Oct 26, 2026 · 1 hr 12 min · 10 segments
Your Medical Oncologist can often be the quarterback of your care - guiding and advising through the many steps in your journey to wellness. Listen as Dr. Weichman and Dr. Thanik, along with Ari…
Pedram RazaviGuest
Vishal ThanikHost
Katie WeichmanHost
Ari HaberbergHost
It really just seems like the treatment of breast cancer has changed so much in a really short amount of time because I would say even before, I mean, maybe 2017, like everyone that had breast cancer got systemic chemotherapy, even stage 1A like was getting And so then you had trials that showed that chemotherapy didn't get a benefit in certain patients with certain oncotypes.
Then we even escalate more after we escalated to see if escalating more than that, can you improve the outcome of the patients? Then you get to the ceiling.
And then we understand that, you know, now it's time for us to start thinking about de-escalation and what are the groups of patients that we can safely de-escalate.
And historically, we didn't have a lot of information, you know, so we had to rely on some pathology information, some, you know, tumor size information.
for breast cancer and a breast oncologist because we are getting a lot of options for our patients, very effective treatments.
We're bringing them now into the early stage setting and now multiple treatments approved for early stage breast cancer this year.
But what you brought up is a very, very important topic in my opinion is one fit doesn't, one size doesn't fit all.
And I think we are getting to the point that we have those tools in hand and we have the data, we have the genomic data, we have the, you know, all these tools that, you know, AI, in my opinion, is going to completely transform the way that we do this if we use it right.
Because the type of information that we couldn't put together before and give a, you know, and give a risk, individualized risk to a patient analyzed in a matter of minutes It would have taken months for us to analyze those without GPUs before or whatever.
It really just seems like the treatment of breast cancer has changed so much in a really short amount of time because I would say even before, I mean, maybe 2017, like everyone that had breast cancer got systemic chemotherapy, even stage 1A like was getting And so then you had trials that showed that chemotherapy didn't get a benefit in certain patients with certain oncotypes.
Then we even escalate more after we escalated to see if escalating more than that, can you improve the outcome of the patients? Then you get to the ceiling.
And then we understand that, you know, now it's time for us to start thinking about de-escalation and what are the groups of patients that we can safely de-escalate.
And historically, we didn't have a lot of information, you know, so we had to rely on some pathology information, some, you know, tumor size information.
for breast cancer and a breast oncologist because we are getting a lot of options for our patients, very effective treatments.
We're bringing them now into the early stage setting and now multiple treatments approved for early stage breast cancer this year.
But what you brought up is a very, very important topic in my opinion is one fit doesn't, one size doesn't fit all.
And I think we are getting to the point that we have those tools in hand and we have the data, we have the genomic data, we have the, you know, all these tools that, you know, AI, in my opinion, is going to completely transform the way that we do this if we use it right.
Because the type of information that we couldn't put together before and give a, you know, and give a risk, individualized risk to a patient analyzed in a matter of minutes It would have taken months for us to analyze those without GPUs before or whatever.
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