A prognostic model, including quantitative fetal fibronectin, to predict preterm labour: the QUIDS meta-analysis and prospective cohort study.

BACKGROUND: The diagnosis of preterm labour is challenging. False-positive diagnoses are common and result in unnecessary, potentially harmful treatments (e.g. tocolytics, antenatal corticosteroids and magnesium sulphate) and costly hospital admissions. Measurement of fetal fibronectin in vaginal fluid is a biochemical test that can indicate impending preterm birth. OBJECTIVES: To develop an externally validated prognostic model using quantitative fetal fibronectin concentration, in combination with clinical risk factors, for the prediction of spontaneous preterm birth and to assess its cost-effectiveness. DESIGN: The study comprised (1) a qualitative study to establish the decisional needs of pregnant women and their caregivers, (2) an individual participant data meta-analysis of existing studies to develop a prognostic model for spontaneous preterm birth within 7 days in women with symptoms of preterm labour based on quantitative fetal fibronectin and clinical risk factors, (3) external validation of the prognostic model in a prospective cohort study across 26 UK centres, (4) a model-based economic evaluation comparing the prognostic model with qualitative fetal fibronectin, and quantitative fetal fibronectin with cervical length measurement, in terms of cost per QALY gained and (5) a qualitative assessment of the acceptability of quantitative fetal fibronectin. DATA SOURCES/SETTING: The model was developed using data from five European prospective cohort studies of quantitative fetal fibronectin. The UK prospective cohort study was carried out across 26 UK centres. PARTICIPANTS: Pregnant women at 22+0-34+6 weeks' gestation with signs and symptoms of preterm labour. HEALTH TECHNOLOGY BEING ASSESSED: Quantitative fetal fibronectin. MAIN OUTCOME MEASURES: Spontaneous preterm birth within 7 days. RESULTS: The individual participant data meta-analysis included 1783 women and 139 events of spontaneous preterm birth within 7 days (event rate 7.8%). The prognostic model that was developed included quantitative fetal fibronectin, smoking, ethnicity, nulliparity and multiple pregnancy. The model was externally validated in a cohort of 2837 women, with 83 events of spontaneous preterm birth within 7 days (event rate 2.93%), an area under the curve of 0.89 (95% confidence interval 0.84 to 0.93), a calibration slope of 1.22 and a Nagelkerke R2 of 0.34. The economic analysis found that the prognostic model was cost-effective compared with using qualitative fetal fibronectin at a threshold for hospital admission and treatment of ≥ 2% risk of preterm birth within 7 days. LIMITATIONS: The outcome proportion (spontaneous preterm birth within 7 days of test) was 2.9% in the validation study. This is in line with other studies, but having slightly fewer than 100 events is a limitation in model validation. CONCLUSIONS: A prognostic model that included quantitative fetal fibronectin and clinical risk factors showed excellent performance in the prediction of spontaneous preterm birth within 7 days of test, was cost-effective and can be used to inform a decision support tool to help guide management decisions for women with threatened preterm labour. FUTURE WORK: The prognostic model will be embedded in electronic maternity records and a mobile telephone application, enabling ongoing data collection for further refinement and validation of the model. STUDY REGISTRATION: This study is registered as PROSPERO CRD42015027590 and Current Controlled Trials ISRCTN41598423. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 52. See the NIHR Journals Library website for further project information.

Identifying which women with symptoms of labour will give birth early is challenging, so many women unnecessarily receive therapies aimed at preventing complications in preterm birth. A test called quantitative fetal fibronectin, which uses vaginal swab samples, may help to improve the diagnosis of preterm labour. Fetal fibronectin is a protein that is released from the fetal membranes that surround the developing baby in the womb. The lower the concentration of fetal fibronectin, the less likely the occurrence of preterm birth. Our aim was to see if quantitative fetal fibronectin, in combination with some features of pregnancy (e.g. previous pregnancy history and twin pregnancy), can accurately predict preterm birth in women who have symptoms of preterm labour. We asked women, their partners, doctors and midwives what information would be most useful to them, and how this should be presented. We then analysed previous research data; we used quantitative fetal fibronectin and clinical risk factors together to predict the chance of preterm birth. We explored which features could predict preterm birth most effectively while still being good value to the NHS. To ensure that this risk predictor worked in UK populations, we undertook a research study across 26 UK hospitals. Women who had symptoms of preterm labour were invited to participate. We collected information from these women (approximately 3000 women), including quantitative fetal fibronectin results. We found that a risk predictor comprising quantitative fetal fibronectin and four other features performed best at predicting whether or not preterm birth will occur within the next week for women with symptoms of preterm labour, and that this had potential to be clinically useful and cost-effective. The quantitative fetal fibronectin testing process was acceptable to women, and clinicians found the risk predictor useful. We used our findings to develop a risk calculator to help women and clinicians assess how likely preterm birth is, and decide whether or not to start treatment.

