Cochrane Metabolic and Endocrine Disorders Group
Department of General Medicine
University Hospital Duesseldorf

Guidelines for writing a Cochrane protocol/review 

These guidelines are thought to help you to produce a high quality Cochrane systematic review. Please do not hesitate to contact the Editorial Base for further questions.

Please note, paragraphs in black refer mainly to the writing of protocols, paragraphs written in blue reflect advice on review production!

Plain language summary (formerly called the 'synopsis')

The plain language summary aims to summarise the review in an easily understood style which would be understandable by consumers of healthcare. Plain language summaries are made freely accessible on the internet, so will often be read as stand-alone documents. 

Plain language summaries have two parts. The first part is a restatement of the review's title using plain language terms. This does not need to be declarative but does need to include participants, intervention and outcome when included in the title of the review. 
The heading should be no more than 256 characters in length, should be written in sentence case (that is with a capital at the beginning of the title and for names, but the remainder in lower case), but should not end with a full stop. 

The second part or body of the summary should be no more than 400 words in length and should include:
•	A statement about why the review is important
•	The main findings of the review (including number of participants randomized to the intervention, number of trials, duration of trials)
•	A brief comment on any limitations of the review (for example trials in very specific populations or poor methods of included trials)
•	Information about all-cause mortality, morbidity/complications, (health related) quality of life, adverse events, costs and primary outcomes (even if there were none!)

Results in the plain language summary should not be presented any differently from the findings in the review (that is no new results should appear in the summary). 
As with other components of a Cochrane review, plain language summaries should follow the format of the Cochrane Style Guide.

Abstract

 Maximum of 400 words.

Background
One or two sentences which should explain the context or elaborate on the purpose and rationale of the review.

Objectives
The style should be of the form "To assess the effects of  (intervention or comparison) for (health problem) in (types of people, disease or problem and setting if specified)". Aim for one sentence. Standardise on the word 'effects' rather than effectiveness, efficacy, benefits and harms, etc.

Search strategy
List the sources of data in the form: "Studies were obtained from computerised searches of MEDLINE, EMBASE, The Cochrane Library and reference lists of relevant articles."
"We contacted (whoever was contacted; for example pharmaceutical companies, investigators) ONLY if you have done this to locate studies], and we handsearched (journals) ONLY if journals were specifically handsearched for this review". 

Selection criteria
Express as "(type of study) of (or comparing) (type of intervention or comparisons) in (disease, problem or type of people)". 

Data collection & analysis
Restrict to how data were extracted and assessed, not what kind of data were extracted. This would cover such things as independent extraction by two or more authors and the quality assessment of trials. 
"Two authors independently extracted data and assessed trial (or study) quality." If the authors contacted investigators to obtain missing information, this should be noted here.

Main results
Should be restricted to the main qualitative and quantitative results and should address the primary objective.
This section should include:
•	Number of trials, duration of trials and number of participants randomized to the intervention; 
•	Brief details pertinent to the interpretation of the results, such as quality of the trials overall and a comment whether the trials were comparable.
•	Information about all-cause mortality, morbidity/complications, (health related) quality of life, adverse events, costs and primary outcomes (even if there were none!)
   
The results should correspond to the stated objectives. Secondary outcome measures should only be included if they are likely to help someone make a decision about whether or not to use a particular intervention. 

If possible, the baseline rates of events (percentage) or average (for continuous data) should be reported for the groups that are compared.

Express the results narratively as well, if the quantitative results are not clear or intuitive.

Use the summary statistic that you specify under 'Methods of the review' or elsewhere in the text. Check the results reported in the abstract against what is reported in the graphs and tables. Summary measures should be presented in a standard way - for example odds ratio 2.31 (95% confidence interval 1.13 to 3.45). Important methodological issues such as excessive heterogeneity and sensitivity analyses indicating non-robust results should be mentioned here.

