Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials irrespective of their publication status (trials may be unpublished or published as an article, an abstract, or a letter), language and country. No limits will be applied with respect to period of follow-up. We will exclude quasi-randomised trials. Trials using a cluster-randomised or cross-over design will be excluded.
Types of participants
Pregnant women of any age, at any stage of pregnancy diagnosed with gonococcal infection (genital, extragenital or both).
Types of interventions
We will include comparative trials of antibiotics (used either alone or in combination), administered parenterally or orally, or both, and compared with another antibiotic.
Types of outcome measures
Cure of gonococcal infection (genital, extragenital or both), according to the definition in included trials
Incidence of obstetric complications (miscarriage, premature rupture of membranes, preterm delivery and fetal death
Incidence of disseminated gonococcal infection
Failure to eradicate gonorrhoea from the genital tract of treated mothers.
Adverse events including treatment-related adverse events (TRAE) (Ioannidis 2004). TRAE will be defined as: “a response to a drug which is noxious and uninitiated and which occurs at doses normally used in man for prophylaxis, diagnosis, or therapy of disease, or for the modification of physiologic functions” (Nebeker 2004). We will extract the number of patients with at least one treatment-related adverse event out of the total randomised in each study arm.
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:
monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);
weekly searches of MEDLINE;
weekly searches of Embase;
handsearches of 30 journals and the proceedings of major conferences;
weekly current awareness alerts for a further 44 journals plus monthly BioMed Central email alerts.
Details of the search strategies for CENTRAL, MEDLINE and Embase, the list of handsearched journals and conference proceedings, and the list of journals reviewed via the current awareness service can be found in the ‘Specialized Register’ section within the editorial information about the Cochrane Pregnancy and Childbirth Group.
Trials identified through the searching activities described above are each assigned to a review topic (or topics). The Trials Search Co-ordinator searches the register for each review using the topic list rather than keywords.
In addition, we will search the following databases using the search terms listed in Appendix 2.
The WHO International Clinical Trials Registry Platform (ICTRP)
The metaRegister of Controlled Trials (mRCT)
Searching other resources
We will handsearch the references of all identified included trials, of relevant review articles and of current treatment guidelines.
We will not apply any language restrictions.
Data collection and analysis
Selection of studies
All three review authors will independently assess for inclusion all the potential studies we identify as a result of the search strategy. We will resolve any disagreement through discussion or, if required, we will consult another person.
Data extraction and management
We will design a form to extract data. For eligible studies, all three review authors will extract the data using the agreed form. We will resolve any disagreement through discussion or, if required, we will consult another person. We will enter data into Review Manager software (RevMan 2014) and check for accuracy.
When information regarding any of the above is unclear, we will attempt to contact authors of the original reports to provide further details.
Assessment of risk of bias in included studies
All three review authors will independently assess risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will resolve any disagreement by discussion or by involving a third assessor as specified above.
(1) Random sequence generation (checking for possible selection bias)
We will describe for each included study the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.
We will assess the method as:
low risk of bias (any truly random process, e.g. random number table; computer random number generator);
high risk of bias (any non-random process, e.g. odd or even date of birth; hospital or clinic record number);
unclear risk of bias.
(2) Allocation concealment (checking for possible selection bias)
We will describe for each included study the method used to conceal allocation to interventions prior to assignment and will assess whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.
We will assess the methods as:
low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes);
high risk of bias (open random allocation; unsealed or non-opaque envelopes, alternation; date of birth);
unclear risk of bias.
(3.1) Blinding of participants and personnel (checking for possible performance bias)
We will describe for each included study the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We will consider that studies are at low risk of bias if they were blinded, or if we judge that the lack of blinding would be unlikely to affect results. We will assess blinding separately for different outcomes or classes of outcomes.
We will assess the methods as:
low, high or unclear risk of bias for participants;
low, high or unclear risk of bias for personnel.
(3.2) Blinding of outcome assessment (checking for possible detection bias)
We will describe for each included study the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received. We will assess blinding separately for different outcomes or classes of outcomes.
We will assess methods used to blind outcome assessment as:
(4) Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data)
We will describe for each included study, and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We will state whether attrition and exclusions were reported and the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information is reported, or can be supplied by the trial authors, we will re-include missing data in the analyses which we undertake.
We will assess methods as:
low risk of bias (e.g. no missing outcome data; missing outcome data balanced across groups);
high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; ‘as treated’ analysis done with substantial departure of intervention received from that assigned at randomisation);
unclear risk of bias.
(5) Selective reporting (checking for reporting bias)
We will describe for each included study how we investigated the possibility of selective outcome reporting bias and what we found.
We will assess the methods as:
low risk of bias (where it is clear that all of the study’s pre-specified outcomes and all expected outcomes of interest to the review have been reported);
high risk of bias (where not all the study’s pre-specified outcomes have been reported; one or more reported primary outcomes were not pre-specified; outcomes of interest are reported incompletely and so cannot be used; study fails to include results of a key outcome that would have been expected to have been reported);
unclear risk of bias.
(6) Other bias (checking for bias due to problems not covered by (1) to (5) above)
We will describe for each included study any important concerns we have about other possible sources of bias.
We will assess whether each study was free of other problems that could put it at risk of bias:
(7) Overall risk of bias
We will make explicit judgements about whether studies are at high risk of bias, according to the criteria given in the Handbook (Higgins 2011). With reference to (1) to (6) above, we will assess the likely magnitude and direction of the bias and whether we consider it is likely to impact on the findings. We will explore the impact of the level of bias through undertaking sensitivity analyses - see Sensitivity analysis.
Measures of treatment effect
For dichotomous data, we will present results as summary risk ratio with 95% confidence intervals.
