Serum multiple cytokines for the prediction of spontaneous preterm birth in asymptomatic women: A nested case-control study

Abstract

Background: Current biomarkers such as fetal fibronectin and cervical length are accurate predictors of spontaneous preterm birth (sPTB) in women with clinically suspected preterm risk; however, these are not effective for predicting the risk of sPTB in asymptomatic women. Therefore, we performed this study with the objective of determining whether the combinations of specific serum cytokines could accurately predict the sPTB risk in asymptomatic women.

Methods: We conducted a nested case-control study with 129 incident sPTB cases and 258 individually matched controls who participated in an ongoing birth cohort study. The maternal serum levels of the selected 35 cytokines were measured. We evaluated the relationship between the multiple cytokines and sPTB risk using conditional logistic regression and elastic net model.

Results: A panel of cytokines was significantly associated with an increased risk of sPTB. The odds ratio (OR) of sPTB per standard deviation (SD) increase of the predictive model score was 1.57 (95% CI 1.25-1.97) for the cytokines model. The combination of the selected serum cytokines was substantially more effective in predicting the risk for sPTB, as the receiver-operator characteristic curve (AUC) values were 0.546 and 0.559 in the single cytokine model and it improved to 0.642 in the multiple cytokines model (P_{AUC difference} = 0.02 for TNF-α vs. multiple cytokines; P_{AUC difference} = 0.05 for TRAIL vs. multiple cytokines). Moreover, the prediction was more accurate in overweight pregnant women, with an AUC = 0.879.

Conclusions: The current study suggested that the combination of selected serum cytokines can more effectively predict the risk of sPTB in asymptomatic women compared with the use of single cytokine.

Keywords: Cytokines; Prediction; Serum; Spontaneous preterm birth.