Accurate mid-pregnancy prediction of spontaneous preterm birth (sPTB) is essential to ensure appropriate surveillance of high-risk women. Advancing the QUiPP prototype, QUiPP 2 aimed to provide individualised risk of delivery based on cervical length, quantitative fetal fibronectin (qfFN), or both tests combined, taking into account further risk factors, such as multiple pregnancy. Validation of the QUiPP 2 predictive models using a distinct dataset aims to confirm the accuracy and transportability of QUiPP overall and within certain clinically relevant timeframes.
METHODS: This was a prospective secondary analysis of data from 13 UK preterm birth clinics. A total of 1803 (3878 visits) women were included in the training set and 904 women (1400 visits) in the validation set. Survival analysis was used to identify the significant predictors of sPTB and parametric structures for survival models were compared and the best selected. The estimated overall probability of delivery before six clinically important timepoints (30, 34, 37 weeks of pregnancy and within 1, 2 and 4 weeks of testing) was calculated for each woman and analysed as a predictive test for the actual occurrence of each event. This allowed receiver-operating characteristics (ROC) curves to be plotted, and areas under the curve (AUC) calculated. Calibration was performed to measure the agreement between expected and actual outcomes.
RESULTS: All algorithms demonstrated high accuracy; AUCs between 0.75 and 0.90 for the use of qfFN and cervical length combined, 0.68 and 0.90 for qfFN and 0.71 and 0.87 for cervical length. The differences between the three algorithms were not statistically significant. Calibration confirmed no significant differences between expected and observed rates of sPTB within 4 weeks and slight over-estimation of risk with the use of cervical length measurement between 22-25+6 weeks' gestation.
CONCLUSION: QUiPP app version 2 is a highly accurate prediction tool for prematurity, based on a unique combination of biomarkers, symptoms and statistical algorithm. It can reliably be used in the context of discussing risk. Whilst further work is required to determine its role in identifying women requiring prophylactic interventions, it is a reliable and convenient screening tool for planning follow-up or hospitalisation for high risk women. This article is protected by copyright. All rights reserved.