Evidence-based medicine and big genomic data

Area of Science:

• Genomic Medicine
• Bioinformatics
• Evidence-Based Practice

Background:

• Big Genomic Data (BGD) is transforming precision medicine.
• The integration of BGD into clinical practice requires careful consideration of evidence-based medicine (EBM) principles.
• Existing frameworks for genomic tests may not fully address the complexities introduced by BGD.

Purpose of the Study:

• To evaluate the applicability of EBM principles to Big Genomic Data.
• To discuss the operationalization of EBM for BGD in the current healthcare landscape.
• To highlight the importance of robust research for the clinical utility of BGD.

Main Methods:

• Review and analysis of EBM principles in the context of BGD.
• Discussion of the systematic identification, validation, and utility assessment of BGD.
• Emphasis on the need for large-scale comparative data alongside personalized N-of-1 trials.

Main Results:

• EBM principles are applicable to BGD, requiring systematic evaluation of validity and utility.
• While BGD enables personalized treatment (N-of-1 trials), population-level data is essential for broad impact.
• Non-evidence-based use of BGD can lead to harm and resource waste.

Conclusions:

• Randomized controlled trials remain the gold standard for determining the clinical utility of genomic technologies, including BGD.
• Future research must prioritize clinical validity, clinical utility (benefit-harm balance), and implementation challenges of BGD.
• Operationalizing EBM for BGD is critical for its effective and safe integration into precision medicine.