeta.Senapati@uphs.upenn.edu organization: Department Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania – sequence: 2 givenname: Mary D. surname: Sammel fullname: Sammel, Mary D. organization: Center for Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania – sequence: 3 givenname: Samantha F. surname: Butts fullname: Butts, Samantha F. organization: Department Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania – sequence: 4 givenname: Peter surname: Takacs fullname: Takacs, Peter organization: Department of Obstetrics and Gynecology, Eastern Virginia Medical School, Norfolk, Virginia – sequence: 5 givenname: Karine surname: Chung fullname: Chung, Karine organization: Reproductive Endocrinology & Infertility, University of Southern California, Los Angeles, California – sequence: 6 givenname: Kurt T. surname: Barnhart fullname: Barnhart, Kurt T. organization: Department Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28340932$$D View this record in MEDLINE/PubMed |
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Keywords | early pregnancy failure Ectopic pregnancy biomarker |
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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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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 |
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