Types of studies

Randomised controlled trials (RCTs) and quasi‐RCTs. We will assess quasi‐RCTs on their merit using the Cochrane risk of bias tool and if the reviewers are satisfied that the groups were similar at baseline, we will include them. We will also assess cross‐over trials for possible inclusion on an individual basis. If we deem the treatment to alter the condition to the extent that, on entry to subsequent phases, the participants differ from their initial state, we will exclude the trial unless we can use data from the first phase only (see Unit of analysis issues).

Types of participants

Children, young people and adults with CF (diagnosed with confirmed sweat test or mutation analysis, or both) who also have a confirmed diagnosis of complete or incomplete DIOS (diagnosed clinically or radiologically). We will include both individuals who are pancreatic sufficient and those who are pancreatic insufficient.

Types of interventions

We will compare each type of pharmacological intervention (osmotic laxatives, stimulant laxatives, mucolytics and other laxative agents) or surgery used for the treatment of DIOS in children, young people and adults with CF to each other, placebo or non‐intervention.

Types of outcome measures

Electronic searches

The authors will identify relevant studies from the Group's Cystic Fibrosis Trials Register using the term: distal intestinal obstruction syndrome (DIOS)

The Cystic Fibrosis Trials Register is compiled from electronic searches of the Cochrane Central Register of Controlled Trials (CENTRAL) (updated each new issue of The Cochrane Library), weekly searches of MEDLINE, a search of Embase to 1995 and the prospective handsearching of two journals ‐ Pediatric Pulmonology and the Journal of Cystic Fibrosis. Unpublished work is identified by searching the abstract books of three major cystic fibrosis conferences: the International Cystic Fibrosis Conference; the European Cystic Fibrosis Conference and the North American Cystic Fibrosis Conference. For full details of all searching activities for the register, please see the relevant sections of the Cochrane Cystic Fibrosis and Genetic Disorders Group's website.

We will search the following databases:

• Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library www.thecochranelibrary.com;

• MEDLINE Ovid (1946 onwards);

• Embase HDAS (Healthcare Databases Advanced Search) (1974 onwards).

We will also search the following trials registries and other resources:

• US National Institutes of Health Ongoing Trials Register Clinicaltrials.gov (www.clinicaltrials.gov);

• International Standard Randomised Controlled Trial Number (ISRCTN) Registry (www.isrctn.com );

• World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (apps.who.int/trialsearch);

• Open Grey (www.opengrey.eu/).

For details of our search strategies, please see the appendices (Appendix 2).

Searching other resources

We will check the bibliographies of included trials and any relevant systematic reviews identified for further references to relevant trials.

Selection of studies

Once we have the complete list of identified references, one author (JG) will check for duplicates and remove them. Two authors (JG and FG) will then review all titles and abstracts and discard references which clearly do not meet the inclusion criteria. We will attempt to resolve any disagreements by discussion, but if we can not reach a decision, the third author (WC) will act as an external arbiter to mediate until we can reach a final conclusion. Once we have discarded trials on the basis of title and abstract, we will obtain full copies of the remaining references and screen these using a standardised screening form customised for this review.

We will consider trials in any language and will translate them as necessary. We will include trials published as full texts; if there is only an abstract available, we will include it if it presents results. If there are no results presented within the abstract or on any trials registry sites, then we will classify the trial as 'Awaiting assessment' until more information is available. Similarly with ongoing trials, if a trial meets our inclusion criteria and quality assessment then we will include it.

We will present the results of the search using a standardised flow chart.

Data extraction and management

Two authors (JG and FG) will independently perform data extraction for the included trials. Data extraction is a significant part of a Cochrane Review, as authors must collect important information from each of the included trials and record the data on a detailed form. We plan to collect data using the data extraction forms on Covidence, an online software program that provides detailed data extraction forms for Cochrane reviews (Covidence 2017). We will collect data on:

• participant characteristics;

• trial characteristics and trial design;

• intervention and comparator;

• outcome data ‐ we will report data for each outcome separately.

One author (JG) will check the two independently completed data extraction forms for discrepancies and if there are any which we can not resolve by discussion, the third author (WC) will arbitrate.

