Criteria for considering studies for this review
Types of studies
Randomised controlled clinical trials.
Types of participants
All patient age groups receiving surgical treatment for Graves' disease.
Our criteria for Graves' disease are clinical examination and suppressed TSH and elevated free T4, free T3, or both. Additional diagnostic tests such as radionuclide uptake and TRAb (TSH receptor antibody)/TBII (thyrotropin binding inhibiting immunoglobulins) are noted where performed, but not considered essential for study inclusion.
Types of interventions
We will consider studies for inclusion where the surgical interventions listed below are compared. We will exclude studies where only one trial arm contains a surgical intervention, or where surgical interventions are compared to medical interventions.
We plan to investigate the following comparisons of intervention versus control/comparator where the same letters indicate direct comparisons.
a) Bilateral subtotal thyroidectomy
b) Unilateral total and contralateral subtotal thyroidectomy
a1) Unilateral total and contralateral subtotal thyroidectomy
a2) Total thyroidectomy
b1) Total thyroidectomy
Types of outcome measures
Rate of recurrent hyperthyroidism
Adverse effects (e.g. permanent recurrent laryngeal nerve palsy, permanent hypocalcaemia)
Timing of outcome measurement
All outcomes must have reported measurements at a minimum of three months follow-up.
Definition of outcome measurement
Rate of recurrent hyperthyroidism: bio-chemically confirmed elevation of T3/T4 with postoperatively suppressed TSH.
Regression of Graves' opthalmopathy: a clinically-significant improvement in Graves' ophthalmopathy using a validated scoring system as reported by the authors of the study.
Health-related quality of life: measured by a validated instrument.
'Summary of findings' table
We will present a 'Summary of findings' table using the following outcomes listed according to priority:
Rate of recurrent hyperthyroidism
Permanent recurrent laryngeal nerve palsy
Regression of Graves' ophthalmopathy
Health-related quality of life
Health economic outcomes
Search methods for identification of studies
We will search the following sources from inception to the present:
The Cochrane Library.
We will also search databases of ongoing trials (ClinicalTrials.gov (www.clinicaltrials.gov/), Current Controlled Trials metaRegister (www.controlled-trials.com/), the EU Clinical Trials register (www.clinicaltrialsregister.eu/) and the WHO International Clinical Trials Registry Platform (http://apps.who.int/trialsearch/)).
For detailed search strategies see Appendix 1. We will continuously apply PubMed's 'My NCBI' (National Center for Biotechnology Information) email alert service to identify newly published studies using a basic search strategy (see Appendix 1). Four weeks before we submit the final review draft to the Cochrane Metabolic and Endocrine Disorders Group (CMED) for editorial approval, we will perform an updated search on all specified databases. If we identify new studies for inclusion we will evaluate these and incorporate findings in our review before submission of the final review draft.
If we detect additional relevant key words 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 place no restrictions on the language of publication when searching the electronic databases or reviewing reference lists in identified studies.
We will send results of electronic searches to the Cochrane Metabolic and Endocrine Disorders Group for databases which are not available at the editorial office.
Searching other resources
We will try to identify other potentially eligible trials or ancillary publications by searching the reference lists of retrieved included trials, (systematic) reviews, meta-analyses and health-technology assessment reports.
Data collection and analysis
Selection of studies
Two review authors (ZWL, LM) will independently scan the abstract, title, or both sections of every record retrieved, to determine the studies to be assessed further. We will investigate all potentially-relevant articles as full text. Where differences in opinion exist, they will be resolved by a third party. If resolving disagreement is not possible, the article will be added to those 'awaiting assessment' and we will contact study authors for clarification. We will present an adapted PRISMA (preferred reporting items for systematic reviews and meta-analyses) flow-chart of study selection (Figure 1) (Liberati 2009).
Data extraction and management
For studies that fulfil inclusion criteria, two review authors (ZWL, LM) will independently abstract relevant population and intervention characteristics using standard data extraction templates (for details see Table 1; Appendix 2; Appendix 3; Appendix 4; Appendix 5; Appendix 6; Appendix 7; Appendix 8; Appendix 9; Appendix 10; Appendix 11; Appendix 12) with any disagreements to be resolved by discussion, or if required by a third party.
Table 1. Overview of study populations
|Characteristic||Intervention(s) and comparator(s)||Sample sizea||[N] Screened/eligible||[N] Randomised||[N] Safety||[N] ITT||[N] Finishing study||[%] Randomised finishing study||Follow-upb|
|(1) Study ID||Intervention 1|| || || || || || || || |
| ||Intervention 2|| || || || || || || || |
| ||Comparator 1|| || || || || || || || |
| ||Comparator 2|| || || || || || || || |
| || || ||total:|| || || || || || |
| Grand total || All interventions || || || ... || || || ... || || |
| || All c omparators || || || ... || || || ... || || |
| || All interventions and c omparators || || || ... || || || ... || || |
We will provide information including trial identifier about potentially-relevant ongoing studies in the table 'Characteristics of ongoing studies' and in the appendix 'Matrix of study endpoints (protocol/trial documents)'. We will try to find the protocol of each included study, either in databases of ongoing trials, in publications of study designs, or both, and specify data in the appendix 'Matrix of study endpoints (protocol/trial documents)'.
