Types of studies

We will include parallel‐grouped randomised controlled trials (RCTs) comparing the gonadotropin‐releasing hormone (GnRH) antagonist degarelix to standard androgen suppression therapy in the form of surgical castration of GnRH antagonists for men with advanced prostate cancer. We will include all RCTs irrespective of their publication status or language of publication. We will consider only the first phase of RCTs with cross‐over design (until cross‐over occurs) eligible for inclusion and will exclude cluster‐randomised controlled trials.

Types of participants

Men with advanced stages of prostate cancer who were not previously treated with hormonal therapy. We will not exclude studies based on age or ethnicity of individuals.

Advanced prostate cancer will be defined as any of the following diagnoses.

(a) Men with documented disease spread outside the prostate either to the lymph nodes or other organs (N+/ M0 or M1).

(b) Men with locally advanced disease who have not undergone surgery or radiation with no spread outside the prostate either to the lymph nodes or other organs (T3‐4/ N0 or Nx/M0).

(c) Men who have undergone local treatment with curative intent (such as local radiation therapy, radical surgery or cryotherapy) with biochemical evidence of failure as documented by an elevated or rising PSA in the absence of spread outside the prostate either to the lymph nodes or other organs (T3‐4/ N0 or Nx/M0).

If studies also included men with localized disease (defined as prostate cancer within the prostate gland; T1‐2 N0 M0), we will consider only data of the subgroup of men with advanced stages of prostate cancer. If this is not possible, we will include only data regarding adverse events and quality of life in our meta‐analyses. If more than 80% of participants in these studies had an advanced disease we will report data on other outcomes descriptively and will exclude these results if less than 80% had an advanced disease.

If studies also included men who already received prior androgen suppression therapy, we will include only the subgroup of men who had not received prior androgen suppression therapy. If this is not be possible, we will exclude the study.

Types of interventions

We plan to investigate the following comparisons of experimental intervention versus comparator intervention.

Types of outcome measures

Measurement of outcomes assessed in this review will not be used as an eligibility criterion.

Electronic searches

We will search the following sources from inception of each database.

• Cochrane Library (most recent issue).

  • Cochrane Database of Systematic Reviews (CDSR)

  • Cochrane Central Register of Controlled Trials (CENTRAL)

  • Database of Abstracts of Reviews of Effects (DARE)

  • Health Technology Assessment Database (HTA)

• MEDLINE (via Ovid; 1946 onwards)

• Embase (1947 onwards)

• Web of Science (Thomson Reuters Web of Knowledge; 1970 onwards)

• Scopus (2011 onwards)

• LILACS (as provided by Latin‐American and Caribbean Center on Health Sciences Information)

For details on the search strategy, see Appendix 1.

Additionally, we will also search the following trial registries:

• ClinicalTrials.gov (www.clinicaltrials.gov/).

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

We will use the following keywords for this search: ‘degarelix’, ‘firmagon’, 'FE200486', 'FE 200486'. We will check every included study for a trial registry entry and will present the results in the 'Characteristics of included studies' tables.

If we detect additional relevant keywords during any of the electronic or other searches, we will modify the electronic search strategies to incorporate these terms and document the changes.

We will update our search within three months of anticipated publication of the full review.

Searching other resources

We will try to identify other potentially eligible trials or ancillary publications by searching the reference lists of retrieved included trials, reviews, meta‐analyses and health technology assessment reports. We will also contact study authors of included trials to identify any further studies that we may have missed. We will contact drug/device manufacturers for ongoing or unpublished trials.

We will also search the electronically available abstract books of the following conferences for unpublished studies.

• American Society of Clinical Oncology (ASCO; jco.ascopubs.org; 2004 onwards).

• European Association of Urology (EAU; www.uroweb.org; 2004 onwards).

• American Urological Association (AUA; www.jurology.com/; 2008 onwards).

We will use the following keywords for this search: ‘degarelix’, ‘firmagon’, 'FE200486', 'FE 200486'.