Dealing with missing data
For included studies, we will note levels of attrition. We will explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.
For all outcomes, we will carry out analyses, as far as possible, on an intention-to-treat basis, i.e. we will attempt to include all participants randomised to each group in the analyses, and all participants will be analysed in the group to which they were allocated, regardless of whether or not they received the allocated intervention. The denominator for each outcome in each trial will be the number randomised minus any participants whose outcomes are known to be missing.
Assessment of heterogeneity
We will assess statistical heterogeneity in each meta-analysis using the T², I² and Chi² statistics. We will regard heterogeneity as substantial if an I² is greater than 30% and either the T² is greater than zero, or there is a low P value (less than 0.10) in the Chi² test for heterogeneity.
Assessment of reporting biases
If there are 10 or more studies in the meta-analysis we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it.
We will carry out statistical analysis using the Review Manager software (RevMan 2014). We will use fixed-effect meta-analysis for combining data where it is reasonable to assume that studies are estimating the same underlying treatment effect: i.e. where trials are examining the same intervention, and the trials’ populations and methods are judged sufficiently similar. If there is clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if substantial statistical heterogeneity is detected, we will use random-effects meta-analysis to produce an overall summary, if an average treatment effect across trials is considered clinically meaningful. The random-effects summary will be treated as the average range of possible treatment effects and we will discuss the clinical implications of treatment effects differing between trials. If the average treatment effect is not clinically meaningful, we will not combine trials.
If we use random-effects analyses, the results will be presented as the average treatment effect with 95% confidence intervals, and the estimates of T² and I².
Summary of findings
We will use the principles of the GRADE system (Guyatt 2008) to assess the quality of the body of evidence associated with all main outcomes: (cure of gonococcal infection (genital, extragenital or both); incidence of obstetric complications (miscarriage, preterm rupture of membranes, preterm delivery and fetal death); incidence of disseminated gonococcal infection; and incidence of neonatal ophthalmia neonatorum); and harms. We will construct a 'Summary of findings' table using the GRADE profiler software (GRADEpro 2008). The GRADE approach appraises the quality of a body of evidence based on the extent to which one can be confident that an estimate of effect or association reflects the item being assessed. Evaluation of the quality of a body of evidence considers within-study risk of bias, the directness of the evidence, heterogeneity in the data, precision of effect estimates and risk of publication bias (Balshem 2011; Guyatt 2011a; Guyatt 2011b; Guyatt 2011c; Guyatt 2011d; Guyatt 2011e; Guyatt 2011f; Guyatt 2011g).
Subgroup analysis and investigation of heterogeneity
If we identify substantial heterogeneity, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random-effects analysis to produce it.
We plan to carry out the following subgroup analyses.
Adolescent pregnant women versus non-adolescent pregnant women
Pregnant women with HIV-AIDS infection versus pregnant women without HIV/AIDS
Pregnant women with co-sexual transmitted infections versus pregnant women without co-sexual transmitted infections
Neonatorum ophthalmia in the babies of women who received prophylaxis versus those who did not receive prophylaxis
Subgroup analysis will be restricted the review's primary outcomes.
We will assess subgroup differences by interaction tests available within RevMan (RevMan 2014). We will report the results of subgroup analyses quoting the χ2 statistic and P value, and the interaction test I² value.
We will perform sensitivity analysis based on trial quality, separating high-quality trials from those of low quality. Furthermore, we plan to conduct a sensitivity analysis to assess attrition bias: trials with low attrition bias (≤ 12% loss of follow-up) versus trials with high attrition bias (> 12% of follow-up).
We will also conduct a trial sequential analysis (TSA), which is a methodology that combines an information size calculation (cumulated sample sizes of included trials) for meta-analysis with the threshold of statistical significance. TSA is a tool for quantifying the statistical reliability of data in a cumulative meta-analysis adjusting P values for repetitive testing on accumulating data. We will conduct a TSA on binary outcomes (Brok 2009; Pogue 1997; Pogue 1998; Thorlund 2009; Wetterslev 2008; Wetterslev 2009). Meta-analysis may result in type I errors due to sparse data or due to repeated significance testing when updating meta-analysis with new trials (Brok 2009; Higgins 2011a; Wetterslev 2008). In a single trial, interim analysis increases the risk of type I errors. To avoid type I errors, group sequential monitoring boundaries are applied to decide whether a trial could be terminated early because of a sufficiently small P value, that is, the cumulative Z-curve crosses the monitoring boundaries (Lan 1983). Sequential monitoring boundaries can be applied to meta-analysis as well, called trial sequential monitoring boundaries (Wetterslev 2008; Wetterslev 2009). In TSA, the addition of each trial in a cumulative meta-analysis is regarded as an interim meta-analysis and helps to clarify whether additional trials are needed.The idea in TSA is that if the cumulative Z-curve crosses the boundary, a sufficient level of evidence is reached and no further trials may be needed. If the Z-curve does not cross the boundary then there is insufficient evidence to reach a conclusion. To construct the trial sequential monitoring boundaries, the required information size is needed and is calculated as the least number of participants needed in a well-powered single trial (Brok 2009; Pogue 1997; Pogue 1998; Wetterslev 2008). We will apply TSA since it prevents an increase of the risk of type I error (less than 5%) due to potential multiple updating in a cumulative meta-analysis, and provides us with important information in order to estimate the level of evidence of the experimental intervention.
Additionally, TSA provides us with important information regarding the need for additional trials and the required sample size of such trials. We will apply trial sequential monitoring boundaries according to a heterogeneity-adjusted required information size based on an a priori 10% relative risk reduction (RRR) (APHIS) employing α = 0.05 and ß = 0.20.
TAS will be conducted using the TSA software (CTU 2011; Thorlund 2011).