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Creating historical controls using data from a previous line of treatment - Two non-standard approaches
Anthony J Hatswell1,2, William G Sullivan3,4
1BresMed Health Solutions, Steel City House, West Street, Sheffield, UK.
Statistical Methods in Medical Research
|January 31, 2019
Summary
Estimating treatment benefits with uncontrolled studies is challenging. This research presents two methods using historical controls to assess incremental benefits for new medical interventions, aiding health technology decisions.
Area of Science:
- Clinical Trials
- Health Economics
- Oncology
Background:
- Medical interventions are often licensed using uncontrolled study data, such as single-arm trials.
- Estimating the incremental benefit of these interventions requires comparison to a suitable control group.
Purpose of the Study:
- To present and illustrate two methods for creating historical controls.
- To quantify the clinical benefit of treatments based on limited, uncontrolled trial data.
- To inform health technology adoption decisions.
Main Methods:
- Utilizing routinely collected clinical trial data on patients' time to disease progression on previous treatments.
- Extrapolating published clinical outcomes from prior treatment lines to estimate outcomes for subsequent lines.
- Applying methods to pharmaceuticals licensed via uncontrolled studies, including idelalisib and ofatumumab.
Main Results:
- Demonstrated two viable methods for constructing historical controls from existing data.
- Showcased the application of these methods using real-world pharmaceutical examples.
- Highlighted the potential utility of these methods for benefit estimation.
Conclusions:
- The presented methods offer a way to estimate incremental benefits when using uncontrolled study data.
- These approaches can be valuable for informing health technology adoption, despite inherent limitations.
- Case-by-case consideration of limitations is crucial for accurate interpretation.
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