 Okay, thank you. Good morning. It's nice to be here. So as stated, I'm going to talk about some observation also some intermittent strategies towards the end I think I think of this sort of maybe building on Danny's talk to say there's a group of patients who have just a favorable biology They have good prognosis and perhaps we can incorporate into our approach to patients taking advantage of that of their good prognosis So again, I'll talk about indolent biology. I'll talk about initial observation and then I guess maybe more broadly taking a break in Systemic treatment both our retrospective and our prospective experience So this is a slide I've showed many times. This was actually I believe a KCA sponsored Analysis and it looked at a very large number of patients That received cytokine therapy So I think we can argue this is probably the natural history of kidney cancer and really what it's meant to show is that What you all know from clinical practice is that kidney cancers extremely biologically diverse I find myself saying that to patients a lot because they'll come in and say Yeah, I read on the internet that kidney cancer slow-growing or I read that it's fast-growing or aggressive or whatever and I say, you know what? It's it's everything right? It's probably the most biologically diverse solid tumor that we see in this graph really shows it where you have Patients on these curves over here who have a median survival measured in about six months Which is as bad as any solid tumor and then patients out here who have a median survival measured in many years Again with probably what we could argue is minimally effective therapy who clearly have a favorable natural history There's some very old data from Tim Oliver now many many years ago that looked at sort of initial basically was Initial versus delayed interferon so fairly small number of patients you see here And the progression rate and really what it's meant to show obviously most patients progress progress fairly quickly So if you take an unselected population the median PFS is about two months Basically when you do the next scan their disease is worse not surprisingly But I would point out that you know there is a subset of patients I would estimate it's about five to ten percent in part I would say that based on these data saying about ten percent of patients didn't progress even after a year So after these patients walked in with metastatic disease and you watched them about one out of ten patients Didn't get significantly worse after twelve months of observation And I think importantly whether you gave in this case interfere on up front or later The response rate was identical So I often tell patients whether you're going to respond to this drug whether it's Sunitinib or Pozapinib or whatever You're gonna respond today just like you're gonna respond in a month just like you're gonna respond in a year I believe that and I think we're starting to collect data in that regard So in whom do we delay? Therapy well that the first bullet point is sort of they catch all so obviously good performance that is patient These patients should be asymptomatic from their disease I have low volume and slow growing growing in quotes there because I know when I see it But I'm not sure I know how to define it And I think you all sort of know it from looking at scans and taking care of patients You know just from sort of that gestalt of looking at the scans how much tumor burden there is and hopefully you have a scanner to To help to help you understand the natural history of this particular patient's disease So a common patient that we would observe is patients who had an effect to me a few years ago And then they have maybe some little nodules and maybe they've grown and maybe they've grown and so you have a few scans to sort of Reassure yourself of what the natural history is in this particular patient We recently collaborated with the centers you see there around the world doing a prospective study that will present it ask Oh, but I will tell you a little bit about in a few slides Basically because we all do this in clinical practice and it's a lot of retrospective experience And when patients walk in the door with already several months if not years of scans It doesn't those patients are obviously selected so it doesn't really help you understand the natural history if you look at it Retrospectively so we wanted to prospectively understand the natural growth rate in this subpopulation To look at clinical outcome and treatment is started so we could say to a patient that we can safely observe you and when we start your Treatment in six months or 60 months. You're gonna have the same response rate We looked at some anxiety and depression scales thinking that this that the burden of watching in untreated cancer might be hard on patients And we also collaborated with Jim Finke my main immunologist looking at their immunomitulatory profile such as MDSC's and t-rags thinking these patients might have Sort of different profile a naturally favorable profile if you will And then in terms of when to start treatment in this particular study was obviously left to the to the discretion of the treating physician For myself and what I told patients at the start is that if they had an increased pace of disease If they had new organ sites if they developed symptoms from disease Which I don't think happened to anybody or if the doctor or the patient got nervous Then we would start treatment and it was really sort of the first one or the first two and we're collecting The data of why they started treatment also on this