Using clinical trial data to tailor adjuvant treatments for individual patients

The 2005 St. Gallen Consensus Panel provided recommendations for the treatment of early breast cancer which rely on target identification first. The foremost advance since 2005—demonstration of trastuzumab efficacy for patients with HER2-positive disease—was realized because an effective treatment was being evaluated and because the trial patients had the targeted disease as determined by quality-controlled assessment prior to study entry. The BIG 1-98 trial provides a striking reminder of patients’ benefit from reliable pathological tumor assessment so that targeted therapies are effectively utilized. Several statistical methods facilitate use of clinical trial data for individualizing treatment. Subgroup analyses summarized using forest plots are essential for better understanding the disease and its treatment. The HERA trial illustrates the interpretation of relative and absolute treatment effects and estimating hazard rates over time as means to distinguish relevant differences across subgroups. Overview analyses, joint analyses, the STEPP (subpopulation treatment effect pattern plot) method and recursive partitioning are valuable tools.