Fetal fibronectin testing for reducing the risk of preterm birth
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To assess the effectiveness of management based on fetal fibronectin testing for preventing preterm birth.
Background
Importance of preterm birth
Preterm birth is defined by the World Health Organization as birth between 20 and 36 6/7 weeks. Its incidence is about 5% to 8% in most developed and developing countries. This incidence is increasing in many countries, including developing countries. Preterm birth is the main cause of neonatal morbidity and mortalities in most countries, especially in developed countries. In the USA, 75% of perinatal mortality occurs in preterm babies; more than two thirds of perinatal mortality (60% of total) occurs in less than 32 week infants. Mortality and morbidities are inversely associated with gestational age at birth. Morbidities include respiratory distress syndrome (RDS), bronchopulmonary dysplasia, intraventricular hemorrhage (IVH), necrotizing enterocolitis, sepsis, retinopathy, etc. All members of a family in which a preterm birth occurs suffer greatly, in several aspects, including medically, socially, psychologically, and financially.
Interventions to reduce preterm birth
Despite extensive research efforts, the incidence of preterm birth is increasing in many countries. It has increased to 12.7% in 2005 in the USA (a greater than 20% increase in the last 10 years), representing more than 500,000 births in this nation alone. Preterm birth can be spontaneous, and follow preterm labour (50%), or preterm premature rupture of membranes (30%); or be iatrogenic (20%). The interventions that have been shown to effectively reduce the risk of preterm birth or improve outcomes for babies born preterm in asymptomatic women have been smoking cessation counseling for smokers (Lumley 2004); antibiotics for asymptomatic bacteriuria (Smaill 2007); intramuscular progesterone for women with prior preterm birth now carrying a singleton gestation (Dodd 2006); ultrasound‐indicated cerclage in women with both a prior preterm birth and shortening of cervical length less than 25 mm before 24 weeks in the current singleton pregnancy (Berghella 2005); and history‐indicated cerclage in women with three or more prior preterm births or second trimester losses (Drakeley 2003). In symptomatic women, corticosteroids (betamethasone 12 mg intramuscularly q 24 hours x 2 doses between 24 to 33 6/7 weeks is preferred, if available) given to mother prior to preterm birth are effective in preventing RDS, IVH, and neonatal mortality (Roberts 2006). Cyclo‐oxygenase inhibitors are the only class of primary tocolytics shown to decrease preterm birth before 37 weeks in women with preterm labour compared to placebo, but this effectiveness is based on less than 100 randomized women (King 2005).
Fetal fibronectin to predict and reduce preterm birth
Fetal fibronectin is an extracellular matrix glycoprotein. Fetal fibronectin in biologic fluids is produced by amniocytes and by cytotrophoblast. It is present throughout gestation in all pregnancies. It is not subject to genetic polymorphism. There are very high levels in amniotic fluid (100 µg/mL) in second trimester, and 30 µg/mL at term. It is localized at the maternal‐fetal interface of the amniotic membranes, between chorion and decidua, where it is concentrated in this area between decidua and trophoblast. Here it acts as a 'glue' between the pregnancy and the uterus. Concentration of fetal fibronectin protein found in blood is 1/5 that found in amniotic fluid; it is not present in urine. In normal conditions, this glycoprotein remains in this area between chorion and decidua, and very low levels are found in cervico‐vaginal secretions after 22 weeks (less than 50 ng/mL). Levels above this value (≥ 50 ng/mL) at or after 22 weeks in the cervico‐vaginal secretions collected by a swab have been associated with an increased risk of spontaneous preterm birth. The fetal fibronectin test assesses risk of preterm labour and preterm birth by measuring the amount of fetal fibronectin in cervicovaginal secretions. In fact, fetal fibronectin is one of the best predictors of preterm birth in all populations studied so far, including low‐ and high‐risk women without preterm labour, twins, and women in preterm labour (Leitich 1999). The overall sensitivity and specificity are 56% and 84% for preterm less than 37 weeks, respectively, but vary according to gestational age at collection, population studied, prevalence of preterm birth, single versus multiple screening, etc. (Leitich 1999). Its positive predictive value varies from about 9% to 46% depending on the incidence of preterm labour in the population studies (Leitich 1999). Even at 13 to 22 weeks, higher (using 90th percentile) fetal fibronectin levels are associated with a two‐ to three‐fold increase risk in subsequent spontaneous preterm labour.