Development and validation of a risk prediction model of preterm birth for women with preterm labour symptoms (the QUIDS study): A prospective cohort study and individual participant data meta-analysis.

BACKGROUND: Timely interventions in women presenting with preterm labour can substantially improve health outcomes for preterm babies. However, establishing such a diagnosis is very challenging, as signs and symptoms of preterm labour are common and can be nonspecific. We aimed to develop and externally validate a risk prediction model using concentration of vaginal fluid fetal fibronectin (quantitative fFN), in combination with clinical risk factors, for the prediction of spontaneous preterm birth and assessed its cost-effectiveness. METHODS AND FINDINGS: Pregnant women included in the analyses were 22+0 to 34+6 weeks gestation with signs and symptoms of preterm labour. The primary outcome was spontaneous preterm birth within 7 days of quantitative fFN test. The risk prediction model was developed and internally validated in an individual participant data (IPD) meta-analysis of 5 European prospective cohort studies (2009 to 2016; 1,783 women; mean age 29.7 years; median BMI 24.8 kg/m2; 67.6% White; 11.7% smokers; 51.8% nulliparous; 10.4% with multiple pregnancy; 139 [7.8%] with spontaneous preterm birth within 7 days). The model was then externally validated in a prospective cohort study in 26 United Kingdom centres (2016 to 2018; 2,924 women; mean age 28.2 years; median BMI 25.4 kg/m2; 88.2% White; 21% smokers; 35.2% nulliparous; 3.5% with multiple pregnancy; 85 [2.9%] with spontaneous preterm birth within 7 days). The developed risk prediction model for spontaneous preterm birth within 7 days included quantitative fFN, current smoking, not White ethnicity, nulliparity, and multiple pregnancy. After internal validation, the optimism adjusted area under the curve was 0.89 (95% CI 0.86 to 0.92), and the optimism adjusted Nagelkerke R2 was 35% (95% CI 33% to 37%). On external validation in the prospective UK cohort population, the area under the curve was 0.89 (95% CI 0.84 to 0.94), and Nagelkerke R2 of 36% (95% CI: 34% to 38%). Recalibration of the model's intercept was required to ensure overall calibration-in-the-large. A calibration curve suggested close agreement between predicted and observed risks in the range of predictions 0% to 10%, but some miscalibration (underprediction) at higher risks (slope 1.24 (95% CI 1.23 to 1.26)). Despite any miscalibration, the net benefit of the model was higher than "treat all" or "treat none" strategies for thresholds up to about 15% risk. The economic analysis found the prognostic model was cost effective, compared to using qualitative fFN, at a threshold for hospital admission and treatment of ≥2% risk of preterm birth within 7 days. Study limitations include the limited number of participants who are not White and levels of missing data for certain variables in the development dataset. CONCLUSIONS: In this study, we found that a risk prediction model including vaginal fFN concentration and clinical risk factors showed promising performance in the prediction of spontaneous preterm birth within 7 days of test and has potential to inform management decisions for women with threatened preterm labour. Further evaluation of the risk prediction model in clinical practice is required to determine whether the risk prediction model improves clinical outcomes if used in practice. TRIAL REGISTRATION: The study was approved by the West of Scotland Research Ethics Committee (16/WS/0068). The study was registered with ISRCTN Registry (ISRCTN 41598423) and NIHR Portfolio (CPMS: 31277).

