Open randomised trial of the (Arabin) pessary to prevent preterm birth in twin pregnancy with health economics and acceptability: STOPPIT-2-a study protocol

Jane E. Norman* (Corresponding Author), John Norrie, Graeme Maclennan, David Cooper, Sonia Whyte, Sarah Cunningham Burley, Joel B.E. Smith, Andrew Shennan, Stephen C. Robson, Steven Thornton, Mark D. Kilby, Neil Marlow, Sarah J. Stock, Philip R. Bennett, Jane Denton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
21 Downloads (Pure)

Abstract

Introduction The STOPPIT-2 study aims to determine the clinical utility of the Arabin cervical pessary in preventing preterm birth in women with a twin pregnancy and a short cervix, about which there is current uncertainty. STOPPIT-2 will resolve uncertainty around effectiveness for women with a twin pregnancy and a cervical length of 35 mm or less, define adverse effects, ascertain acceptability and estimate National Health Service costs and savings. Methods STOPPIT-2 is a pragmatic multicentre openlabel randomised controlled trial. Consenting women with twin pregnancy will have an transvaginal ultrasound scan of their cervical length performed between 18+0 and 20+6 weeks' gestation by an accredited practitioner: women with a cervical length of =35 mm will be eligible for inclusion in the treatment phase of the study. The intervention by the insertion of the Arabin cervical pessary will be compared with standard treatment (no pessary). The primary outcomes are (obstetric) spontaneous onset of labour for the mother leading to delivery before 34 weeks' gestation and (neonatal) a composite of specific adverse outcomes or death occurring up to the end of the first 4 weeks after the estimated date of delivery to either or both babies. We plan to recruit 500 women in the treatment phase of the study. Assuming a treatment effect of 0.6, and background rates of 35% and 18%, respectively, for each of the primary outcomes, our study has 85% power to detect a difference between the intervention and the control groups. Analysis Data will be analysed on the intention-to-treat principle. Ethics STOPPIT-2 was approved by the South East Scotland Ethics Committee 02 on 29 August 2014, reference number 14/SS/1031 IRAS ID 159610. Dissemination Peer reviewed journals, presentations at national and international scientific meetings.

Original languageEnglish
Article numbere026430
JournalBMJ Open
Volume8
Issue number12
Early online date6 Dec 2018
DOIs
Publication statusPublished - Feb 2019

Bibliographical note

Contributors All authors contributed to the intellectual content of this protocol. JEN and SW wrote the first draft, with the exception of the statistical analysis plan (which was written by DC, with input from GM and JN), health economics (written by JS) and the qualitative research (written by SCB). All authors contributed to further drafting and approved the final version.
Funding This study was funded by the NIHR Health Technology Assessment Programme (project number 13/04/22).
Disclaimer Department of Health and Social Care disclaimer. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care
Competing interests JEN is a member of the HTA Maternal, Neonatal and Child health prioritisation panel. She has performed consultancy for the pharma companies LifeArc and Dilafor outside the scope of this work. ST provides commercial consultancy advice and is a Trustee or advisor for funding organisations. AS is on the HTA commissioning board and has received funding from Hologic (paid to institution) for preterm prediction studies (outside the scope of this work.)
Patient consent Not required.
Ethics approval STOPPIT-2 was approved by the South East of Scotland Research Ethics Committee 2 on 29th August 2014, reference number 14/SS/1031.
Provenance and peer review Not commissioned; peer reviewed for ethical and funding approval prior to submission.

Keywords

  • twin pregnancy
  • CERVICAL LENGTH
  • WOMEN
  • MULTICENTER
  • PREDICTION

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