Types of studies

We will include RCTs. We will not include quasi‐RCT or controlled clinical trials.

Types of participants

Women aged 18 years or over with early‐stage cervical cancer who have undergone radical hysterectomy (Piver type II, Piver type III, Querleu‐Morrow class B2 or class C1). If studies include women with other types of gynaecological cancer (i.e. endometrial cancer), we will contact the trial authors to retrieve data related to participants with cervical cancer only. If this is not possible, we will include the study only if at least 80% of participants were diagnosed with cervical cancer.

Types of interventions

We will include any trial that attempted to compare the following.

• A pharmacological agent and placebo or standard care.

• A non‐pharmacological intervention and a standard care. Specific interventions include postoperative suprapubic catheterisation, bladder training and acupuncture.

• A pharmacological agent and a non‐pharmacological intervention.

• A pharmacological agent and another agent.

• A non‐pharmacological intervention and another intervention.

• Combinations of intervention and placebo or standard care.

• Combinations of intervention and single intervention.

• Combinations of intervention and other combinations

Types of outcome measures

Electronic searches

We will search the following electronic databases.

• Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, latest issue).

• MEDLINE (1946 to present date).

• Embase (1980 to present date).

We present the Ovid MEDLINE search strategy in Appendix 5. For databases other than MEDLINE, we will adapt the search strategy accordingly.

Searching other resources

We will search the World Health Organization International Clinical Trials Registry Platform (who.int/ictrp/en/) and ClinicalTrials.gov to identify any ongoing trials. If ongoing trials that have not been published are identified, we will approach the principal investigators and major co‐operative groups active in this area to ask for relevant data. We will search the following databases for grey literature: Open‐Grey (opengrey.eu/) and Index to theses (proquest.com/products‐services/pqdt_uk_ireland.html).

Selection of studies

We will download all titles and abstracts retrieved via electronic search of the Endnote reference management database. After duplicates are removed, we will transfer these data to Covidence (covidence.org). Two review authors (AA and CK) will examine the remaining references independently. We will exclude those studies which clearly do not meet the inclusion criteria, and we will obtain full‐text copies of potentially relevant references. Two review authors (AA and CK) will independently assess the eligibility of the retrieved reports/publications. We will resolve any disagreement through discussion or, if required, we will consult a third review author (KG/PL). We will identify and exclude duplicates and collate multiple reports of the same study so that each study rather than each report is the unit of interest in the review. We will use the details obtained from the selection process in Covidence to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table (Liberati 2009).

Data extraction and management

Two review authors (AA and CK) will independently extract study characteristics and outcome data from included studies using Covidence. We will note in the 'Characteristics of included studies' table if outcome data were not reported in a usable way. We will resolve disagreements by consensus or by involving a third review author (KG/TT). One review author (CK) will check study characteristics for accuracy against the trial report.

For included studies, we will extract the following data.

• Author, year of publication and journal citation (including language).

• Country.

• Setting.

• Inclusion and exclusion criteria.

• Study methodology.

• Study population and disease characteristics:

  • total number enrolled;

  • participant characteristics;

  • age;

  • comorbidities;

  • other baseline characteristics;

  • percentage of participants with non‐cervical cancer (only RCTs involving mixed gynaecologic malignancies);

  • FIGO stage of cervical cancer;

• • histopathological subtype of cervical cancer;

  • tumour size (largest tumour diameter);

• • radicality of surgery (Piver or Querleu‐Morrow).

• Intervention details:

  • schedule of bladder training;

  • suprapubic cystostomy technique;

  • acupuncture;

  • cholinergic agents (dose, duration).

• Comparison:

  • Placebo.

• Risk of bias in study (see below).

• Duration of follow‐up.

• Outcomes: for each outcome, we will extract the outcome definition and unit of measurement (if relevant); for adjusted estimates, we will record variables adjusted for in analyses.

• Results: we will extract the number of participants allocated to each intervention group, the total number analysed for each outcome and the missing participants.

• Notes: funding for trial and notable conflicts of interest of trial authors.

Assessment of risk of bias in included studies

We will assess and report on the methodological quality and risk of bias in included studies in accordance with the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011), which recommends the explicit reporting of the following individual elements for RCTs.

• Selection bias: random sequence generation and allocation concealment.

• Performance bias: blinding of participants and personnel (treatment providers).

• Detection bias: blinding of outcome assessment.

• Attrition bias: incomplete outcome data.

• Reporting bias: selective reporting of outcomes.

• Other possible bias.