We will also search databases from regulatory agencies (European Medicines Agency (EMA) and US Food and Drug Administration (FDA)) (Hart 2012; Schroll 2015).

Selection of studies

We will use reference management software (EndNote, Covidence (www.covidence.org)) to collate references and remove potential duplicate records. Two review authors (JJJ, FZ) will independently scan the abstracts, titles, or both, of remaining records retrieved, to determine which studies should be assessed further as full texts. Two review authors (JJJ, FZ) will investigate all potentially relevant records as full text, map records to studies, and classify studies as included studies, excluded studies, studies awaiting classification, or ongoing studies in accordance with the criteria for each provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We will resolve any discrepancies through consensus or recourse to a third review author (CS). If resolution of a disagreement is not possible, we will designate the study as 'awaiting classification' and we will contact study authors for clarification. We will document reasons for exclusion of studies in a 'Characteristics of excluded studies' table. We will present a PRISMA flow diagram showing the process of study selection (Liberati 2009).

Data extraction and management

We will use a data abstraction form that was already pilot tested during data assessment of previous evaluations (Kunath 2012).

For studies that fulfil inclusion criteria, two review authors (JJJ, FZ) will independently abstract the following information, which we will provide in the 'Characteristics of included studies' table.

• Study design.

• Study dates.

• Study settings and country.

• Participant inclusion and exclusion criteria.

• Participant details, such as baseline demographics and disease characteristics.

• The number of participants by study and by study arm.

• Details of relevant experimental and comparator interventions such as dose, route, frequency, and duration.

• Definitions of relevant outcomes, method and timing of outcome measurement, as well as any relevant subgroups.

• Study funding sources.

• Declarations of interest by primary investigators.

We will extract outcome data relevant to this review as needed for calculation of summary statistics and measures of variance. For time‐to‐event outcomes, we will attempt to obtain hazard ratios (HRs) with corresponding measures of variance or data necessary to calculate this information. For dichotomous outcomes, we will attempt to obtain numbers of events and totals for population of a 2 × 2 table, as well as summary statistics with corresponding measures of variance. For continuous outcomes, we will attempt to obtain means and standard deviations or data necessary to calculate this information. We will resolve any disagreements by discussion, or, if required, by consultation with a third review author (AB).

We will attempt to contact authors of included studies to obtain key missing data as needed.

We will provide information, including trial identifier, about potentially relevant ongoing studies in the table 'Characteristics of ongoing studies'.

Assessment of risk of bias in included studies

Two review authors (JJJ, FZ) will assess the risk of bias of each included study independently. We will resolve disagreements by consensus, or by consultation with a third review author (SS or CS).

We will assess risk of bias using Cochrane's tool for RCTs (Higgins 2011b). We will assess the following domains.

• Random sequence generation (selection bias).

• Allocation concealment (selection bias).

• Blinding of participants and personnel (performance bias).

• Blinding of outcome assessment (detection bias).

• Incomplete outcome data (attrition bias).

• Selective reporting (reporting bias).

• Other sources of bias.

We will judge risk of bias domains as 'low risk', 'high risk' or 'unclear risk' and will evaluate individual bias items as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). We will present a 'Risk of bias summary' figure to illustrate these findings.

For performance bias (blinding of participants and personnel) and detection bias (blinding of outcome assessment), we will evaluate the risk of bias separately for each outcome, and we will group outcomes according to whether measured subjectively or objectively when reporting our findings in the 'Risk of bias' tables.

We will also assess attrition bias (incomplete outcome data) on an outcome‐specific basis, and will group outcomes with judgements when reporting our findings in the 'Risk of bias' tables.

We will further summarize the risk of bias across domains for each outcome in each included study, as well as across studies and domains for each outcome.

We define the following endpoints as subjective outcomes as determined by their susceptibility to detection bias and the importance of blinding outcome assessors.

• Cancer‐specific survival.

