{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T16:44:36Z","timestamp":1782319476396,"version":"3.54.5"},"reference-count":99,"publisher":"National Institute for Health and Care Research","issue":"52","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.nationalarchives.gov.uk\/doc\/non-commercial-government-licence\/non-commercial-government-licence.htm"}],"funder":[{"DOI":"10.13039\/501100000664","name":"Health Technology Assessment programme","doi-asserted-by":"publisher","award":["14\/32\/01"],"award-info":[{"award-number":["14\/32\/01"]}],"id":[{"id":"10.13039\/501100000664","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journalslibrary.nihr.ac.uk"],"crossmark-restriction":false},"short-container-title":["Health Technol Assess"],"abstract":"\n Background<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Objectives<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Design<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Data sources\/setting<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Participants<\/jats:title>\n Pregnant women at 22+0<\/jats:sup>\u201334+6<\/jats:sup> weeks\u2019 gestation with signs and symptoms of preterm labour.<\/jats:p>\n <\/jats:sec>\n \n Health technology being assessed<\/jats:title>\n Quantitative fetal fibronectin.<\/jats:p>\n <\/jats:sec>\n \n Main outcome measures<\/jats:title>\n Spontaneous preterm birth within 7 days.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n 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<\/jats:italic>\n 2<\/jats:sup> 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 \u2265\u20092% risk of preterm birth within 7 days.<\/jats:p>\n <\/jats:sec>\n \n Limitations<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Future work<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Study registration<\/jats:title>\n This study is registered as PROSPERO CRD42015027590 and Current Controlled Trials ISRCTN41598423.<\/jats:p>\n <\/jats:sec>\n \n Funding<\/jats:title>\n 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<\/jats:italic>; Vol. 25, No. 52. See the NIHR Journals Library website for further project information.<\/jats:p>\n <\/jats:sec>","DOI":"10.3310\/hta25520","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T14:15:19Z","timestamp":1631110519000},"page":"1-168","update-policy":"https:\/\/doi.org\/10.3310\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":9,"title":["A prognostic model, including quantitative fetal fibronectin, to predict preterm labour: the QUIDS meta-analysis and prospective cohort study"],"prefix":"10.3310","volume":"25","clinical-trial-number":[{"clinical-trial-number":"isrctn41598423","registry":"10.18810\/isrctn","type":"results"}],"author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4308-856X","authenticated-orcid":true,"given":"Sarah J","family":"Stock","sequence":"first","affiliation":[{"name":"Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, 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