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“We have no cure. I don’t want to know.” If astronomers announced that a large asteroid might strike Earth in twenty years, and that we currently had no way to deflect it, nobody would respond by saying, “Come back when you already have the rocket.” We would immediately build better telescopes to track it precisely, refine its trajectory models, and begin developing propulsion systems capable of interception. You do not wait for the cure before improving the measurement. You improve the measurement so that a cure becomes possible, targeted, and effective. Medicine is no different. Refusing to improve early, probabilistic diagnosis because today’s treatments are modest confuses sequence with outcome. Breakthroughs do not emerge from vague labels and mixed populations. They emerge from precise, quantitative stratification that allows real effects to be seen. The danger is not that we measure too early. It is that we continue making irreversible clinical and research decisions using imprecise, binary classifications while biological insight and therapeutic tools are advancing rapidly. Building the probabilistic layer now is not premature. It is how we make future intervention feasible. |
This is absolutely nothing like the asteroid example, where knowing that anybody is going to fall victim to it would itself be news of astronomical proportions. Previously there was a high chance the event wouldn't happen, and now it seems likely it will, so that entirely change the calculus of your priorities.
This just completely destroys the analogy. (There are other reasons it doesn't fit too, but one is enough.)