We will enter the data extracted into Review Manager software for analysis (RevMan 2014). We plan to report data at up to one week, up to two weeks, up to one month, up to three months, up to six months and up to one year. If data are reported at other time points we will consider reporting these too. We will initially carry out a comparison of any osmotic agents, stimulant laxatives or mucolytics versus placebo or usual treatment with further subgroup analyses planned as data allow (see below).

Assessment of risk of bias in included studies

We will use the risk of bias tool as described in the Cochrane Handbook for Systematic Reviews of Interventions to assess the risk of bias across six domains (sequence generation, allocation concealment, blinding, incomplete outcome data, selective reporting and other potential sources of bias) (Higgins 2011).

If the trial describes methods of randomisation in the allocation of participants to their intervention groups, we will rank this domain (sequence generation) as having a low risk of bias. We will also look for methods of concealment of the allocation sequence from the researchers, and we deem these to be adequate, then we will rank the trial as having a low risk of bias for this domain. Where these are inadequate, we will rank the trial as being at a high risk and where it is unclear from the description given, then we will rank it as having an unclear risk of bias.

Similarly for blinding, the trial should state that participants and personnel were blinded, in order to have a low risk of bias for this domain. We will also look for the blinding of outcome assessors, which should be specifically mentioned for the rank of low risk of bias.

For the domain of incomplete outcome data, we will extract information on missing data and how the investigators recorded participant withdrawals and loss to follow up. We will also look at whether missing data were equally distributed between the intervention and control groups. If the review authors agree that missing data have been accounted for adequately, then we will judge the trial to be at a low risk of bias. We will record the trial as having a high risk of bias if the missing data have not been reported adequately and will record it as having an unclear risk of bias if we are unable to see how the missing data have been reported. The authors will assess each included trial to determine whether the investigators used an intention‐to‐treat (ITT) analysis and again, once we have reached an agreement, we will rank the trials as being at a high, low or unclear risk of bias.

If the trial investigators report all outcomes in the paper, the review authors will record a low risk of bias from selective reporting. If the paper states that investigators measured outcomes, but they do not report the results of these, the review authors will rank the paper as being at high risk. If it is unclear to the review authors whether the trial reports all outcomes measured, then we will state this and rank it as unclear for this domain. We will search for trial protocols to be able to assess outcome reporting. If we can not locate the protocol, we will assess outcome reporting based on a comparison between the methods section of the full published paper and the results section.

The review authors will look for any other potential sources of bias in the included trials and will record what they find. If the authors cannot find any other source of bias, then we will rank the trial as having a low risk for this domain and high risk if the opposite is true.

We will present the results of the risk of bias assessment both individually and in a summary table.

Measures of treatment effect

For dichotomous data (adverse effects, treatment failure, recurrence and adherence), we will calculate a pooled estimate of the treatment effects for each outcome across trials using risk ratio (RR) and 95% confidence intervals (CIs) where appropriate.

For continuous data, we plan to record the mean change and standard deviation (SD) from baseline for each group. We intend to calculate a pooled estimate of treatment effect using the mean difference (MD) and 95% CIs. Where trials use different units of measurement or measurement scales for reporting the same outcome (which is likely to be true for QoL and symptom scores) we will use the standardised MD (SMD) to report the results. Where trials only report only a pre‐intervention mean (SD) and post‐intervention mean (SD) then we can calculate the mean change but not the SD of the change. These results will be reported narratively

For time‐to‐event data (time to resolution of DIOS) we will express the intervention effect as a hazard ratio (HR) with 95% CIs using the generic inverse variance method. It may be that time taken to resolution of DIOS is reported as continuous data (rather than time‐to‐event data) in some trials. If this is the case, we will seek advice from the Cochrane Review Group, but plan to analyse the results according to how the majority of included trials present the data, so that we obtain an accurate estimate of treatment effect.

Where end‐points are semantically different but report to similar outcomes then we will group outcomes. Thus, synonymous terms will be considered jointly. We will consider:

• abdominal distension to be synonymous with bloating, swelling, gaseous distension;

• pain to be synonymous with discomfort or ache;

• vomiting to be synonymous with emesis; and

• constipation to be synonymous with straining at stool or dyschezia.