If a summary statistic was not calculated, use your qualitative assessment (provided this is clearly linked to the data that are reported in the tables or text of the review) or describe the range and pattern of the results. Avoid reporting just numbers of studies showing positive outcomes and numbers of studies showing negative outcomes ('vote counts').

Reviewers' conclusions
These should only be drawn directly from the findings and should directly and transparently reflect the main results. Do not confuse 'no evidence of effect' with 'evidence of no effect'. Do not make assumptions about practice circumstances, values, preferences, tradeoffs. Giving advice or recommendations should generally be avoided. Any important limitations of data and analyses should be noted. Aim to be succinct. Only important conclusions about implications for research that are not obvious should be included.

Background

General comments
•	Please refer to the Cochrane Style Guide (http://www.cochrane.org/style/home.htm) for general issues on style.
•	Please separate paragraphs by an empty line.
•	References should be cited in alphabetical, then chronological order, separated by a semicolon: 
(Alva 1990; Fritz 1987; Smith 1989; Smith 1990). 

(1) For diabetes reviews
We have developed a standard introduction on the subject of diabetes mellitus. You therefore only need to explain the specific question you are reviewing, and not any details about diabetes mellitus. This introduction looks as follows:

"Diabetes mellitus is a metabolic disorder resulting from a defect in insulin secretion, insulin action, or both. A consequence of this is chronic hyperglycaemia (that is elevated levels of plasma glucose) with disturbances of carbohydrate, fat and protein metabolism. Long-term complications of diabetes mellitus include retinopathy, nephropathy and neuropathy. The risk of cardiovascular disease is increased. For a detailed overview of diabetes mellitus, please see under 'Additional information' in the information on the Metabolic and Endocrine Disorders Group in The Cochrane Library (see 'About', 'Cochrane Review Groups (CRGs)'). For an explanation of methodological terms, see the main Glossary in The Cochrane Library."

•	Then introduce your own subject, using suggested subheading(s), which you find in your protocol template.

(2) Reviews about subjects other than diabetes mellitus and related disorders
•	Start with a short introduction to the subject, that is basically a definition of your title. Then use the subheadings already supplied in your protocol template.

Description of the condition
•	Include information on for example symptoms, natural course of the disorder, prevalence, aetiology and costs (please express all costs in Euros, followed in brackets by the value in U.S. Dollars). You may want to use subheadings.
•	Make sure you maintain an international perspective

Diagnosis
•	What are acceptable / validated diagnostic criteria for the disorder?

Description of the intervention
•	What are the different options for dealing with the problem?

How the intervention might work 
•	How is the intervention supposed to work?

Adverse effects of the intervention

Why it is important to do this review 
•	Why is your review important? How important is it? Is there any uncertainty?
•	What is known about the subject (systematic reviews, big studies...)? What were the shortcomings of these studies/systematic reviews (if any)? What do you yourself want to achieve in contrast? If you did not find a systematic review on the subject you should state so.

Objectives

"To assess the effects of... on..."

Criteria for considering studies for this review

•	Taken together, 'types of studies', 'types of studies, 'types of participants', 'types of interventions' and 'types of outcome measures' describe your in- and exclusion criteria. 
•	Specific exlusion criteria should be named using the heading "Exclusion criteria" in the appropriate section (for example, cross-over studies under types of studies)

Types of studies

Usually, randomised controlled and controlled clinical trials.

Types of participants

•	Give desired participant characteristics such as age, sex etc.
•	Do not call people 'subjects' or 'diabetics', etc. Alternatives include 'people with...', 'participants', 'patients' (but note that a dynamic otherwise healthy obese person may not see herself as a patient!).
•	For people with a particular disorder, you will need to define diagnostic criteria. Only use validated or well established diagnostic criteria. However, make sure that you are not excluding useful studies by being too rigorous. 
•	If your question relates to a complication of a disease, for example diabetic neuropathy, you need to describe diagnostic criteria both for the complication and the underlying disease. 