Evaluation of institutional readiness at sites within the UK NHS using a novel advanced therapy medicinal product assessment tool.

Aim: This paper reports on a study to assess institutional readiness (IR) of UK National Health Service sites that form part of the Northern Alliance Advanced Therapy Treatment Centre to deliver advanced therapy medicinal products (ATMPs). The paper discusses the development of an assessment tool to support self-assessment of IR in healthcare institutions. Methods: The tool utilized criteria developed by clinicians to self-assess IR to deliver four classes of ATMP over a series of time points. Each assessment was independently analyzed and validated by independent expert groups. Results & conclusion: The collated results indicated an overall trend toward IR for all classes of ATMP. The study highlighted areas where IR is evidenced, areas where work is ongoing and areas where further work is required to achieve IR. The study also facilitated validation of the IR assessment tool.

Tweetable abstract This paper describes the development of a novel tool for assessment of healthcare institutions' capacity to deliver advanced therapies and use of the tool to evaluate institutional readiness within selected UK National Health Service sites. #advancedtherapies @NAATTC @innovateuk.

Quantitative fibronectin to help decision-making in women with symptoms of preterm labour (QUIDS) part 1: Individual participant data meta-analysis and health economic analysis.

INTRODUCTION: The aim of the QUIDS study is to develop a decision support tool for the management of women with symptoms and signs of preterm labour, based on a validated prognostic model using quantitative fetal fibronectin (qfFN) concentration, in combination with clinical risk factors. METHODS AND ANALYSIS: The study will evaluate the Rapid fFN 10Q System (Hologic, Marlborough, Massachusetts) which quantifies fFN in a vaginal swab. In part 1 of the study, we will develop and internally validate a prognostic model using an individual participant data (IPD) meta-analysis of existing studies containing women with symptoms of preterm labour alongside fFN measurements and pregnancy outcome. An economic analysis will be undertaken to assess potential cost-effectiveness of the qfFN prognostic model. The primary endpoint will be the ability of the prognostic model to rule out spontaneous preterm birth within 7 days. Six eligible studies were identified by systematic review of the literature and five agreed to provide their IPD (n=5 studies, 1783 women and 139 events of preterm delivery within 7 days of testing). ETHICS AND DISSEMINATION: The study is funded by the National Institute of Healthcare Research Health Technology Assessment (HTA 14/32/01). It has been approved by the West of Scotland Research Ethics Committee (16/WS/0068). PROSPERO REGISTRATION NUMBER: CRD42015027590. VERSION: Protocol version 2, date 1 November 2016.

Study protocol: quantitative fibronectin to help decision-making in women with symptoms of preterm labour (QUIDS) part 2, UK Prospective Cohort Study.

INTRODUCTION: The aim of the QUIDS study is to develop a decision support tool for the management of women with symptoms and signs of preterm labour, based on a validated prognostic model using quantitative fetal fibronectin (fFN) concentration, in combination with clinical risk factors. METHODS AND ANALYSIS: The study will evaluate the Rapid fFN 10Q System (Hologic, Marlborough, Massachusetts, USA) which quantifies fFN in a vaginal swab. In QUIDS part 2, we will perform a prospective cohort study in at least eight UK consultant-led maternity units, in women with symptoms of preterm labour at 22+0 to 34+6 weeks gestation to externally validate a prognostic model developed in QUIDS part 1. The effects of quantitative fFN on anxiety will be assessed, and acceptability of the test and prognostic model will be evaluated in a subgroup of women and clinicians (n=30). The sample size is 1600 women (with estimated 96-192 events of preterm delivery within 7 days of testing). Clinicians will be informed of the qualitative fFN result (positive/negative) but be blinded to quantitative fFN result. Research midwives will collect outcome data from the maternal and neonatal clinical records. The final validated prognostic model will be presented as a mobile or web-based application. ETHICS AND DISSEMINATION: The study is funded by the National Institute of Healthcare Research Health Technology Assessment (HTA 14/32/01). It has been approved by the West of Scotland Research Ethics Committee (16/WS/0068). VERSION: Protocol V.2, Date 1 November 2016. TRIAL REGISTRATION NUMBER: ISRCTN 41598423andCPMS: 31277.