For complex interventions that combine different components, it may not always be so clear which of the components truly have an effect or if the components may have different effects that trend in different directions. Ironically, the interventions in precision medicine are complicated in exactly this way. Precision medicines combine a particular therapy with diagnostic procedures designed to select only those patients that are likely to benefit from the therapy. The graphs below show three different ways of mapping out the same set of studies that were all testing the utility of a precision medicine strategy in lung cancer.

What does this show?

The progression of graphs from one tab to the next shows how there are different ways to carve up this data, and each picture reveals something different about the total body of evidence. The “Assay” tab reflects how many of the researchers in the field interpreted this data, focusing on the contrast between two assay modalities (IHC vs. PCR), and puzzling about which of these was the better method to use, given that both had seen inconsistent results. The “Therapy” tab shows how the story is more complicated, since studies using the same assay were not always comparing the same platinum-based treatment, and therefore their results were not necessarily comparable. Then the “Ensemble Space” tab takes this a step further and maps therapy vs. assay (and brings in the tissue specimen as an additional variable) to capture even more of the complexity in this field—and reveal that one column (PCR testing peripheral blood specimens) actually looks pretty promising!