Prediction of Preterm Birth Using the Second-Trimester Quadruple Test
The second-trimester quadruple test shows moderate ability to predict preterm birth, but further research in larger cohorts is needed to validate its effectiveness.
Where it sits
this study against the rest of the hcg (human chorionic gonadotropin) corpusSummary and findings
This study evaluated the predictive performance of the second-trimester quadruple test for preterm birth in 200 pregnant women. The four-marker model demonstrated an area under the ROC curve (AUC) of 0.747. The study found that the quadruple test had a sensitivity of 72.3% and specificity of 72.5%.
Abstract
<title>Abstract</title> <p>Background Preterm birth is a major contributor to neonatal morbidity and mortality. Maternal serum biomarkers measured during the second trimester may help identify pregnancies at increased risk of preterm delivery. This study evaluated the predictive performance of the second-trimester quadruple test and its individual components for preterm birth. Methods This prospective observational study included 200 pregnant women attending the antenatal and fetal medicine outpatient departments of Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi. Women with singleton pregnancies between 15 + 0 and 20 + 6 weeks of gestation were enrolled. Maternal serum alpha-fetoprotein (AFP), free beta-human chorionic gonadotropin (free β-hCG), unconjugated estriol (uE3), and inhibin A were measured using validated laboratory assays. The predictive performance of individual biomarkers and combinations of the four markers was evaluated using receiver operating characteristic (ROC) curve analysis. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were assessed at the selected cut-off values. Results The four-marker model demonstrated the highest area under the ROC curve (AUC) of 0.747, followed by inhibin A (0.721), AFP (0.680), free β-hCG (0.659), and uE3 (0.644). At the selected cut-offs, AFP demonstrated a sensitivity of 74.5% and specificity of 48.4%, whereas inhibin A showed a sensitivity of 53.2% and specificity of 79.1%. The four-marker model demonstrated a sensitivity of 72.3%, specificity of 72.5%, positive predictive value of 44.8%, and negative predictive value of 89.5%. Conclusion The second-trimester quadruple test demonstrated moderate discriminatory ability for predicting preterm birth, with better overall discrimination than individual biomarkers. These findings support further evaluation of the quadruple test as a potential component of preterm birth risk assessment in larger prospective cohorts.</p>
Background
Preterm birth is a significant cause of neonatal morbidity and mortality, making the identification of at-risk pregnancies crucial. Previous studies have suggested that maternal serum biomarkers during the second trimester may aid in predicting preterm delivery. This study investigates the predictive performance of the second-trimester quadruple test, which includes multiple biomarkers, to enhance risk assessment for preterm birth.
Methods
This was a prospective observational study involving 200 pregnant women with singleton pregnancies between 15 + 0 and 20 + 6 weeks of gestation. The biomarkers measured included maternal serum alpha-fetoprotein, free beta-human chorionic gonadotropin, unconjugated estriol, and inhibin A. The study employed receiver operating characteristic (ROC) curve analysis to evaluate the predictive performance of the biomarkers.
Results
The four-marker model exhibited the highest area under the ROC curve (AUC) of 0.747. The sensitivity and specificity of individual biomarkers varied, with AFP showing a sensitivity of 74.5% and specificity of 48.4%. The four-marker model achieved a sensitivity of 72.3% and specificity of 72.5%, with a positive predictive value of 44.8% and a negative predictive value of 89.5%.
Interpretation
The findings indicate that the second-trimester quadruple test has moderate discriminatory ability for predicting preterm birth, outperforming individual biomarkers. However, the clinical significance of the predictive values, particularly the positive predictive value of 44.8%, may be limited. The study's observational design and sample size could confound the results, necessitating further research in larger cohorts to validate these findings.
Key findings
- AUC of the four-marker model was 0.747.
- Sensitivity of AFP was 74.5% and specificity was 48.4%.
- Sensitivity of inhibin A was 53.2% and specificity was 79.1%.
- Four-marker model sensitivity was 72.3% and specificity was 72.5%.
- Positive predictive value of the four-marker model was 44.8% and negative predictive value was 89.5%.
Limitations
- observational design limits causal inference
- sample size of 200 may not be sufficient for generalization
- results need confirmation in larger prospective cohorts