In systematic reviews, when heterogeneity is present, what is an appropriate approach?

In systematic reviews, when heterogeneity is present, what is an appropriate approach?

• A. Pool all studies without assessment
• B. Consider study design differences and possibly restrict to higher-level designs
• C. Ignore heterogeneity
• D. Increase the sample size of included studies

Answer: (B)

Heterogeneity in systematic reviews means study results vary beyond what would be expected by chance, often due to differences in design, populations, and methods. Because these differences can bias combined estimates, the right approach is to examine and account for how study designs differ and to pursue more comparable evidence when possible. By considering design differences and potentially restricting the synthesis to higher-level designs (for example, prioritizing randomized controlled trials or other rigorous designs), you improve comparability and reduce bias that can drive heterogeneity, leading to more reliable conclusions. Pooling all studies without assessing heterogeneity can yield misleading results, and ignoring heterogeneity is not appropriate because it can hide important differences in effects. Simply increasing the sample size of included studies won’t fix these fundamental design and bias issues.

Heterogeneity in systematic reviews means study results vary beyond what would be expected by chance, often due to differences in design, populations, and methods. Because these differences can bias combined estimates, the right approach is to examine and account for how study designs differ and to pursue more comparable evidence when possible. By considering design differences and potentially restricting the synthesis to higher-level designs (for example, prioritizing randomized controlled trials or other rigorous designs), you improve comparability and reduce bias that can drive heterogeneity, leading to more reliable conclusions.

Pooling all studies without assessing heterogeneity can yield misleading results, and ignoring heterogeneity is not appropriate because it can hide important differences in effects. Simply increasing the sample size of included studies won’t fix these fundamental design and bias issues.