A non-restrictive description of diagnostic criteria could look like this (example):

"Ideally, the diagnostic criteria for type 2 diabetes mellitus should have been described in the trial. To be consistent with changes in classification and diagnostic criteria of the disease through the years, the diagnosis should have been established using the standard criteria valid at the time of the beginning of the trial (ADA 1997; ADA 1999; NDDG 1979; WHO 1980; WHO 1985; WHO 1999). Also, authors' definition of type 2 diabetes mellitus will be used.
Changes in diagnostic criteria may have produced significant variability in the clinical characteristics of the patients included as well as in the results obtained. These differences will be considered and explored in a sensitivity analysis."
Types of interventions

Use a bullet list, for example: 
•	intervention 1 versus no treatment;
•	intervention 1 versus standard treatment; 
•	intervention 1 versus placebo; 
•	intervention 1 versus intervention 2.

•	Specify the minimum duration of the intervention, distinguish between duration of follow-up and duration of therapy.

Types of outcome measures

Use the following subheadings (see your draft protocol):

Primary outcomes (maximum number of three)

Secondary outcomes

Covariates, confounders and effect modifiers
 If you cannot identify one, say 'none known'.

Timing of outcome assessment

•	Always evaluate: mortality (all-cause and specific), morbidity/development of complications, health-related quality of life/wellbeing/patient satisfaction, adverse effects of the intervention (give examples). You may also like to consider outcome measures such as hospitalisations, emergency room treatments, days off school/work, medication use.
•	You should also consider cost, if studied in a trial. While it is difficult to do a full economic analysis beyond that, you may want to look for economic analyses in your search strategy and then discuss these in the discussion section of the review.
•	If you are using scales, for example for assessment of quality of life or pain, you should use validated scales. If non-validated scales are used, this information may be better than nothing, but the effect of including non-validated scales should lateron be assessed in a sensitivity analysis.
•	Outcomes need to be defined in detail. For example, terms like 'cardiovascular events' are too vague, you need to say what these include. 
•	For each outcome measure, you should think of a preferred way in which the outcome should have been measured. For example: 1. You may be more confidence in the result, if quality of life was measured using a validated rather than an unvalidated instrument, 2. Some biochemical tests for certain substances may be more reliable than others, 3. If one of your outcomes is 'occurrence of a complication', then you need to define acceptable criteria for diagnosis of the complication etc.
•	In reviews dealing with diabetes, you should include a measure of glycaemic control (for example glycosylated haemoglobin) even if this is not your main parameter of interest. 
•	Other than listing primary and secondary outcome measures, it may also be helpful to list co-variates that could influence results. For example, this could be: 1. Compliance (which could also be a measure of adverse effects of an intervention - especially if there is a difference in compliance between intervention and control groups), 2. Glycosylated haemoglobin, for example in interventions aimed at the treatment of a diabetes complication
•	Define clinically meaningful time points for short term, medium term and long term duration of the intervention. This also refers to follow-up. Make sure you don't confuse length of follow-up with treatment duration. Sometimes you need to consider also length of follow-up under randomised conditions or under non-randomised conditions.

Search strategy for identification of studies

Electronic searches (see your draft protocol):
We will use the following sources for the identification of trials: 
•	The Cochrane Library (latest issue);
•	MEDLINE (until recent);
•	EMBASE (until recent);
•	.. (until recent) .

We will also search databases of ongoing trials: ….
The described search strategy (see for a detailed search strategy under 'Additional tables' - Table 01) will be used for MEDLINE. For use with EMBASE and The Cochrane Library this strategy will be slightly adapted.

