Hacker News new | past | comments | ask | show | jobs | submit login

Isn’t that what “stage” classifications are for? So that you have different starting points for tracking outcomes?



Stage refers to the progression of the tumor (size, spread). Generally Stage IV is bad news - the cancer has spread throughout your body. https://www.cancer.gov/about-cancer/diagnosis-staging/stagin...

It is generally helpful to track statistics by stage, but stage is just one of MANY factors.


Stage is also usually not just about the size. It's about genetics of it. Next stage is 'one particularly bad mutation later'. Basically, different stages of the same kind of cancer are different diseases, not different degrees of the same disease.


The further down the genetics rabbit hole you go, the more you realize how little we know. At the same time, the further down the cancer rabbit hole you go, the more you realize tumor size and tumor relationships to certain anatomic thresholds (vascular invasion, serosal involvement, etc) really, really matter.

For most cancer staging, anatomic thresholds remain the gold standard of staging. For many lymphomas and leukemias, and certain solid tumors, there are some specific genetic tidbits we have been able to tease out.

Sequencing by synthesis, whole slide imaging, mass spec, and just simple inventory control (e.g. barcoding specimens, blocks, and slides) are likely to significantly improve cancer care. Probably the biggest gains will be from barcoding samples. At some point in the distant future we'll have sufficient control of the inventory problem to actually do meaningful epidemiological studies where we can fluidly move through population data, prescribing and procedure data, anatomic data, histologic data, and finally into the molecular realms of mass spec and sequencing. But I think a lot of people think "We can just sequence this tumor and prescribe the appropriate drug." But that totally misses the problem that you run into, where you very quickly end up with a study population of N=1 for a lot of things.

I think a growing number of researchers at the ground level understand this is going to involve many, many classes of very, very large data problems.


Staging is complex and depends on many factors.

But roughly you have pathologic staging (microarchitecture, genetics, etc.) and anatomical/clinical staging (size, laterality, lymph nodes, etc.). Those are distinct.

So what you say is not completely incorrect, but it's not really correct either.


Yes, that’s exactly what they do to correct for the bias.

We can, however, compensate for lead-time bias by tracking survival based upon the stage of the cancer (a measure of how advanced the cancer is)


I think I heard somewhere is that this doesn't fully correct for the bias. Do you know if that is the case?


Of course it doesn't fully correct. A consistent measurement of "how advanced is the disease" is only achievable in a very rough way (by staging).




Join us for AI Startup School this June 16-17 in San Francisco!

Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: