Review criteria

From 3 June 2024, all intervention and flexible (rapid) reviews and protocols of these review types have study-centric data management enabled as a default system setting. See study-centric data management.

Study-centric data management does not prevent you from setting up and editing manual-input analyses in your review. See Set up a manual-input analysis.

Your review will be underpinned by the PICO of your review question: the Populations, Interventions, Comparators and Outcomes that will inform how you select studies for potential inclusion in your review.

With the PICO of your review question in mind, use the Review criteria section in RevMan to plan the syntheses that you will conduct. This is where you set your synthesis criteria.

Click on Review criteria on the left side navigation panel. In this Review criteria section you see six tabs: Interventions, Intervention groupings, Outcomes, Covariates, Characteristics, and Risk of bias.  

Define interventions and intervention groupings

  • In the real-world, healthcare interventions can be defined and discussed at various levels of granularity. 
  • Define your interventions at the most granular level required for your planned analyses.

RevMan enables meta-analyses to be conducted at various levels of intervention granularity, within the same review. For example, you could compare paracetamol at a specific dose to placebo - a narrow synthesis question. To do so, you can simply select the most granular interventions for your comparison when setting up an analysis.

You can also have analyses for broader questions, for example comparing paracetamol of any dose to placebo. To do so, an intervention group for 'Oral paracetamol (any dose)' would need to be defined within an intervention grouping.

  • An intervention grouping consists of two or more intervention groups, which in turn contain interventions. 
  • Intervention groupings can be used for broader analyses, and also for configuring subgroup analyses.

Add intervention groupings

First, ensure you have defined your most granular interventions on the 'Interventions' tab, including any control interventions.

Click on the Intervention groupings tab. Add the intervention groups and assign the relevant interventions to each group. Ensure that you also enter the comparator group as well.

In this example, one intervention grouping is called ‘Any antibiotic vs placebo’ with two intervention groups and the relevant interventions for each group:

  1. Antibiotics: Xibornolics, Aureomycin, Tetracycline, Co-amoxiclav, Co-trimoxazol, Penicillin V
  2. Placebo: Placebo

Another grouping is called ‘Grouping by coverage’ with three intervention groups and the relevant interventions for each group:

  1. Broad-spectrum antibiotics: Tetracycline, Co-amoxiclav, Co-trimoxazol
  2. Narrow-spectrum antibiotics: Penicillin V, Xibornolics, Aureomycin
  3. Placebo: Placebo

These intervention groupings help you address broader synthesis questions.  

Add and describe the outcomes

Click on the Outcomes tab and add your outcomes, a description, whether they are continuous or dichotomous, and if continuous, the unit of measure. In this example we assume you are interested in looking at whether the participants still have a cold after one week. Click the Add Outcome button. Under Name, type 'Persistent symptoms after 7 days'. Under Description add which symptoms you are concerned about. Since the participants are assessed to either have a cold or no cold, choose Dichotomous as the outcome Type.  Later, if you want to analyse other outcomes, you can return here to add them. 

If you have multiple time points for an outcome, these need to be added into RevMan as separate outcomes. 

Add covariates for subgroup and sensitivity analyses

Click on the Covariates tab. This tab is used to define study characteristics and associated categories that you plan to investigate with subgroup analyses (see Subgroup analyses) or filter for sensitivity analyses (see Sensitivity analyses). 

Click the Add Covariate button and type your Covariate name. Type a category and press Enter to start defining the different Categories. 

Note, that in order for content to fit in the forest plot, covariate names can only be 60 characters long.  

Set up your analyses using your review criteria

It is essential that authors set up analyses at protocol stage before entering any study results data. This enables you to check that you have included the Interventions, Intervention groupings, Outcomes and Covariates within the Review criteria correctly. It also means that once you import your results data, your analyses will be automatically populated (a key benefit of using study centric data management). To do this, follow the steps on the Pre-define analyses page.

The Characteristics tab includes high-level criteria for extracting data from your included studies. The Risk of bias for tab includes the domains of the risk of bias tool you plan to use for assessing risk in your included studies. These are already set-up as default, so you do not need to edit them.