Ongoing trials
Databases of ongoing trials, for example:
•	Current Controlled Trials (http://www.controlled-trials.com - with links to other databases of ongoing trials)
•	UK National Research Register (http://www.update-software.com/National/)
•	USA - CenterWatch Clinical Trials Listing Service (http://www.CenterWatch.com/)
•	USA - National Institutes of Health (http://clinicalstudies.info.nih.gov/)

Search hints
•	 Keep good note of the exact results of your searches, as you will have to report these later in the review (adapted QUOROM [quality of reporting of meta-analyses] flow-chart).
•	Each search strategy will be checked by our Trials Search Coordinator, Karla Bergerhoff. For further questions, please contact Karla Bergerhoff  (bergerhf@uni-duesseldorf.de).
•	As a minimum, searches should include The Cochrane Library, MEDLINE and EMBASE. But also consider other databases that may be more specific to your question, for example, REACTIONS if you are particularly interested in adverse effects, or PsycINFO when you are interested psychological interventions. Also consider databases of ongoing trials (see below) and of grey literature (for example SIGLE).
•	 Always also search for (systematic) reviews, meta-analyses and health-technology assessment (HTA) reports.
•	Use both Medical Subject Headings (MeSH) and free text.
•	When using Medical Subject Headings (MeSH), include all sub-terms (that is 'explode' the main term') and all subheadings.
•	When identifying a useful record, check its associated Medical Subject Headings (MeSH) or keywords - this may give you ideas about terms you may have forgotten and should be included in a second run of an electronic search. This applies particularly to articles you have identified non-electronically, for example through searching reference lists. If you change the search strategy using this technique, you should explain in the final review what was changed (that is what the original search was and how you altered it).
•	Think of as many alternative terms as possible (use an English Thesaurus).
•	Think of as many alternative spellings as possible.
•	Use truncation symbols if possible (for example, if you use 'diabet*' you will not have to worry about including 'diabetes' and 'diabetic') - but beware of being over-inclusive (for example, 'glyc*' will include 'glycaemia' and 'glycemia', but also 'glycerol', 'glycoprotein' etc.).

Other sources 
•	Specific searches for unpublished information by contacting experts and manufacturers. In the protocol, you should define what you mean by 'expert' (for example every trialist? only trialists of trials of a certain size? people who published a review on the subject? who else?). You should also list the main manufacturers you think will be worth while contacting. 
•	Restricting a search to a certain language is NOT acceptable. An international search is assumed, but for clarity, it should be stated that articles in any language will be included. 

Handsearches
•	With respect to journals, you may wish to handsearch the most recent issues, which will not be indexed in the electronic databases.
•	NOTE: Trials available in abstract form only should be treated with caution

Grey literature
•	Such as abstracts of conference proceedings, theses, information from drug regulatory authorities like the FDA and EMEA.

Reference lists
•	Reference lists of trials or reviews (or other relevant documentation, which must be named).

Correspondence
•	Authors of relevant identified studies, other experts (for example authors of reviews), and manufacturers in order to obtain additional references, unpublished trials, or ongoing trials. 

Methods of the review

Use the following subheadings (see your draft protocol):

Selection of studies
•	This should be done in duplicate by two authors - report interrater agreement using Cohen's kappa (Cohen 1960) and state how you will resolve differences in opinion (the order of describing this should be - 1. measure kappa, then 2. work on consensus). 
•	In case of initial disagreement on potentially relevant studies, mark these studies. If these trials are lateron included they should be eventually subjected to a sensitivity analysis.
•	Blinding of trials for trial selection and quality assessment is not required.

Data extraction and management
•	Data extraction tables (see Tables  'Additional tables' and Tables  'Characterisitics of included studies') are provided in your draft protocol and have to be adapted to your research question.
•	Both data extraction and data entry should be done in duplicate by two authors. Describe how you will resolve differences in data extraction (for example by consensus, referring back to the original paper, or by consulting a third person).
•	Contacting authors about missing information in their trials is a standard requirement. This may include issues such as: methods of randomisation and allocation concealment, separate information for certain patient subgroups, information about complications etc. 

Assessment of methodological quality of included studies 
•	Beware of using scores arising from quality scales. A rough classification into quality A, B and C is okay (Cochrane Handbook for Systematic Reviews of Interventions), but single scores of more complex scales are not reliable. Better look at individual quality criteria specific to your research question.
•	Quality assessment should be done in duplicate by two authors - report interrater agreement using Cohen's kappa on key quality issues (like concealment of allocation) and state how you will resolve 
•	differences in opinion.

