Development and validation of predictive models for QUiPP App v.2: tool for predicting preterm birth in asymptomatic high‐risk women

Abstract

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 fol...

Development and validation of predictive models for QUiPP App v.2: tool for predicting preterm birth in women with symptoms of threatened preterm labor

“…In this paper, we report findings from the validation of the three algorithms appropriate for the cohorts with symptoms of TPTL. Development and validation of the predictive models for asymptomatic high‐risk women is reported in another paper by our group published in the same issue of the Journal.…”

Volatile organic compound analysis, a new tool in the quest for preterm birth prediction—an observational cohort study

“…More recently cervical length measurement, quantitative fetal fibronectin and clinical factors have been combined and developed into a predictive model for preterm birth in asymptomatic women. This work has demonstrated that spontaneous preterm both can be accurately predicted with AUC values ranging from 0.75 to 0.90 40 . VOCs have potential benefits, in addition to the existing published model for several reasons.…”

Re: Effect of QUiPP prediction algorithm on treatment decisions in women with a previous preterm birth: a prospective cohort study

“…They only had 15 cases of spontaneous preterm birth <34 weeks. In our most recent validation of the fetal fibronectin (fFN) QUiPP asymptomatic algorithm, 86 cases (out of 1081 women) from multiple sites illustrated close correlation between predicted and actual event rates …”

“…The QUiPP app, a decision‐making tool for preterm birth, is an accurate determinant of preterm birth risk as proven in evaluating outcomes of nearly 3000 high‐risk women from multiple sites . Fundamentally, QUiPP's core value is to individualise risk and facilitate shared decision‐making.…”

“…Applying a fixed threshold to direct prophylactic interventions, as Goodfellow et al. have suggested, undermines QUiPP's value and is not the advised approach . Currently, prophylactic interventions should be directed to those with a short cervix.…”