Cervicovaginal fetal fibronectin for the prediction of spontaneous preterm birth in multiple pregnancies: a systematic review and meta-analysis

Abstract

Objective. To investigate the accuracy of cervicovaginal fetal fibronectin in predicting preterm birth in women with multiple pregnancies.

Methods. Systematic review and meta-analysis of predictive test accuracy. Cohort or cross-sectional studies were identified through searches in databases, reference lists, proceedings, and reviews. Study selection, quality assessment, and data extraction were performed. We constructed summary receiver operating characteristic curves and calculated pooled sensitivities and specificities using a bivariate, random-effects meta-regression model. We also calculated summary likelihood ratios and post-test probabilities of preterm birth.

Results. Fifteen studies (11 in asymptomatic women and 4 in women with symptoms of preterm labor) involving 1221 women with multiple pregnancies were included. Among asymptomatic women with multiple or twin pregnancies, the pooled sensitivities, specificities, and positive and negative likelihood ratios for predicting preterm birth before 32, 34, and 37 weeks' gestation ranged from 33% to 45%, 80% to 94%, 2.0 to 5.5, and 0.68 to 0.76, respectively. Among women with twin pregnancies and threatened preterm labor, the test was most accurate in predicting spontaneous preterm birth within 7 days of testing (pooled sensitivity, specificity, and positive and negative likelihood ratios of 85%, 78%, 3.9, and 0.20, respectively).

Conclusions. Cervicovaginal fetal fibronectin provides moderate to minimal prediction of preterm birth in women with multiple pregnancies. The test is most accurate in predicting spontaneous preterm birth within 7 days of testing in women with twin pregnancies and threatened preterm labor.

Keywords:

• Multiple pregnancy
• twin pregnancy
• preterm labor
• prematurity
• twins

Acknowledgements

This research was supported by the Perinatology Research Branch: Division of Intramural Research of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services. We are very grateful to Dr. Percy Pacora for his assistance in obtaining the articles. We would like to thank Dr. Nathan Fox for assistance in providing unpublished data from your study and for clarifications of other queries.