Measures of treatment effect
Dichotomous data
•	Are my data dichotomous (binary, that is 'yes' or 'no') or continuous (and if they are continuous, might it make sense to dichotomise them (this may make analysis easier but obviously also means that you lose data)?
•	EXAMPLE: Dichotomous outcomes (for example stroke yes/no) will be expressed as odds ratios (OR) or relative risks (RR) with 95% confidence intervals (CI).

Continuous data
•	EXAMPLE: Continuous outcomes (for example metabolic control as measured by glycosylated haemoglobin A1c (HbA1c)) will be expressed, if possible, as mean differences with 95% CI.

Time-to-event data
•	EXAMPLE: Time-to-event outcomes (for example time until death) will be expressed as hazard ratios (HR) with 95% CI.

Unit of analysis issues
•	EXAMPLE: Different units of analysis (for example OR and RR) will be subjected to a sensitivity analysis.

Alternatively headings specific to the types of studies may be used, such as:
Studies with multiple treatment groups 
Cross-over trials 
Cluster randomised trials 

Dealing with missing data
•	EXAMPLE: Relevant missing data will be obtained from authors, if feasible. Evaluation of important numerical data such as screened, eligible and randomised patients as well as intention-to-treat and per-protocol population will be carefully performed. Attrition rates like drop-outs, misses to follow-up and withdrawn study participants will be investigated. Issues of last-observation-carried-forward (LOCF) will be critically appraised and compared to specification of primary outcome parameters and power calculation.

Dealing with duplicate publications
•	EXAMPLE: In the case of duplicate publications and companion papers of a primary study, we will try to maximise yield of information by simultaneous evaluation of all available data. In cases of doubt, the original publication (usually the oldest version) will obtain priority.

Assessment of heterogeneity
•	Demonstrating no statistically significant heterogeneity does not mean that there is no heterogeneity, so possible heterogeneity should still be explored.
•	The "problem" of heterogeneity is not solved by application of a random effects model once a fixed effect model demonstrated heterogeneity.
•	Causes of heterogeneity might be roughly subdivided into five domains:
(1) the patient (for example rate of drug metabolism, risk factors, co-morbidity, compliance)
(2) the disease (for example stage of development, duration)
(3) the intervention (for example doses, routes, timing, study design factors)
(4) the comparison (for example different control interventions, co-medication)
(5) the outcome (for example timing of measurement, method of measurement)
•	EXAMPLE: In the event of substantial clinical or methodological or statistical heterogeneity, study results will not be combined in a meta-analysis. Heterogeneity will be identified by visual inspection of the forest plots, by using a standard χ2-test and a significance level of α = 0.1, in view of the low power of such tests. Quantification of heterogeneity will also examined with I2, ranging from 0-100% including its 95% confidence interval (Higgins 2002). I2 demonstrates the percentage of total variation across studies due to heterogeneity and will be used to judge the consistency of evidence. I2 values of 50% and more indicate a substantial level of heterogeneity (Higgins 2003). When heterogeneity is found, we will attempt to determine potential reasons for it by examining individual study characteristics and those of subgroups of the main body of evidence.

Assessment of reporting biases
•	RevMan offers a funnel plot method. However, funnel plot asymmetry should be assessed statistically and not just by eye. 
•	Do not place undue emphasis on funnel plots (especially when the number of trials is small, for example less than 10).

Data synthesis (meta-analysis)
•	GOLDEN RULE: Make sure you know what you are doing!
•	Always refer to the newest version of the Cochrane Handbook for Systematic Reviews of Interventions.
•	Remember your audience - this section should be comprehensible for a non-expert and not just for a statistician, so do not forget to explain briefly what you are trying to achieve with particular statistical techniques.
•	The first sentence of this section should read: "Data will be summarised statistically if they are available, sufficiently similar, and of sufficient quality."
•	IMPORTANT! Do not try to do a meta-analysis at all cost - sometimes it is better not to. 