We will regard outcome data as complete if at least 80% of participants undergo follow‐ups and are assessed for primary outcomes. Two review authors (AA and CK) will independently apply the 'Risk of bias' tool and differences will be resolved by discussion or by appeal to a third review author (KG/PL). We will judge each item as being at high, low or unclear risk of bias as set out in the criteria displayed in Appendix 6. We will provide a quote from the study report or a statement, or both as justification for our judgement for each item in the 'Risk of bias' table. We will summarise results in both a 'Risk of bias' graph and a 'Risk of bias' summary. When interpreting treatment effects and meta‐analyses, we will take into account the risk of bias in the studies that contribute to that outcome. Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the table.

Measures of treatment effect

We will use the following measures of the effect of treatment.

• For dichotomous outcomes (e.g. rate of spontaneous voiding recovery one week after surgery, rate of urethral catheter removal, rate of urinary tract infections, number of participants with normal detrusor pressure at maximum flow, adverse events, recurrences and death), we will analyse data based on the number of events and the number of people assessed in the intervention and comparison groups. We will use these to calculate the risk ratio and 95% confidence interval.

• For continuous outcomes (e.g. duration of postoperative retained urethral catheterisation, post‐void residual urine volume and QoL measures), we will analyse data based on the means, standard deviations and number of people assessed for both the intervention and comparison groups to calculate the mean difference between treatment arms with a 95% confidence interval. If the mean difference is reported without individual group data, we will use this to report the study results. If more than one study measures the same outcome using different tools, we will calculate the standardised mean difference and 95% confidence interval using the inverse variance method.

• For time‐to‐event data (e.g. time to post‐void residual volume of urine ≤ 50 mL after surgery), we will extract the log of the hazard ratio (log_HR) and its standard error from trial reports. If these have not been reported, we plan to estimate the log_HR and its standard error using the methods of Parmar 1998.

Unit of analysis issues

We will include studies in which individual participants were randomised. In a study with multiple intervention groups, we will combine all relevant experimental intervention groups into a single group to create a single pair‐wise comparison, where possible (Higgins 2011). It is unlikely that cross‐over or cluster‐RCTs could be designed to evaluate the interventions that this review aims to evaluate.

Dealing with missing data

We will contact the original investigators to request missing data. If we cannot contact the investigators or cannot obtain the requested missing data, we will analyse only the available data and will not impute missing outcome data for any of the outcomes.

Assessment of heterogeneity

We will clinically assess heterogeneity by visual inspection of forest plots. We will assess statistical heterogeneity in each meta‐analysis using the I² statistic and Chi² test (Higgins 2003). We will regard heterogeneity as substantial if the I² statistic value is greater than 50% or there is a low P value (< 0.10) in the Chi² test for heterogeneity (Deeks 2001; Higgins 2011). If there is substantial statistical heterogeneity, we will carry out subgroup analyses to assess differences among the included studies. However, if there is both clinical and methodological heterogeneity across included studies, we will not report pooled results from meta‐analysis, but will instead use a narrative approach to data synthesis.

Assessment of reporting biases

We will examine funnel plots corresponding to a meta‐analysis of the primary outcome to assess the potential for small‐study effects such as publication bias if more than 10 studies are identified. We plan to assess funnel plot asymmetry visually, and if asymmetry of funnel plots is identified, we will perform exploratory analyses to investigate it (Sterne 2011).

Data synthesis

We will use the random‐effects model with inverse variance weighting for all meta‐analyses (DeSimonian 1986). We will perform statistical analysis using Review Manager 5.3 (RevMan 2014).

• For time‐to‐event data, we will pool hazard ratios using the generic inverse variance.

• For any dichotomous outcomes, we will calculate the relative risks for each study and then pooled them.

• For continuous outcomes, we will pool the mean differences among the treatment arms, if all trials measure the outcome on the same scale; otherwise we will pool standardised mean differences.

Subgroup analysis and investigation of heterogeneity

We will carry out subgroup analyses in order to assess the effect of the following factors.

• Tumour size (2 cm or less versus more than 2 cm).

• Surgical approach (laparotomy versus minimal invasive surgery).

• Nerve‐sparing approach during radical hysterectomy (yes versus no).

• Radicality of surgery (Piver type II versus Piver type III, or Querleu‐Morrow class B2 versus class C1).

• Extent of pelvic lymph node dissection determined by number of lymph nodes removed.

We will assess subgroup differences using the interaction tests available within RevMan 2014. We will report the results of subgroup analyses by quoting the Chi² statistic and P value, the interaction test and the I² statistic.

Sensitivity analysis

We will perform sensitivity analyses in order to assess the effect of the following factors.

• Repeating the analysis excluding unpublished studies (if any).

• Repeating the analysis excluding studies judged to be at “high” or “unclear” risk of bias for allocation concealment.