Progestogens to prevent preterm birth in twin pregnancies: An individual participant data meta-analysis of randomized trials

Ewoud Schuit, Sarah Stock, Rolf H H Groenwold, Kimberly Maurel, C. Andrew Combs, Thomas Garite, Cathy Y. Spong, Elizabeth A. Thom, Dwight J. Rouse, Steve N. Caritis, George Saade, Julia M. Zachary, Jane E. Norman, Line Rode, Katharina Klein, Ann Tabor, Elçin Çetingöz, John C. Morrison, Everett F. Magann, Christian M. BrieryVicente Serra, Alfredo Perales, Juan Meseguer, Anwar H. Nassar, Arianne C. Lim, Karel G M Moons, Anneke Kwee, Ben Willem J Mol

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Background: Preterm birth is the principal factor contributing to adverse outcomes in multiple pregnancies. Randomized controlled trials of progestogens to prevent preterm birth in twin pregnancies have shown no clear benefits. However, individual studies have not had sufficient power to evaluate potential benefits in women at particular high risk of early delivery (for example, women with a previous preterm birth or short cervix) or to determine adverse effects for rare outcomes such as intrauterine death.Methods/design: We propose an individual participant data meta-analysis of high quality randomized, double-blind, placebo-controlled trials of progestogen treatment in women with a twin pregnancy. The primary outcome will be adverse perinatal outcome (a composite measure of perinatal mortality and significant neonatal morbidity). Missing data will be imputed within each original study, before data of the individual studies are pooled. The effects of 17-hydroxyprogesterone caproate or vaginal progesterone treatment in women with twin pregnancies will be estimated by means of a random effects log-binomial model. Analyses will be adjusted for variables used in stratified randomization as appropriate. Pre-specified subgroup analysis will be performed to explore the effect of progestogen treatment in high-risk groups.Discussion: Combining individual patient data from different randomized trials has potential to provide valuable, clinically useful information regarding the benefits and potential harms of progestogens in women with twin pregnancy overall and in relevant subgroups.

Original languageEnglish (US)
Article number13
JournalBMC Pregnancy and Childbirth
Volume12
DOIs
StatePublished - Mar 15 2012

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Twin Pregnancy
Premature Birth
Progestins
Meta-Analysis
17-alpha-Hydroxyprogesterone
Multiple Pregnancy
Perinatal Mortality
Statistical Models
Random Allocation
Cervix Uteri
Progesterone
Therapeutics
Randomized Controlled Trials
Placebos
Morbidity

ASJC Scopus subject areas

  • Obstetrics and Gynecology

Cite this

Progestogens to prevent preterm birth in twin pregnancies : An individual participant data meta-analysis of randomized trials. / Schuit, Ewoud; Stock, Sarah; Groenwold, Rolf H H; Maurel, Kimberly; Combs, C. Andrew; Garite, Thomas; Spong, Cathy Y.; Thom, Elizabeth A.; Rouse, Dwight J.; Caritis, Steve N.; Saade, George; Zachary, Julia M.; Norman, Jane E.; Rode, Line; Klein, Katharina; Tabor, Ann; Çetingöz, Elçin; Morrison, John C.; Magann, Everett F.; Briery, Christian M.; Serra, Vicente; Perales, Alfredo; Meseguer, Juan; Nassar, Anwar H.; Lim, Arianne C.; Moons, Karel G M; Kwee, Anneke; Mol, Ben Willem J.

In: BMC Pregnancy and Childbirth, Vol. 12, 13, 15.03.2012.

