A quick note that my latest story for Wired, on the emerging science of early detection of cancer, is now on stands (and online).

The story focuses on the Canary Foundation, a Silicon Valley-based nonprofit that's funding an innovative approach to cancer research: strictly focusing on developing two-step tests that will spot various cancers in their earliest stages, when the odds of successful treatment are highest.

My effort here was to explore how early detection - which sounds obvious on its face; of course we should find cancer early - in practice creates a series of riddles and/or paradoxes. For instance, when you're looking for something floating in the bloodstream (a molecular signal of early cancer), how can you be sure it's present in high enough volumes early enough to be worthwhile as a test? Or: What if a test is great at spotting cancers that, paradoxically, may not actually be lethal, and thus may not merit immediate treatment? What I find admirable about the Canary Foundation approach is that they don't look at finding a protein or a DNA signal as the be-all/end-all of a valid test - it's just the beginning the a statistical parsing that may or may not result in something clinically useful.

If it's not obvious, the connection to the decision tree thesis is this: Finding disease early, when treatment choices are various and have more promise of success, is a far better position to be in than waiting for symptoms and late-stage treatments. My hunch is we're going to be moving towards more and more screening tests for more and more conditions. The challenge will be striking a balance between good tests that and the expense of too much screening and too many false signals.

Oh, and a shout-out to Wired's design department, helmed by Scott Dadich, which always does an ace job turning some rather sober writing on my part into something alluring and cover-worthy.