Measures of effect size and methods of meta-analysis
When doing a meta-analysis, you will need to decide on some key questions: 
•	What summary statistic will I use in the meta-analysis?
•	What meta-analytical model will I use?
•	What method of meta-analysis will I use?
•	How will I express the results?

To find an answer to these questions, consider the following:

What summary statistic?
•	Summary statistics to choose from are: Dichotomous data - odds ratio, Peto odds ratio, relative risk (either of benefit or harm), risk difference; continuous data - weighted mean difference, standardised mean difference.
•	PITFALL: Don't confuse the summary statistic you use in the meta-analysis with the way in which you express the data in the end.
•	Whatever you choose - explain why you chose it! 
•	Note that one factor to take into account is the underlying event rate (for example, with an event rate of more than 10% you should better use relative risks).
•	In some cases it may be more appropriate to assess 'time to event' rather than the occurrence of the event, that is to do a survival analysis. Ideally, this requires individual patient data and calculation of hazard ratios, but you could also analyse different follow-up periods by using the different time points as part of the outcome, provided publication provide enough results.
•	For continuous data, the weighted mean difference should generally be used. If outcomes are conceptually the same but measured in different ways (for example different pain scales), the standardised mean difference may be used - but care has to be taken when interpreting these results.

Meta-analytic model - random or fixed effects?
•	PITFALLS: Don't imply a causal relationship between finding heterogeneity and using a random effects model, that is DON'T write: "If significant heterogeneity is found, we will use a random effects model.", BUT you could say: "If significant heterogeneity is found, it is unreasonable to assume that there is one 'true' effect underlying the data, that is constant across different populations, and therefore a random effects model will be used." However, if heterogeneity is substantial, it may be better not to do a meta-analysis at all (because your effect estimate does not reliably reflect the "true" value).

Method of meta-analysis
•	RevMan currently offers: DerSimonian and Laird method (DerSimonian 1986); Peto method; Mantel-Haenzel model (Mantel-Haenzel 1959), Generic Inverse Variance method. 

How to express results
•	Results should be expressed in a way that is easily comprehensible to the reader. Odds ratios are probably not suitable here, and you may even think about expressing your data in more than one way. You may want to contrast absolute and relative measures, talk about underlying event rates, express results as number-needed-to-treat (or harm) (NNT, NNH), etc.
•	NNT, NNH - remember that these depend among other things on follow-up time and baseline risk.

Subgroup analysis and investigation of heterogeneity
•	Subgroup analyses are used to determine whether there are any systematic differences between groups of patients. The generally refer to biological factors and not study design factors.
•	Examples for subgroup analyses are: stratification by age, sex, weight, different doses or routes of application (for example intravenous, oral), different comparison interventions, different stages/durations of a disease, different co-morbidities, smoking status, different times of follow-up... In each case, the groups need to be defined.
•	Subgroup analyses should be kept to a minimum - only use what you think is really important in your particular case.
•	Subgroup analyses should be avoided if there is no statistically significant treatment effect in one of your primary outcomes.

Sensitivity analysis
•	Sensitivity analyses are used to determine how robust the analysis is. They generally do not refer to biological factors but to study design factors (for example study quality criteria, definition of inclusion criteria). The analysis examines if the result is changed when studies are selectively excluded, according to the factors specified.
•	Other examples of sensitivity analyses: excluding studies based on 1. use of non-validated scales, 2. use of certain other methods of outcome assessment felt to be less valid than the standard.

Other statistical methods
•	For example, meta-regression or Baysian meta-analysis - these are not yet available in RevMan, but if you can justify their use, do use them.
•	If you are using statistical methods not available in RevMan, report what software you used. 
•	It may also be helpful to use a l'Abbé plot for inspecting your data.

