If you want the strongest evidence to guide a new protocol, which type should you rely on?

If you want the strongest evidence to guide a new protocol, which type should you rely on?

• A. A single descriptive study
• B. A summary that combines results from multiple high-quality studies
• C. Expert opinions from a panel
• D. A well-designed study comparing two groups without randomization

Answer: (B)

When guiding a new protocol, the strongest evidence comes from summaries that combine results from multiple high-quality studies. These systematic reviews or meta-analyses pool data across settings and populations, increasing the precision of the effect estimate and helping to determine whether findings are consistent or vary by context. They also assess the quality of the included studies and potential biases, giving a more reliable overall conclusion than any single study. A single descriptive study provides limited evidence and can be biased by the specific sample or methods. Expert opinions rely on experience rather than empirical data. A well-designed nonrandomized comparison reduces some bias but remains vulnerable to confounding and selection bias, making causal conclusions less robust than a well-conducted synthesis of multiple high-quality studies.

When guiding a new protocol, the strongest evidence comes from summaries that combine results from multiple high-quality studies. These systematic reviews or meta-analyses pool data across settings and populations, increasing the precision of the effect estimate and helping to determine whether findings are consistent or vary by context. They also assess the quality of the included studies and potential biases, giving a more reliable overall conclusion than any single study.

A single descriptive study provides limited evidence and can be biased by the specific sample or methods. Expert opinions rely on experience rather than empirical data. A well-designed nonrandomized comparison reduces some bias but remains vulnerable to confounding and selection bias, making causal conclusions less robust than a well-conducted synthesis of multiple high-quality studies.