trial So I'll present sort of the full data at ASCO But here's a little bit of a taste so this is there were 52 patients that were put on you could see the patient characteristics I would point out the median age was a little bit older 67 So again sort of like in the example not surprisingly patient Physicians that are a little more out to watch Patients who are a bit older that 50 52 year old were a little nervous about watching that patient We want to be more aggressive with quote-unquote younger healthier patients otherwise Mostly male obviously E.C.I.G. zero clear cells so these are sort of typical what you would expect about one out of ten patients had prior metastasectomy So the eligibility for the trial was that you had to be diagnosed with metastatic disease within a year of enrollment And the reason we did it that way is because we often saw patients who came in and they had to scan three months ago With those small lung nodules and then we saw them and lung nodules were a little bit bigger And so in essence in retrospect they were they were clinically diagnosed with metastases three months before we saw them So we needed to allow a little bit of that Time to have passed in order to be able to enroll those people on study But about 10% had had prior metastasectomy again speaking to the favorable favorable biology You don't take patients to metastasectomy over rapidly growing disease I think maybe somewhat surprisingly when we looked at Danny's risk groups most people were intermediate risk So you would have expected maybe that this would be a very predominant Favorable risk group, but I'm actually most patients were intermediate and we'll look at the specific breakdown and then baseline tumor burden again, I think goes into our our gestalt about Whether we should watch a patient and the baseline tumor burden was just over three centimeters so I would I think that would probably classify as low volume and we looked at a Separate analysis of patients receiving soon it and when we were looking at tumor burden characteristics I think our baseline tumor burden was more about 12 or 14 centimeters for patients walking in the door So this is obviously low volume. Although you see there are some high volume patients who were observed The median time until systemic therapy was started was just over a year about 14 months And you could see the 12 and 24 month rate there So on average we were able to watch people about a year before starting systemic therapy keeping in mind that the start of therapy was Entirely physician slash patient driven there wasn't an equation to say if their disease increases by this much or at this pace Then you have to start And then just some sort of bullet points here One thing I thought was interesting is that the median growth rate again in this highly selected population Was about point one four centimeters per month. So about a millimeter and a half per month now again We're not necessarily we're using resist here So we're not necessarily capturing every single site of disease right if they have ten lung nodules We can only measure three right three five overall and three and one organ So it doesn't necessarily capture everything, but but I thought that was surprisingly small But half the people have come off observation 25 patients have gotten therapy and I just looked at these data before I came They've really gotten a mix of therapy So I'm not sure we're gonna be able to say a lot about their response to systemic therapy Some of these people who are at our center they go back They drive a long way to see us and then they've been observed for a few years They get tired of driving they go back to their local doctor And so we don't have the follow-up on their systemic treatment to be able to record We looked a little bit preliminarily and we'll look a lot more at this in terms of how fast do people grow and who is the best Observation patient IE who has the slowest growth rate over time The only thing we found sort of on a preliminary look that was of borderline significance was baseline tumor burden That you see there obviously patients with smaller tumor burden being observed longer and that makes sense again as a Physician when you see that scan with accumulating disease you get more and more nervous about withholding treatment on that patient Location or number of matastatic sites did not impact the length of observation and we did all these fancy anxiety depression scales And they really didn't tell us anything patients We were concerned maybe that patients wouldn't this trial would be hard to accrue that patients wouldn't want to be observed And in fact patients love not getting treatment. They're not anxious about it They're actually anxious and depressed about getting treatment. So we didn't really find anything and we didn't find anything in the At least on first look in the immunologic parameters in these patients They clearly have a more favorable profile than Patients who receive immediate systemic treatment within this group at least on first look nothing that was striking Turning out is sort of taking breaks in systemic therapy. So Starting several years ago when we started using systemic therapy We'd have patients who are on therapy for a period of time months to years and they'd come to us and they say Gee, I'm tired of taking these pills. Can I stop and so that was sort of the night is to say, okay Gee, maybe we can give patients holidays And again, we'll present it ask her this year pretty much all is one of my fellows who will present this in a poster highlight session We've collaborated with Bernardus