A change-point regression approach for estimating no observed adverse effect level from systematic review

Area of Science:

• Pharmacology
• Toxicology
• Biostatistics

Background:

• Systematic reviews are crucial for evaluating drug and food ingredient efficacy and safety.
• Estimating the no observed adverse effect level (NOAEL) is a key aspect of safety assessment.
• Current methodologies lack a statistical approach for NOAEL estimation from systematic review data.

Purpose of the Study:

• To develop and validate a statistical methodology for estimating the NOAEL from systematic review findings.
• To explore dose-response thresholds for adverse events in systematic reviews.
• To apply the developed model to omega-3 fatty acid safety data.

Main Methods:

• Utilized a weighted change-point regression model incorporating study weights from systematic reviews.
• Applied the model to analyze safety data from a systematic review on omega-3 intake.
• Investigated dose-response relationships to identify adverse event thresholds.

Main Results:

• The developed model successfully estimated the NOAEL for omega-3 intake.
• A statistically significant threshold was identified in the dose-response relationship for adverse events.
• The weighted change-point regression model proved applicable to systematic review safety data.

Conclusions:

• A novel statistical method using weighted change-point regression enables NOAEL estimation from systematic reviews.
• This approach can identify dose-response thresholds for adverse events.
• The method offers a valuable tool for robust drug and food safety assessments.