We will send an email to all study authors of included studies to ask whether they are willing to answer questions regarding their trials. We will publish the results of this survey in Appendix 13. Thereafter, we will seek relevant missing information on the trial from the primary author(s) of the article, if required.
Dealing with duplicate publications and companion papers
In the event of duplicate publications, companion papers or multiple reports of a primary study, we will maximise yield of information by collating all available data. In case of doubt the publication reporting the longest follow-up associated with our primary or secondary outcomes will be given priority.
Assessment of risk of bias in included studies
Two review authors (ZWL, LM) will assess the risk of bias of each trial independently. We will resolve possible disagreements by consensus, or with consultation of a third party. In cases of disagreement, the rest of the group will be consulted and a judgement will be made based on consensus.
We will assess risk of bias using The Cochrane Collaboration's tool (Higgins 2011a; Higgins 2011b). We will assess the following criteria:
Random sequence generation (selection bias).
Allocation concealment (selection bias).
Blinding (performance bias and detection bias), separated for blinding of participants and personnel, and blinding of outcome assessment.
Incomplete outcome data (attrition bias).
Selective reporting (reporting bias).
We will assess outcome reporting bias (Kirkham 2010) by integrating the results of 'Examination of outcome reporting bias' (Appendix 8), 'Matrix of study endpoints (protocol/trial documents)' (Appendix 7), and section 'Outcomes (outcomes reported in abstract of publication)' of the 'Characteristics of included studies' table. This analysis will form the basis for the judgement of selective reporting (reporting bias).
We will judge 'Risk of bias' criteria as 'low risk', 'high risk' or 'unclear risk' and evaluate individual bias items as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). We will present a 'Risk of bias' figure and a 'Risk of bias summary' figure.
We will assess the impact of individual bias domains on study results at endpoint and study levels.
For blinding of participants and personnel (performance bias), detection bias (blinding of outcome assessors) and attrition bias (incomplete outcome data) we intend to evaluate risk of bias separately for subjective and objective outcomes (Hróbjartsson 2013). We will consider the implications of missing outcome data from individual participants.
We define the following endpoints as subjective outcomes:
We define the following outcomes as objective outcomes:
Rate of recurrent hyperthyroidism.
Permanent recurrent laryngeal nerve palsy.
Health economic outcomes.
Measures of treatment effect
We will express dichotomous data as odds ratios (OR) or risk ratios (RR) with 95% confidence intervals (CI). We will express continuous data as mean differences (MD) with 95% CI.
Unit of analysis issues
We will take into account the level at which randomisation occurred, such as cluster-randomised trials and multiple observations for the same outcome.
Dealing with missing data
We will obtain relevant missing data from authors, if feasible, and carefully evaluate important numerical data such as screened, randomised patients as well as intention-to-treat (ITT), as-treated and per-protocol (PP) populations. We will investigate attrition rates, for example drop-outs, losses to follow-up and withdrawals, and critically appraise issues of missing data and imputation methods (e.g. last observation carried forward (LOCF)).
Assessment of heterogeneity
In the event of substantial clinical or methodological or statistical heterogeneity, we will not report study results as meta-analytically pooled effect estimates.
We will identify heterogeneity by visual inspection of the forest plots and by using a standard Chi2 test with a significance level of α = 0.1, in view of the low power of this test. We will examine heterogeneity using the I2 statistic, which quantifies inconsistency across studies to assess the impact of heterogeneity on the meta-analysis (Higgins 2002; Higgins 2003), where an I2 statistic of 75% or more indicates a considerable level of inconsistency (Higgins 2011b).
When we find heterogeneity, we will attempt to determine potential reasons for it by examining individual study and subgroup characteristics.
We expect the following characteristics to introduce clinical heterogeneity:
Assessment of reporting biases
If we include 10 studies or more for a given outcome, we will use funnel plots to assess small study effects. Owing to several possible explanations for funnel plot asymmetry, we will interpret results carefully (Sterne 2011).
Unless there is good evidence for homogeneous effects across studies, we will primarily summarise low risk of bias data by means of a random-effects model (Wood 2008). We will interpret random-effects meta-analyses with due consideration of the whole distribution of effects, ideally by presenting a prediction interval (Higgins 2009). A prediction interval specifies a predicted range for the true treatment effect in an individual study (Riley 2011). In addition, we will perform statistical analyses according to the statistical guidelines contained in the latest version of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b).
Subgroup analysis and investigation of heterogeneity
We will carry out the following subgroup analyses and plan to investigate interaction:
We will perform sensitivity analyses in order to explore the influence of the following factors on effect sizes:
Restricting the analysis to published studies.
Restricting the analysis taking into account risk of bias, as specified at Assessment of risk of bias in included studies.
Restricting the analysis to very long or large studies to establish how much they dominate the results.
Restricting the analysis to studies using the following filters: diagnostic criteria, language of publication, source of funding (industry versus other), country.
We will also test the robustness of the results by repeating the analysis using different measures of effect size (RR, OR etc.) and different statistical models (fixed-effect and random-effects models).