[Algorithm for Choosing the Study Design in Systematic Reviews]

Area of Science:

• Health Services Research
• Evidence-Based Medicine

Background:

• The Federal Joint Committee (Gemeinsamer Bundesausschuss) assigns the highest evidence level (Ia) to systematic reviews of randomized controlled trials for therapeutic benefit evaluation.
• Contradictory findings in studies may stem from factors beyond study design.
• Systematic reviews are crucial for synthesizing evidence on therapeutic interventions.

Purpose of the Study:

• To identify expert statements on selecting study designs for systematic reviews.
• To develop a practical algorithm for choosing appropriate study designs in systematic reviews.

Main Methods:

• Systematic search and analysis of reviews (systematic and non-systematic) discussing study design selection.
• Development of a decision-making algorithm based on identified criteria.

Main Results:

• 85% of 42 reviewed articles supported including non-randomized alongside randomized study designs.
• A key reason for including diverse designs is evaluating treatment-associated harm.
• The developed algorithm incorporates follow-up length, event frequency, outcomes, and study designs as decision points.

Conclusions:

• Evaluating both benefit and harm of therapeutic interventions often necessitates the inclusion of multiple study designs.
• The proposed algorithm offers guidance for selecting study designs for inclusion in systematic reviews.