Research output: Contribution to journalArticle

Schuit, E, Stock, S, Groenwold, RHH, Maurel, K, Combs, CA, Garite, T, Spong, CY, Thom, EA, Rouse, DJ, Caritis, SN, Saade, G, Zachary, JM, Norman, JE, Rode, L, Klein, K, Tabor, A, Çetingöz, E, Morrison, JC, Magann, EF, Briery, CM, Serra, V, Perales, A, Meseguer, J, Nassar, AH, Lim, AC, Moons, KGM, Kwee, A & Mol, BWJ 2012, 'Progestogens to prevent preterm birth in twin pregnancies: An individual participant data meta-analysis of randomized trials', BMC Pregnancy and Childbirth, vol. 12, 13. https://doi.org/10.1186/1471-2393-12-13
Schuit, Ewoud ; Stock, Sarah ; Groenwold, Rolf H H ; Maurel, Kimberly ; Combs, C. Andrew ; Garite, Thomas ; Spong, Cathy Y. ; Thom, Elizabeth A. ; Rouse, Dwight J. ; Caritis, Steve N. ; Saade, George ; Zachary, Julia M. ; Norman, Jane E. ; Rode, Line ; Klein, Katharina ; Tabor, Ann ; Çetingöz, Elçin ; Morrison, John C. ; Magann, Everett F. ; Briery, Christian M. ; Serra, Vicente ; Perales, Alfredo ; Meseguer, Juan ; Nassar, Anwar H. ; Lim, Arianne C. ; Moons, Karel G M ; Kwee, Anneke ; Mol, Ben Willem J. / Progestogens to prevent preterm birth in twin pregnancies : An individual participant data meta-analysis of randomized trials. In: BMC Pregnancy and Childbirth. 2012 ; Vol. 12.
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abstract = "Background: Preterm birth is the principal factor contributing to adverse outcomes in multiple pregnancies. Randomized controlled trials of progestogens to prevent preterm birth in twin pregnancies have shown no clear benefits. However, individual studies have not had sufficient power to evaluate potential benefits in women at particular high risk of early delivery (for example, women with a previous preterm birth or short cervix) or to determine adverse effects for rare outcomes such as intrauterine death.Methods/design: We propose an individual participant data meta-analysis of high quality randomized, double-blind, placebo-controlled trials of progestogen treatment in women with a twin pregnancy. The primary outcome will be adverse perinatal outcome (a composite measure of perinatal mortality and significant neonatal morbidity). Missing data will be imputed within each original study, before data of the individual studies are pooled. The effects of 17-hydroxyprogesterone caproate or vaginal progesterone treatment in women with twin pregnancies will be estimated by means of a random effects log-binomial model. Analyses will be adjusted for variables used in stratified randomization as appropriate. Pre-specified subgroup analysis will be performed to explore the effect of progestogen treatment in high-risk groups.Discussion: Combining individual patient data from different randomized trials has potential to provide valuable, clinically useful information regarding the benefits and potential harms of progestogens in women with twin pregnancy overall and in relevant subgroups.",
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T1 - Progestogens to prevent preterm birth in twin pregnancies

T2 - An individual participant data meta-analysis of randomized trials

AU - Schuit, Ewoud

AU - Stock, Sarah

AU - Groenwold, Rolf H H

AU - Maurel, Kimberly

AU - Combs, C. Andrew

AU - Garite, Thomas

AU - Spong, Cathy Y.

AU - Thom, Elizabeth A.

AU - Rouse, Dwight J.

AU - Caritis, Steve N.

AU - Saade, George

AU - Zachary, Julia M.

AU - Norman, Jane E.

AU - Rode, Line

AU - Klein, Katharina

AU - Tabor, Ann

AU - Çetingöz, Elçin

AU - Morrison, John C.

AU - Magann, Everett F.

AU - Briery, Christian M.

AU - Serra, Vicente

AU - Perales, Alfredo

AU - Meseguer, Juan

AU - Nassar, Anwar H.

AU - Lim, Arianne C.

AU - Moons, Karel G M

AU - Kwee, Anneke

AU - Mol, Ben Willem J

PY - 2012/3/15

Y1 - 2012/3/15

N2 - Background: Preterm birth is the principal factor contributing to adverse outcomes in multiple pregnancies. Randomized controlled trials of progestogens to prevent preterm birth in twin pregnancies have shown no clear benefits. However, individual studies have not had sufficient power to evaluate potential benefits in women at particular high risk of early delivery (for example, women with a previous preterm birth or short cervix) or to determine adverse effects for rare outcomes such as intrauterine death.Methods/design: We propose an individual participant data meta-analysis of high quality randomized, double-blind, placebo-controlled trials of progestogen treatment in women with a twin pregnancy. The primary outcome will be adverse perinatal outcome (a composite measure of perinatal mortality and significant neonatal morbidity). Missing data will be imputed within each original study, before data of the individual studies are pooled. The effects of 17-hydroxyprogesterone caproate or vaginal progesterone treatment in women with twin pregnancies will be estimated by means of a random effects log-binomial model. Analyses will be adjusted for variables used in stratified randomization as appropriate. Pre-specified subgroup analysis will be performed to explore the effect of progestogen treatment in high-risk groups.Discussion: Combining individual patient data from different randomized trials has potential to provide valuable, clinically useful information regarding the benefits and potential harms of progestogens in women with twin pregnancy overall and in relevant subgroups.

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