Suppr超能文献

评估孕激素预防早产国际协作组(EPPPIC)个体参与者数据(IPD)荟萃分析:方案。

Evaluating progestogens for prevention of preterm birth international collaborative (EPPPIC) individual participant data (IPD) meta-analysis: protocol.

机构信息

Centre for Reviews and Dissemination, University of York, Heslington, York, YO10 5DD, UK.

Nottingham Clinical Trials Unit Queen's Medical Centre, University of Nottingham, Nottingham, NG7 2UH, UK.

出版信息

Syst Rev. 2017 Nov 28;6(1):235. doi: 10.1186/s13643-017-0600-x.

Abstract

BACKGROUND

Preterm birth is the most common cause of death and harm to newborn babies. Babies that are born early may have difficulties at birth and experience health problems during early childhood. Despite extensive study, there is still uncertainty about the effectiveness of progestogen (medications that are similar to the natural hormone progesterone) in preventing or delaying preterm birth, and in improving birth outcomes. The Evaluating Progestogen for Prevention of Preterm birth International Collaborative (EPPPIC) project aims to reduce uncertainty about the specific conditions in which progestogen may (or may not) be effective in preventing or delaying preterm birth and improving birth outcomes.

METHODS

The design of the study involves international collaborative individual participant data meta-analysis comprising systematic review, re-analysis, and synthesis of trial datasets. Inclusion criteria are as follows: randomized controlled trials comparing progestogen versus placebo or non-intervention, or comparing different types of progestogen, in asymptomatic women at risk of preterm birth. Main outcomes are as follows; fetal/infant death, preterm birth or fetal death (<=37 weeks, <=34 weeks, <= 28 weeks), serious neonatal complications or fetal/infant death, neurosensory disability (measured at 18 months or later) or infant/child death, important maternal morbidity, or maternal death. In statistical methods, IPD will be synthesized across trials using meta-analysis. Both 'two-stage' models (where effect estimates are calculated for each trial and subsequently pooled in a meta-analysis) and 'one-stage' models (where all IPD from all trials are analyzed in one step, while accounting for the clustering of participants within trials) will be used. If sufficient suitable data are available, a network meta-analysis will compare all types of progesterone and routes of administration extending the one-stage models to include multiple treatment arms.

DISCUSSION

EPPPIC is an international collaborative project being conducted by the forming EPPPIC group, which includes trial investigators, an international secretariat, and the research project team. Results, which are intended to contribute to improvements in maternal and child health, are expected to be publicly available in mid 2018.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017068299.

摘要

背景

早产是新生儿死亡和发病的最常见原因。早产儿在出生时可能会遇到困难,并在幼儿期出现健康问题。尽管进行了广泛的研究,但孕激素(与天然激素黄体酮相似的药物)在预防或延迟早产以及改善分娩结局方面的有效性仍存在不确定性。预防早产的孕激素评估国际合作(EPPPIC)项目旨在减少关于孕激素在预防或延迟早产以及改善分娩结局方面可能(或可能不)有效的具体情况的不确定性。

方法

该研究的设计包括国际合作的个体参与者数据荟萃分析,包括系统评价、重新分析和试验数据集的综合。纳入标准如下:比较孕激素与安慰剂或非干预措施,或比较不同类型孕激素在有早产风险的无症状妇女中的随机对照试验。主要结局如下:胎儿/婴儿死亡、早产或胎儿死亡(<=37 周、<=34 周、<=28 周)、严重新生儿并发症或胎儿/婴儿死亡、神经感觉障碍(在 18 个月或以后测量)或婴儿/儿童死亡、重要的产妇发病率或产妇死亡。在统计方法中,将使用荟萃分析对来自各试验的 IPD 进行综合。将使用“两阶段”模型(其中为每个试验计算效应估计值,然后在荟萃分析中进行汇总)和“一阶段”模型(其中所有来自所有试验的 IPD 一步分析,同时考虑到试验内参与者的聚类)。如果有足够的合适数据,将进行网络荟萃分析,比较所有类型的孕激素和给药途径,将一阶段模型扩展到包括多个治疗臂。

讨论

EPPPIC 是由正在组建的 EPPPIC 小组进行的国际合作项目,该小组包括试验研究者、国际秘书处和研究项目团队。预计将于 2018 年年中公布有助于改善母婴健康的结果。

系统评价登记

PROSPERO CRD42017068299。

相似文献

9
Antiplatelet agents for preventing pre-eclampsia and its complications.用于预防子痫前期及其并发症的抗血小板药物。
Cochrane Database Syst Rev. 2019 Oct 30;2019(10):CD004659. doi: 10.1002/14651858.CD004659.pub3.

引用本文的文献

6
Spontaneous premature birth as a target of genomic research.自发性早产作为基因组研究的目标。
Pediatr Res. 2019 Mar;85(4):422-431. doi: 10.1038/s41390-018-0180-z. Epub 2018 Sep 18.

本文引用的文献

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验