Abstract
There is a somewhat confused belief that a biomarker must show an interaction effect with a treatment before it can be used to determine the need for such a treatment. This is rarely true for well-established clinical markers such as tumor size or regional lymph node involvement. In many cases, this is also not true for biomarkers, especially when considering nontargeted therapies. Here I argue that for nontargeted treatments prognosis is often more important than interaction with treatment, because it is the absolute and not the relative benefit that matters, and when there is no treatment interaction, the same relative benefit translates into a larger absolute benefit for poor prognosis patients.
Highlights
I argue that for nontargeted treatments prognosis is often more important than interaction with treatment, because it is the absolute and not the relative benefit that matters, and when there is no treatment interaction, the same relative benefit translates into a larger absolute benefit for poor prognosis patients
When determining the need for additional treatment, confusion exists between the importance of a marker capable of predicting the likelihood of disease recurrence vs one that predicts an interaction with treatment response
For women age 50 to 69 years, there was a slightly and statistically nonsignificantly larger relative benefit in node-negative women, belying the fact that the absolute benefit was larger in the node-positive women (1.6% vs 0.8% per year, P 1⁄4 1.4Â10-6)
Summary
When determining the need for additional treatment, confusion exists between the importance of a marker capable of predicting the likelihood of disease recurrence (or progression) vs one that predicts an interaction with treatment response. This is largely due to the fact that treatment effects need to be assessed in terms of absolute benefits, but most of the statistical models used are based on relative effect sizes.
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