Objectives
To assess the effectiveness of management based on fetal fibronectin testing for preventing preterm birth.
Methods
Criteria for considering studies for this review
Types of studies
Published and unpublished randomized controlled trials. We will include quasi‐randomized trials.
Types of participants
Pregnant women between the gestational ages of 22 to 34 weeks screened with fetal fibronectin for risk of preterm birth.
Types of interventions
A screening test such as fetal fibronectin can only be considered effective if interventions based on fetal fibronectin screening results reduce the outcome of preterm birth. Interventions based on fetal fibronectin screening results can also be classified as:
(1) interventions based on knowledge of fetal fibronectin results (eg, fetal fibronectin is collected on all women, but women are randomized so that in 50% of them the result is available to the managing obstetrician, while in 50% the fetal fibronectin is blind to the managing obstetrician; or fetal fibronectin screening is done only on half of the women);
(2) interventions based on positive fetal fibronectin;
(3) interventions based on negative fetal fibronectin.
Types of outcome measures
Primary outcome
(1) Preterm birth (less than 37 weeks)
Secondary outcomes
(1) Preterm birth less than 34 weeks
(2) Preterm birth less than 32 weeks
(3) Preterm birth less than 28 weeks
(4) Gestational age at delivery
(5) Birthweight less than 2500 grams
(6) Perinatal death (fetal death and neonatal death)
(7) Fetal death
(8) Neonatal death
(9) Respiratory distress syndrome
(10) Intraventricular hemorrhage
(11) Necrotizing enterocolitis
(12) Sepsis
(13) Neonatal intensive care unit (NICU) admission
(14) NICU days
(15) Maternal hospitalization
(16) Maternal well‐being (eg, stress level, etc)
(17) Economic analysis (cost effectiveness, cost utility)
(18) Unnecessary interventions
(19) Predictive accuracy of fetal fibronectin screening (sensitivity, specificity, positive and negative predictive values, relative risk and 95% confidence interval, likelihood ratios)
Search methods for identification of studies
We will contact the Trials Search Co‐ordinator to search the Cochrane Pregnancy and Childbirth Group's Trials Register.
The Cochrane Pregnancy and Childbirth Group's Trials Register is maintained by the Trials Search Co‐ordinator and contains trials identified from:
(1) quarterly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);
(2) monthly searches of MEDLINE;
(3) handsearches of 30 journals and the proceedings of major conferences;
(4) weekly current awareness search of a further 36 journals plus monthly BioMed Central email alerts.
Details of the search strategies for CENTRAL and MEDLINE, the list of handsearched journals and conference proceedings, and the list of journals reviewed via the current awareness service can be found in the 'Search strategies for identification of studies' section within the editorial information about the Cochrane Pregnancy and Childbirth Group.
Trials identified through the searching activities described above are given a code (or codes) depending on the topic. The codes are linked to review topics. The Trials Search Co‐ordinator searches the register for each review using these codes rather than keywords.
In addition, we will search MEDLINE (January 1966 to current) using the following strategy:
#1 exp Obstetric labor, premature/
#2 Fibronectins/
#3 #1 and #2
#4 fetal adj3 fibronectin
#5 #3 or #4
We will review the reference list of all articles, in particular trials and review articles. If necessary, we will contact researchers to provide further information. We will contact experts in the field for additional and ongoing trials.
We will not apply any language restrictions.
Data collection and analysis
Selection of studies
We will assess for inclusion all potential studies we identify as a result of the search strategy. Independently, three review authors (V Berghella (VB), J Visintine (JV), T Hayes (TH)) will assess all studies for inclusion in the review using the inclusion criteria. We will resolve any disagreement through discussion or, if required, consult a fourth author (J Baxter (JB)).
Data extraction and management
We will design a form to extract data. Three authors (VB, TH, JV) will extract the data using the agreed form. We will resolve any disagreement through discussion or, if required, consult a fourth author (JB). We will use the Review Manager software (RevMan 2003) to double enter all the data or a subsample.
When information regarding any of the above is unclear, or to obtain additional data not published, we will attempt to contact authors of the original reports to provide further details.
