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I think there is a distinction to be made here in questioning patient outcomes and questioning the relevance of genomic sequencing in treatment decisions.

Don't you think it is fair to say that high throughput data (whole genome sequencing with variant calling) is still in a state of being evaluated to measure its effectiveness in aiding the treatment decision process but that early results seems to lean towards it becoming part of the standard diagnostic approach?

Genomic sequencing and patient outcomes is a thornier question. My non-practitioner take is that it is too early to tell scientifically, but that there will probably be some benefit to early identification of specific cancer types and choosing treatment. But I think many people would have made a similar statement about mammography and early detection, and absolute mortality appears to not be reduced by adding mammography to the diagnostic procedures, right?

The research value of genomic sequencing seems high enough to make it worthwhile. At least, when I sit in on molecular tumor board reviews (the oncologists at a table looking at called variant results for a specific patient), I hear them commenting about possibly new and unknown variants being of research value.

I am really looking forward to your reply - Internet message boards in general have to be almost the worst way to discuss medicine, but having participation from researchers and practioners like you is tremendously illuminating!



I define genomics as the unbiased interrogation of the genome using high throughput technology. Sequencing one mutant locus using Sanger sequencing does not fall under this definition - I don't think IBM's business model is using Watson to interpret that. So when other people point out that HER2 is a useful genomic marker they are missing the point - HER2 can be determined with immunohistochemistry for example which has been around for 50 years.

I'm not sure what your question is... genomics has research value, for sure, it's great. Is it worth trying to incorporate it into routine care? Yes, probably, if you have enough cash. Should a hospital pay for a black box machine learning algorithm to make recommendations from a highly polluted, often erroneous and hugely incomplete literature corpus? The alternative put forward by people actually doing the science is that we should try and develop large open source databases/repositories about the significance of genomic findings, and then collect the data about what happens to the patients.




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