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Predicting first trimester pregnancy outcome: derivation of a multiple marker test.
Senapati, Suneeta; Sammel, Mary D; Butts, Samantha F; Takacs, Peter; Chung, Karine; Barnhart, Kurt T.
Afiliación
  • Senapati S; Department Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: Suneeta.Senapati@uphs.upenn.edu.
  • Sammel MD; Center for Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Butts SF; Department Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Takacs P; Department of Obstetrics and Gynecology, Eastern Virginia Medical School, Norfolk, Virginia.
  • Chung K; Reproductive Endocrinology & Infertility, University of Southern California, Los Angeles, California.
  • Barnhart KT; Department Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania.
Fertil Steril ; 106(7): 1725-1732.e3, 2016 Dec.
Article en En | MEDLINE | ID: mdl-28340932
ABSTRACT

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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteína Plasmática A Asociada al Embarazo / Embarazo Ectópico / Primer Trimestre del Embarazo / Progesterona / Aborto Espontáneo / Activinas / Proteína ADAM12 / Glicodelina Tipo de estudio: Clinical_trials / Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy País/Región como asunto: America do norte Idioma: En Revista: Fertil Steril Año: 2016 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteína Plasmática A Asociada al Embarazo / Embarazo Ectópico / Primer Trimestre del Embarazo / Progesterona / Aborto Espontáneo / Activinas / Proteína ADAM12 / Glicodelina Tipo de estudio: Clinical_trials / Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy País/Región como asunto: America do norte Idioma: En Revista: Fertil Steril Año: 2016 Tipo del documento: Article