Assessment of methodological quality of included studies
We will assess the validity of each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2005). Methods used for generation of the randomization sequence will be described for each trial.
(1) Selection bias (allocation concealment)
We will assign a quality score for each trial, using the following criteria:
(A) adequate concealment of allocation: such as telephone randomization, consecutively‐numbered, sealed opaque envelopes;
(B) unclear whether adequate concealment of allocation: such as list or table used, sealed envelopes, or study does not report any concealment approach;
(C) inadequate concealment of allocation: such as open list of random‐number tables, use of case record numbers, dates of birth or days of the week.
(2) Attrition bias (loss of participants, for example, withdrawals, dropouts, protocol deviations)
We will assess completeness to follow up using the following criteria:
(A) less than 5% loss of participants;
(B) 5% to 9.9% loss of participants;
(C) 10% to 19.9% loss of participants;
(D) more than 20% loss of participants.
(3) Performance bias (blinding of participants, researchers and outcome assessment)
We will assess blinding using the following criteria:
(1) blinding of participants (yes/no/unclear);
(2) blinding of caregiver (yes/no/unclear);
(3) blinding of outcome assessment (yes/no/unclear).
Measures of treatment effect
We will carry out statistical analysis using the Review Manager software (RevMan 2003). We will use fixed‐effect meta‐analysis for combining data in the absence of significant heterogeneity if trials are sufficiently similar. If heterogeneity is found, this will be explored by sensitivity analysis followed by random‐effects if required.
Dichotomous data
For dichotomous data, we will present results as summary relative risk with 95% confidence intervals.
Continuous data
For continuous data, we will use the weighted mean difference if outcomes are measured in the same way between trials. We will use the standardized mean difference to combine trials that measure the same outcome, but use different methods. If there is evidence of skewness, this will be reported.
Unit of analysis issues
Cluster‐randomized trials
We will include cluster‐randomized trials in the analyses along with individually randomized trials. Their sample sizes will be adjusted using the methods described in Gates 2005 using an estimate of the intracluster correlation co‐efficient (ICC) derived from the trial (if possible), or from another source. If ICCs from other sources are used, this will be reported and sensitivity analyses conducted to investigate the effect of variation in the ICC. If we identify both cluster‐randomized trials and individually randomized trials, we plan to synthesise the relevant information. We will consider it reasonable to combine the results from both if there is little heterogeneity between the study designs and the interaction between the effect of intervention and the choice of randomization unit is considered to be unlikely.
We will also acknowledge heterogeneity in the randomization unit and perform a separate meta‐analysis; therefore, the meta‐analysis will be performed in two parts as well.
Dealing with missing data
We will analyse data on all participants with available data in the group to which they are allocated, regardless of whether or not they received the allocated intervention. If in the original reports participants are not analysed in the group to which they were randomized, and there is sufficient information in the trial report, we will attempt to restore them to the correct group.
Assessment of heterogeneity
We will apply tests of heterogeneity between trials, if appropriate, using the I‐squared statistic. If we identify high levels of heterogeneity among the trials (exceeding 50%), we will explore it by prespecified subgroup analysis and perform sensitivity analysis. A random‐effects meta‐analysis will be used as an overall summary if this is considered appropriate.
Subgroup analyses
We will conduct planned subgroup analyses classifying whole trials by interaction tests as described by Deeks 2001. We plan to carry out the following group analyses:
(1) asymptomatic compared with signs and symptoms of preterm labour;
(2) low‐risk singleton gestations compared with high‐risk (eg, prior preterm labour) singleton gestations;
(3) singleton pregnancies compared with multiple gestations;
(4) timing of availability of results;
(5) gestational age at collection of fetal fibronectin (22 to 23, 24 to 28, more than 28 weeks).
Sensitivity analyses
We will carry out sensitivity analysis to explore the effect of trial quality. This will involve analysis based on an A, B, C, or D rating of selection bias and attrition bias. Studies of poor quality will be excluded in the analysis (those rating B, C, or D) in order to assess for any substantive difference to the overall result.
We will carry out sensitivity analysis to explore the effect of trial quality assessed by concealment of allocation, by excluding studies with clearly inadequate allocation of concealment (rated C).
If quasi‐randomized trials are included in the review a sensitivity analysis by trial quality will be performed.
