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Statistical Considerations for Planning Clinical Trials with Quantitative Imaging Biomarkers
Nancy A Obuchowski1, P David Mozley2, Dawn Matthews3
1Cleveland Clinic Foundation, Quantitative Health Sciences/JJN3, Cleveland, OH.
Journal of the National Cancer Institute
|January 1, 2019
Summary
Measurement error in quantitative imaging biomarkers (QIBs) can affect clinical trial outcomes. Adjusting for known error rates in QIBs is crucial for accurate drug development and clinical practice decisions.
Area of Science:
- Medical Imaging
- Biomarkers
- Clinical Trials
Background:
- Quantitative imaging biomarkers (QIBs) are increasingly used in drug development and clinical practice.
- QIBs aid in subject selection, response assessment, and safety monitoring.
- Despite advantages, QIBs are subject to measurement error.
Purpose of the Study:
- To examine the impact of measurement error on clinical trial designs using QIBs.
- To test proposed adjustments for measurement error in QIBs.
- To focus on QIBs studied by the Quantitative Imaging Biomarkers Alliance.
Main Methods:
- Monte Carlo simulation was employed to model measurement error.
- The study analyzed various clinical trial designs.
- Proposed error adjustment methods were tested.
Main Results:
- Measurement error attenuates the ability of QIBs to differentiate health states and predict outcomes.
- Known QIB performance characteristics can be used for adjustments.
- Adjustments can inform sample size, control misinterpretation rates, and set decision thresholds.
Conclusions:
- Estimates of QIB precision and bias are vital for robust clinical trial design.
- Understanding and accounting for measurement error is essential for reliable QIB application.
- Establishing imaging standardization levels is critical for valid QIB use.
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