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Objectives: Accurate mid-pregnancy prediction of spontaneous preterm birth (sPTB) is essential to ensure appropriate surveillance of high-risk women. Advancing the QUiPP App prototype, QUiPP App v.2 aimed to provide individualized risk of delivery based on cervical length (CL), quantitative fetal fibronectin (qfFN) or both tests combined, taking into account further risk factors, such as multiple pregnancy. Here we report development of the QUiPP App v.2 predictive models for use in asymptomatic high-risk women, and validation using a distinct dataset in order to confirm the accuracy and transportability of the QUiPP App, overall and within specific clinically relevant time frames.Methods: This was a prospective secondary analysis of data of asymptomatic women at high risk of sPTB recruited in 13 UK preterm birth clinics. Women were offered longitudinal qfFN testing every 2-4 weeks and/or transvaginal ultrasound CL measurement between 18 + 0 and 36 + 6 weeks' gestation. A total of 1803 women (3878 visits) were included in the training set and 904 women (1400 visits) in the validation set. Prediction models were created based on the training set for use in three groups: patients with risk factors for sPTB and CL measurement alone, with risk factors for sPTB and qfFN measurement alone, and those with risk factors for sPTB and both CL and qfFN measurements. 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 time points (< 30, < 34 and < 37 weeks' gestation and within 1, 2 and 4 weeks after testing) was calculated for each woman and analyzed as a predictive test for the actual occurrence of each event. This allowed receiver-operating-characteristics curves to be plotted, and areas under the curve (AUC) to be calculated. Calibration was performed to measure the agreement between expected and observed outcomes.Results: All three algorithms demonstrated high accuracy for the prediction of sPTB at < 30, < 34 and < 37 weeks' gestation and within 1, 2 and 4 weeks of testing, with AUCs between 0.75 and 0.90 for the use of qfFN and CL combined, between 0.68 and 0.90 for qfFN alone, and between 0.71 and 0.87 for CL alone. 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 a slight overestimation of risk with the use of CL measurement between 22 + 0 and 25 + 6 weeks' gestation.Conclusions: The QUiPP App v.2 is a highly accurate prediction tool for sPTB that is based on a unique combination of biomarkers, symptoms and statistical algorithms. It can be used reliably in the context of communicating to patients the risk of sPTB. 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 hospitalization for high-risk women. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Objective: To develop enhanced prediction models to update the QUiPP App prototype, a tool providing individualized risk of spontaneous preterm birth (sPTB), for use in women with symptoms of threatened preterm labor (TPTL), incorporating risk factors, transvaginal ultrasound assessment of cervical length (CL) and cervicovaginal fluid quantitative fetal fibronectin (qfFN) test results.Methods: Participants were pregnant women between 23 + 0 and 34 + 6 weeks' gestation with symptoms of TPTL, recruited as part of four prospective cohort studies carried out at 16 UK hospitals between October 2010 and October 2017. The training set comprised all women whose outcomes were known in May 2017 (n = 1032). The validation set comprised women whose outcomes were gathered between June 2017 and March 2018 (n = 506). Parametric survival models were developed for three combinations of predictors: risk factors plus qfFN test results alone, risk factors plus CL alone, and risk factors plus both qfFN and CL. The best models were selected using the Akaike and Bayesian information criteria. The estimated probability of sPTB < 30, < 34 or < 37 weeks' gestation and within 1 or 2 weeks of testing was calculated and receiver-operating-characteristics (ROC) curves were created to demonstrate the diagnostic ability of the prediction models.Results: Predictive statistics were similar between the training and the validation sets at most outcome time points and for each combination of predictors. Areas under the ROC curves (AUC) demonstrated that all three algorithms had good accuracy for the prediction of sPTB at < 30, < 34 and < 37 weeks' gestation and within 1 and 2 weeks' post-testing in the validation set, particularly the model combining risk factors plus qfFN alone (AUC: 0.96 at < 30 weeks; 0.85 at < 34 weeks; 0.77 at < 37 weeks; 0.91 at < 1 week from testing; and 0.92 at < 2 weeks from testing).Conclusions: Validation of the new prediction models suggests that the QUiPP App v.2 can reliably calculate risk of sPTB in women with TPTL. Use of the QUiPP App in practice could lead to better targeting of intervention, while providing reassurance and avoiding unnecessary intervention in women at low risk. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Objective: To report on the routine clinical implementation of cell-free DNA (cfDNA) analysis of maternal blood for trisomies 21, 18 and 13, contingent on the results of the first-trimester combined test in twin pregnancy.Methods: Screening for trisomies 21, 18 and 13 was carried out in 959 twin pregnancies by assessment of a combination of maternal age, fetal nuchal translucency thickness, and serum free β-human chorionic gonadotropin and pregnancy-associated plasma protein-A at 11-13 weeks' gestation in two UK NHS hospitals. Women in the high-risk group (risk ≥ 1 in 100) were offered the option of invasive testing, cfDNA testing or no further testing, and those in the intermediate-risk group (risk 1 in 101 to 1 in 2500 in the first phase of the study and 1 in 101 to 1 in 500 in the second phase) were offered cfDNA or no further testing. The trisomic status of the pregnancies was determined by prenatal or postnatal karyotyping or examination of the neonates.Results: In 42 (4.4%) of the 959 pregnancies, there was termination, miscarriage or stillbirth with no known karyotype or there was loss to follow-up. The 917 pregnancies with known trisomic status of both twins included six that were discordant for trisomy 21, four that were discordant for trisomy 18 and 907 with no trisomy 21, 18 or 13. Following combined screening, 47 (5.1%), 203 (22.1%) and 667 (72.7%) of the pregnancies were classified as high risk, intermediate risk and low risk, respectively. The high-risk group included five (83.3%) cases of trisomy 21 and three (75.0%) of trisomy 18. The cfDNA test was carried out in 224 pregnancies and results were provided in 214 (95.5%); this group included six pregnancies with trisomy 21, three with trisomy 18 and 206 with no trisomy 21, 18 or 13. The cfDNA test classified correctly as screen positive all six cases of trisomy 21 and two of the three with trisomy 18, and as screen negative for each of the trisomies all 206 unaffected pregnancies. Contingent screening led to prenatal detection of all cases of trisomy 21 and three of four with trisomy 18.Conclusion: This study has demonstrated the feasibility of introducing cfDNA testing, contingent on the results of the first-trimester combined test for major trisomies, in a routine population of twin pregnancies. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]