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Table 1 Summary of TOMAS-R steps

From: TOMAS-R: A template to identify and plan analysis for clinically important variation and multiplicity in diagnostic test accuracy systematic reviews

Step 1 Summary of review objectives and proposed eligibility criteria
Set out key review objectives with broad definition of study participants, target condition and reference standard, index test(s) and study design
Step 2 Scoping potential complexities resulting from clinically important variation and multiplicity.
Identify and record potential complexities that could ultimately affect how data are extracted, presented and combined. Examples of variation could include differences in participants, index tests and their methods, target conditions and reference standards used to define them, study design and methodological quality.
Step 3 Simplify the review whilst maintaining clinical relevance
For each potential source of variation (complexity) consider whether differences in test accuracy might be observed. Consider whether separate analysis or heterogeneity investigation is appropriate
Step 4 Planning data extraction
Develop and pilot a standardised data extraction sheet. Define any data or categories of data to be preferentially extracted, e.g. by participant group, by definition of target condition, by index test method or threshold
Step 5 Planning presentation and analysis of data
Record plan for meta-analysis. Record how data complexity will be presented using graphs, tables, and additional analyses such as investigation of heterogeneity or sensitivity analysis where appropriate and feasible with available data. Recommended graphical presentation includes summary ROC (SROC) plots with individual study data and summary estimates of sensitivity and specificity (summary point) with 95% confidence and prediction regions.