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Top Line: We spend a lot of money on breast cancer trials that are detecting fewer and fewer events.
The Study: If you read the QuadShot enough, you’ll notice pretty quickly that modern oncology trials often have far fewer events (i.e., far better outcomes) than expected. While that’s great for our patients, it makes for pretty lousy trial designs. This article helps explain that. Using patient data from ongoing breast cancer trials, the authors show that traditional T and N eligibility criteria leads to a huge range of individual risk for the outcome of interest (i.e. recurrence). Using freely available multivariable risk models like Adjuvant!, they calculated residual event risks--baseline risk minus estimated benefit of standard of care treatment. What they found is that only about 25% of enrollees were actually at a baseline high residual risk (>20%) of the outcome of interest, a rate far below the perceived 75%. They then found that study power was altered dramatically by the proportion of enrolled patients with high versus low residual event risk.
Bottom Line: Using a minimum residual risk threshold for adjuvant breast cancer trials could drastically improve their power to actually detect improvements in outcomes of interest. After all, if your patient fails to meet that threshold, you should feel pretty good signing them up for the off-trial standard of care.
The Study: If you read the QuadShot enough, you’ll notice pretty quickly that modern oncology trials often have far fewer events (i.e., far better outcomes) than expected. While that’s great for our patients, it makes for pretty lousy trial designs. This article helps explain that. Using patient data from ongoing breast cancer trials, the authors show that traditional T and N eligibility criteria leads to a huge range of individual risk for the outcome of interest (i.e. recurrence). Using freely available multivariable risk models like Adjuvant!, they calculated residual event risks--baseline risk minus estimated benefit of standard of care treatment. What they found is that only about 25% of enrollees were actually at a baseline high residual risk (>20%) of the outcome of interest, a rate far below the perceived 75%. They then found that study power was altered dramatically by the proportion of enrolled patients with high versus low residual event risk.
Bottom Line: Using a minimum residual risk threshold for adjuvant breast cancer trials could drastically improve their power to actually detect improvements in outcomes of interest. After all, if your patient fails to meet that threshold, you should feel pretty good signing them up for the off-trial standard of care.
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