Benchmark dose modeling for epidemiological dose-response assessment using case-control studies

Area of Science:

• Environmental Toxicology
• Epidemiology
• Risk Assessment

Background:

• Toxicological risk assessment traditionally uses prospective cohort studies.
• This study extends toxicological risk assessment to case-control studies using odds ratios (OR).
• A standardized benchmark dose (BMD) framework exists for toxicological data.

Purpose of the Study:

• To compare two BMD modeling approaches for case-control studies: effective count (Wang algorithm) vs. adjusted OR.
• To develop a generalized BMD modeling framework for published case-control study data.
• To apply and compare methods using data on inorganic arsenic and cancer risk.

Main Methods:

• Utilized odds ratio (OR) as the primary epidemiological measure.
• Applied benchmark dose (BMD) methodology for dose-response modeling.
• Compared "effective count" BMD approach (with Wang algorithm) against adjusted OR-based BMD analysis.
• Utilized a database of bladder and lung cancer associations with inorganic arsenic exposure.

Main Results:

• Both compared BMD methods yielded relatively consistent BMD and BMDL estimates.
• Modeling adjusted ORs as continuous data demonstrated better alignment with established toxicological BMD practices.
• The adjusted OR-based BMD analysis approach proved more generalizable.

Conclusions:

• The adjusted odds ratio-based benchmark dose (BMD) modeling approach is recommended for analyzing case-control studies in toxicological risk assessment.
• This approach offers better generalizability and aligns with existing toxicological data analysis practices.
• The study provides a framework for analyzing published case-control data, enhancing chemical toxicity assessments.