Unit of analysis issues

We will assess any trials using a cross‐over design to establish how much data we can include in the analysis. We will be able to include the trial if the authors have taken account of the cross‐over design in the analysis, any carry‐over effect (i.e. included a washout period for the intervention) and within‐person differences. Where the original authors have not analysed the data appropriately, we may be able to include data from the first phase of the cross‐over trial as if it were a parallel design; although the advantage of the cross‐over design (using participants as their own controls) would be lost (Elbourne 2002).

If we find trials which are multi‐arm they will possibly fall into more than one comparison. In such cases, where the two active treatment arms are different types of laxative regimen, e.g. macrogol 3350 versus lactulose and senna versus placebo, each treatment arm will be analysed separately against placebo and where appropriate included in a meta‐analysis. If the two active treatment arms are of the same type of laxative (e.g. softening agents), but employ a different laxative or dose, we will combine them against the placebo arm to look at the effect of the type of laxative rather than an individual drug. If there is heterogeneity between trials looking at different types of laxative regimen, we will carry out a subgroup analysis to look at the effect of individual drugs (see Subgroup analysis and investigation of heterogeneity).

Dealing with missing data

We will attempt to request additional data from the trial author(s) if there are insufficient data in the published paper or uncertainty about data we are able to extract from the included trials. We will undertake an intention‐to‐treat (ITT) analyses wherever possible throughout the review.

We will also assess the extent to which trial authors have employed an ITT analysis and we will report the numbers of participants who dropped out of each arm of the trial, where possible.

Where data are incomplete but partially available, we will use the last available measurement.

Assessment of heterogeneity

Where there are trials reporting the same outcomes which we are able to include in a meta‐analysis, we will assess the level of heterogeneity using the I² statistic. We will look at the overlap of the CIs on the forest plots to gauge the significance of the I² value.

We will base our definitions of different levels of heterogeneity on the levels described in the Cochrane Handbook for Systematic Reviews of Interventions:

• low (might not be important) = 0% to 40%;

• moderate = 30% to 60%;

• substantial = 50% to 90%; and

• considerable = 75% to 100%.

The Cochrane Handbook for Systematic Reviews of Interventions states that this is a rough guide because the importance of inconsistency depends on several factors (Deeks 2011).

Assessment of reporting biases

Where we are able to include at least 10 trials, we will generate a funnel plot to attempt to identify any publication bias in the included trials (Sterne 2011). We will also attempt to identify any selective reporting in the included publications, by comparing the trial protocols with the final papers and by careful examination of the trial publications and consideration of reporting of both positive and negative effects of the intervention. Where trial protocols are not available, we will compare the outcomes reported in the results section against the methods section of the paper. We will extract information on the sponsors, sources of funding and competing interests of the authors to determine the role of external bias being introduced. To minimise publication bias, we will search trial registries and contact pharmaceutical companies for unpublished data.

Data synthesis

Where we are able to combine trials in a meta‐analysis, we will use the data from the selected trials to generate forest plots using the Review Manager software (RevMan 2014). We will carry out separate meta‐analyses for different groups of laxative agents (e.g. osmotic laxatives, stimulant laxatives and mucolytics and those with a combined mechanism of action) versus placebo, usual treatment or each other. We will examine the level of heterogeneity to determine which type of analysis model to use. If there is low heterogeneity (less than 40%) then we will use a fixed‐effect model and if the I² statistic is greater than 40% then we will use a random‐effects model to summarize the data. However, it is important to note that as the random‐effects model allows for heterogeneity, the CI for the pooled estimate will be wider and therefore, less precise. If heterogeneity is considerable (I² over 75%), we plan to report results narratively as it would not be appropriate in these cases to combine results in a meta‐analysis.

Subgroup analysis and investigation of heterogeneity

If there is greater than 40% heterogeneity in the included trials, we plan to undertake the following subgroup analyses:

• comparison of individual treatment agents or combinations or agents;

• children (under 18 years of age) versus adults;

• route of administration (e.g. oral, via nasogastric tube, via gastrostomy or rectally).

Sensitivity analysis

Where we have performed a meta‐analysis, we will carry out sensitivity analyses to look at the effect of the risk of bias findings. We will look at the effect of adding in and taking out trials where there is high risk of bias. We will also attempt to examine the effect of cross‐over trials on the results by carrying out a sensitivity analysis to include and exclude them.