IMPORTANT!
•	When you are doing the review and discover that you have found no data to enable you to do a meta-analysis, do not delete the section from your protocol outlining any planned analysis but specify that this will be the analysis you will carry out if appropriate studies become available in the future

The following optional headings may be helpful:
Economic issues
Methods for future updates

Description of studies

Hints
•	Don't forget to provide citations for the trials mentioned in brackets whenever this seems to be appropriate. (For example, NOT: "Three trials examined people with type 1 diabetes only.", BUT: "Three trials examined people with type 1 diabetes only (Smith 1960; Johnson 1989; Schiller 1997).")
•	Give detailed numbers of what you identified when carrying out your searches. Explain main reasons for exclusion of studies with reference to the table 'Characteristics of excluded studies'.
•	Provide an overview of duplicate publications and companion papers.
•	The flow of trials through the different stages of the review should be clearly indicated (see our adapted QUOROM flow-chart template):
- How many trials were identified in which database through the initial search?
- How many duplicates were excluded?
- How many titles/abstracts were screened?
- How many titles/abstracts were irrelevant?
- How many references were identified through scanning systematic reviews, HTA reports?
- How many potentially relevant trials had to be retrieved for detailed examination?
- How many were then excluded (give reasons)? 
- How many relevant publications (studies) were detected?
- How many unpublished studies were identified?
- How many studies had to be excluded thereafter (give reasons)?
- How many relevant studies were noted (uniquely identified in which database)?

•	Report your interrater agreement for study inclusion and quality assessment.
•	Report whom you contacted about what kind of missing data and what the response was.
•	Participants: including numbers in the study groups; age, sex and other patient characteristics; co-morbidity, co-medication and information about other potentially relevant variables; any information on how representative the sample was; any information on how similar the comparison groups were at the beginning of the study; diagnostic criteria; any other relevant patient-related information.
•	Interventions: Intervention and comparison intervention(s); route; dose; timing of intervention; duration of treatment; NOTE: use chemical names for drugs, not trade names (although these may be added in brackets if desired).
•	Outcomes: Describe primary and secondary outcome measures assessed and not assessed (with respect to your original list); timing of outcome measurement (incl. length of follow-up). Also comment on the validity of the outcome assessment. Was the description adequate? Were the methods adequate? If scales were used, were they validated (and what aspects were validated)?

 Use the following subheadings:

Studies identified

Assessment of publication bias and interrater agreement

Excluded studies

(Studies awaiting assessment)
(Ongoing studies )
(New studies found at this update)

Characteristics of included studies
Interventions
Comparisons
Number of study centres
Country and location
Setting
Treatment before study

Methods
Duration of intervention
Duration of follow-up
Run-in period
Language of publication

Participants
Who participated
Inclusion criteria
Exclusion criteria
Diagnostic criteria

Outcomes
Primary outcomes
Secondary and additional outcomes 

Methodological quality of included studies

Refer to details on methodological quality of included studies in Table XY under 'Additional tables'.

 Use the following subheadings:

Overview (including interrater agreement for the key quality indicators)

Randomisation and allocation concealment 
Blinding
Definition of primary and secondary endpoints
Power calculation
Intention-to-treat, per-protocol analyses and missing data
Screened and randomised patients 
Discontinuing participation and attrition rates
Compliance measures
Funding
Publication status

Results

Refer to details on baseline characteristics in Table XY under 'Additional tables'.

•	Please put anything related to interpretation of results in the discussion section.
•	Talk about comparisons and outcome measures in the same order as before.
•	Do not confuse 'no evidence of an effect' with 'evidence of no effect'.
•	You may also add additional sub-headings, for example if you have examined more than one previously specified hypothesis.
•	If meta-analyses were performed consider issues of heterogeneity in the appropriate section discussing the specific outcome parameters.

