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

Sarah J Stock, Lisa M Wotherspoon, Kathleen A Boyd, Rachel K Morris, Jon Dorling, Lesley Jackson, Manju Chandiramani, Anna L David, Asma Khalil, Andrew Shennan, Victoria Hodgetts Morton, Tina Lavender, Khalid Khan, Susan Harper-Clarke, Ben W Mol, Richard D Riley, John Norrie, Jane E Norman

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Abstract

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.

Original languageEnglish
Article numbere020796
JournalBMJ open
Volume8
Issue number4
DOIs
Publication statusPublished - 7 Apr 2018

Keywords

  • Journal Article

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