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Table 9 Framework for reviewing factors influencing heterogeneity across included studies

From: An approach to addressing subpopulation considerations in systematic reviews: the experience of reviewers supporting the U.S. Preventive Services Task Force

1. Population 2. Intervention 3. Comparator 4. Outcomes 5. Timing and tools 6. Study design and conduct
Heterogeneity factors for each major domain driving heterogeneity
- Baseline risk for primary outcome (without intervention) as well as for intervention-related harms
- Other main population differences hypothesized to drive differences in intervention effects
- Differences in the approach, intensity, modalities, or components of interventions that could drive differences in intervention effects - Components of comparison condition that might influence the size/direction of intervention effects - Comparability of inpatient outcomes across studies that might influence intervention effects - Appropriateness and comparability of outcome assessment timing considering hypothesized intervention effects and natural history - Variability in design and conduct of studies within a body of evidence
Potential categories of variable approaches by individual studies
- Risk based (low, average, high, unclear, mixed)
- Other selected (age, race/ethnicity, sex, education, socioeconomic status)
- Approach (generic, targeted, tailored)
- Intensity/dose (hours, duration, staff)
- Modalities (simple, multiple)
- Components (single, co-interventions)
- Placebo
- Usual care
- Active/alternative treatment
- Incremental effect (intervention and comparator only, vary by one or minimal components)
- Type of outcome (primary, secondary, incidental)
- Number and type of beneficial outcomes (one main, multiple, composite)
- Number and type of harmful outcomes (one main, multiple, composite)
- Validity of outcome measurement
- Appropriateness (measured or timed after intervention ended, delayed measurement at meaningful timeframes
- Comparability (consistent timeframe between studies, variable timeframe for study)
- Quality rating (good, fair, poor)
- Risk of bias (lack of allocation concealment, lack of blinded outcome assessment, inappropriate randomization)