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

Author:

Stock Sarah J1ORCID,Horne Margaret1ORCID,Bruijn Merel1ORCID,White Helen2ORCID,Heggie Robert3ORCID,Wotherspoon Lisa4ORCID,Boyd Kathleen3ORCID,Aucott Lorna5ORCID,Morris Rachel K6ORCID,Dorling Jon7ORCID,Jackson Lesley8ORCID,Chandiramani Manju9ORCID,David Anna10ORCID,Khalil Asma11ORCID,Shennan Andrew12ORCID,Baaren Gert-Jan van13ORCID,Hodgetts-Morton Victoria5ORCID,Lavender Tina2ORCID,Schuit Ewoud14ORCID,Harper-Clarke Susan15ORCID,Mol Ben16ORCID,Riley Richard D17ORCID,Norman Jane4ORCID,Norrie John1ORCID

Affiliation:

1. Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK

2. Division of Nursing, Midwifery and Social Work, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

3. Health Economics and Health Technology Assessment, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK

4. Medical Research Council Centre for Reproductive Health, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK

5. Health Services Research Unit, University of Aberdeen, Aberdeen, UK

6. Institute of Applied Health Research, University of Birmingham, Birmingham, UK

7. Department of Neonatology, IWK Health Centre, Halifax, NS, Canada

8. Department of Neonatology, Queen Elizabeth Hospital, Glasgow, UK

9. Department of Obstetrics and Gynaecology, Guy’s and St Thomas’ NHS Foundation Trust, London, UK

10. Elizabeth Garrett Anderson Institute for Women’s Health, University College London, London, UK

11. Department of Fetal Medicine, St George’s Hospital, St George’s, University of London, London, UK

12. Department of Women and Children’s Health, School of Life Course Sciences, King’s College London, London, UK

13. Department of Obstetrics and Gynaecology, Amsterdam University Medical Center, Amsterdam, the Netherlands

14. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands

15. Public and patient representative, Teddington, UK

16. Department of Obstetrics and Gynaecology, Monash University, Melbourne, VIC, Australia

17. Centre for Prognosis Research, Research Institute for Primary Care and Health Sciences, Keele University, Keele, UK

Abstract

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 R 2 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.

Funder

Health Technology Assessment programme

Publisher

National Institute for Health Research

Subject

Health Policy

Reference99 articles.

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