 Use the following subheadings:

Baseline characteristics
Primary outcomes
Secondary outcomes
Heterogeneity
Subgroup analyses
Sensitivity analyses
Publication bias

Discussion

 Use the following subheadings:

Summary of main results (benefits and harms)
Overall completeness and applicability of evidence
Quality of the evidence
Limitations of the review
Agreements and disagreements with other studies or reviews

Issues in this section may include:
•	Interpretation of the results, starting with a short summary of the latter.
•	Distinguish between statistical and clinical significance.
•	Brief comments on any methodological limitations of the included studies and the review itself that are important for decisions about practice or future research.
•	Comments on how the included studies fit into the context of other evidence, stating clearly whether the other evidence was systematically reviewed.  
•	Comments on how the results of the review fit into the context of current clinical practice. Bear in mind that current clinical practice might vary internationally.
•	Comments on how the patient population studied in the trials included compares to the patients one might expect to see in daily clinical practice. 

Reviewers' conclusions

Implications for practice

•	Only present information, do not offer advice. Do not go beyond the evidence that was reviewed. 'No evidence of effect' should not be confused with 'evidence of no effect'. 

Implications for research

•	Avoid just demanding longer and better studies. This should include a mini research proposal, outlining the desirable characteristics of a good study in that area, if you feel one is needed. 
•	Why and how urgently is further research needed?
•	Opinions on how the review might be improved with additional data or resources might also be included here.

Acknowledgements

•	Please say what in particular you acknowledge people for.
•	Please do not forget to acknowledge trialists and companies who provided additional data, as well as anyone who gave helpful advice etc.

Potential conflict of interest 

•	The main thing here is to be as transparent as possible. Conflict of interest does not necessarily mean that you should not be allowed to compose your systematic review. 
•	If none, say: 'None known.'
•	Most important conflicts of interest will obviously be financial, or any association with the pharmaceutical industry. But please also list if you are one of the authors of one of the trials considered for inclusion, or if you are planning a trial.
•	Other examples of conflicts of interest: if you belong to a lobby with particular views on the subject in question, if your religious or cultural background leads you to having particular views on the question, etc. 
•	For further definition, please also see the Cochrane Handbook for Systematic Reviews of Interventions.

Tables

Characteristics of included studies

•	 Please use and adapt the provided template.
•	Use the footnote section to explain all abbreviations.

Characteristics of included studies

•	Provide short but distinct reasons for exclusion.
•	Use the footnote section to explain all abbreviations.

Characteristics of ongoing studies

•	Use the footnote section to explain all abbreviations.

Comparisons and data

•	These data form the base for your meta-analyses.
•	Before keying in data thoroughly think about a clear structure. 

EXAMPLE: Table of comparisons
01 Intervention A versus Intervention B
	01 Death (dichotomous outcome)
		01 You might add sub-categories here
		02 Cardiovascular causes
		03 Suicide
	02 Blood pressure (continuous outcome)
		01 Systolic blood pressure
		02 Diastolic blood pressure
03 'Other data' allows you to add data to a table – usually this will be data that cannot be   
      summarised 

•	Specification of outcome / categories:
(1) "Tab" General: Short description, appropriate group labels (for example insulin glargine, NPH insulin).
(2) "Tab" Statistical: No totals if only one study is added (that means no "pseudo" meta-analysis is performed).
(3) "Tab" Graph: Appropriate group label (for example favours glargine, favours NPH)

Additional tables

•	 Please use and adapt the provided additional tables for your search strategy and data extraction.
•	Use the last row or column to explain all abbreviations.

Additional figures

•	Add additional figures for the adapted QUOROM (quality of reporting of meta-analyses) flow-chart of study selection (use template) and funnel plots, if feasible.

References to studies 

•	You can import references by going to 'file' menu, 'import', 'references'. Ask the Editorial Base for further details. 
•	Authors: Use 'et al' only when there are more than six authors.
•	English title: Provide an English translation for foreign titles.
•	 Journal/book/source: Full journal titles, please (exception BMJ, JAMA). 
•	Pages - page number format: 1234-5; 1234-45; 1234-456 etc.
•	Multiple publications: If you have identified more than one publication referring to the same trial, list them all under the same study ID (mark main publication as primary reference).
•	The date added as part of the study ID should be the date of the first publication. 
•	If an author published several studies in one year use "a", "b" etc., for example Smith 2005a, Smith 2005b, Smith 2005c.