• Serious adverse events.

• Quality of life.

We define the following endpoints as objective outcomes.

• Overall survival.

• Clinical progression.

• Biochemical progression.

Concomitant interventions will have to be the same in the experimental and comparator groups to establish valid comparisons. If not or if not explicitly reported, we will consider this in our risk‐of‐bias analysis and will perform sensitivity analyses (see Sensitivity analysis).

Measures of treatment effect

We will express time‐to‐event data as hazard ratios (HRs) with 95% confidence intervals (CIs). We will express dichotomous data as risk ratios (RRs) with 95% CIs. We will express continuous data as mean differences (MDs) with 95% CIs unless studies use different measures to assess the same outcome, in which case we will express data as standardized mean differences with 95% CIs.

Unit of analysis issues

The unit of analysis will be the individual participant. Should we identify cross‐over trials we will only assess the results of the first phase if data are available. Otherwise we will exclude cross‐over trials. Should we identify trials with more than two intervention groups for inclusion in the review, we will handle these in accordance with guidance provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011c).

Dealing with missing data

We will try to obtain missing data from study authors, if feasible, and will perform intention‐to‐treat (ITT) analyses if data are available; we will otherwise perform available case analyses. We will investigate attrition rates, e.g. drop‐outs, losses to follow‐up and withdrawals, and will critically appraise issues of missing data. We will not impute missing data.

Assessment of heterogeneity

In the event of considerable heterogeneity unexplained by subgroup analyses, we will not report outcome results as the pooled effect estimate in a meta‐analysis but will provide a narrative description of the results of each study.

We will identify heterogeneity (inconsistency) through visual inspection of the forest plots to assess the amount of overlap of CIs, and the I² statistic, which quantifies heterogeneity across studies (Higgins 2002; Higgins 2003). We will interpret I² as follows.

• 0% to 40%: may not be important.

• 30% to 60%: may indicate moderate heterogeneity.

• 50% to 90%: may indicate substantial heterogeneity.

• 75% to 100%: considerable heterogeneity.

When we find heterogeneity, we will attempt to determine possible reasons for it by examining individual study and subgroup characteristics.

Assessment of reporting biases

We will attempt to obtain study protocols to assess for selective outcome reporting.

If we include 10 studies or more investigating a particular outcome, we will use funnel plots to assess small‐study effects. Several explanations can be offered for the asymmetry of a funnel plot, including true heterogeneity or poor methodological design (and hence bias of small trials) and publication bias. We will therefore interpret results carefully.

Data synthesis

We will summarize data using a random‐effects model. We will interpret random‐effects meta‐analyses with consideration of the whole distribution of effects. In addition, we will perform statistical analyses according to the statistical guidelines contained in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). For dichotomous outcomes, we will use the Mantel‐Haenszel method; for continuous outcomes, we will use the inverse variance method; and for time‐to‐event outcomes, we will use the generic inverse variance method. We will use the most up‐to‐date Review Manager software to perform analyses (RevMan).

Subgroup analysis and investigation of heterogeneity

We expect the following characteristics to introduce clinical heterogeneity, and plan to carry out subgroup analyses with investigation of interactions.

• Different doses of degarelix subcutaneous maintenance doses (80 mg versus 160 mg versus other doses).

• Different standard androgen suppression therapies (surgical castration versus medical castration versus antiandrogen monotherapy versus combination of medical castration and antiandrogen therapy).

• Different stages of advanced hormone‐sensitive prostate cancer (non‐metastatic versus metastatic disease).

We will use the test for subgroup differences in Review Manager to compare subgroup analyses if there are sufficient studies (RevMan).

Sensitivity analysis

We plan to perform sensitivity analyses in order to explore the influence of the following factors (when applicable) on effect sizes.

• Restricting the analysis by taking into account risk of bias, by excluding studies at 'high risk' or 'unclear risk' (one of the criteria 'high risk' or two of the criteria 'unclear risk').