Goudier's group and we published these data initially and this is sort of an update of those data Basically looking at kidney cancer patients on targeted therapy Who had a period of drug cessation for greater than or equal to three months? And that was our completely arbitrary definition of how we define patients who took a break Obviously, we didn't want them progressing and taking a break. That's not the patients We're looking at we're talking about patients doing well on therapy Who choose to take a break? So we have 112 patients so fairly large experience I think we're our comfort level in doing this has grown over time you can see the characteristics there again not all Favorable risk although I in this particular group of more of a predominance of bid risk patients again You're taking advantage of that natural biology to either delay therapy or in this case take a break from therapy And here's sort of first sort of blush at the data If you look at the treatment here is is basically the break So remember there's 112 patients that all took a break so the first break everybody took right That's how they got in to this analysis And then there were smaller groups of patients who took a second break and a third break and a fourth break And that's what these bottom three rows focus on But again if you just sort of focus your attention here patients were on therapy a little over a year And then we're able to take a break from therapy that was almost a year and a half again highly selected retrospective experience We would certainly admit this is not necessarily average patient I'm not saying the average patient can take a year off therapy, but there's a I would say sizable minority of patients Who have a favorable biology who may be able to take a prolonged break of therapy and again obviously no no therapy No toxicity right that's the best part patients love delaying therapy They love even more taking a break from therapy, especially if they've had side effects Which is often why these patients took a break not necessarily any one terrible grade three side effect It was often an accumulation of grade two side effects as you might imagine And then I'll end just talking about our prospective intermittent study We've presented these data at asco last year and the paper is working its way into draft form this was Again based on that retrospective experience. We say well gee maybe we can look at this prospectively Maybe we can treat people for a little while and then take a break and then retreat and when they grow and give them some time off therapy This was the study schema. So this was a up front metastatic clear cell patients no prior treatment They got four cycles of standard Sunitin of 50 milligrams for two four cycles was a completely arbitrary time point But it was felt to be enough that generally if you're going to see a response in tumor shrinkage You see it within the first scan or two if patients had their overall tumor burden decreased by 10 percent again Arbitrary threshold would felt to represent something that that was meaningful that represent some reasonable degree of Anti-tumor effect then we held their drug scan them approximately every two months and then started their drug again when their tumor burden grew by That same 10 percent compared to the tumor burden when they stopped So they had 10 centimeters of tumor burden when they stopped when they grew to 11 centimeters Then they would they would start again and you can see that again 10 percent threshold was set fairly low So as not to withhold treatment from from patients who we thought needed it again an arbitrary but reasonable threshold They then got two more cycles and again if they shrank again Then they held again and sort of entered this on and off intermittent phase Obviously patients who had more primary refractory disease either continued if it was appropriate or changed therapy So here the results again not sort of in final form But but fairly final 37 total patients 20 were eligible for in for the intermittent therapy and all entered the intermittent phase and actually when we Sent this study to scientific review many years ago. They said well G Why would patients who are on a therapy that's working stop and we don't think that that it would be ethical to do this or we don't Think actually patients will go for it. So why don't you make your primary endpoint feasibility? Feasibility that patients who are eligible to stop therapy actually stop so fine So we did that and ever and again patients love stopping therapy. I've had patients on this study say to me I can't believe some people just keep taking the drug So all patients entered the intermittent phase Patients who didn't really were just patients who had progressed before four cycles a couple people who had either toxicity or with your consent And you see that I'm trying to my point you're here that Almost all patients 80 percent did have that 10 percent tumor burden increase at the next scan So for this is obviously a less selected population than the observation patient These were just same as any patients we put on frontline trials most people not all but most people had that 10 percent increase at that first Scan after the break they increased by about 1.5 centimeters. So not much these patients weren't taking off in disease all this Discussion that G when you give edge at TKI's and then you stop it. There's this rebound effect and patients grow faster I happen to think it's a bunch of nonsense I think these data show that patients do not take off when they when they stop therapy they increase actually fairly modestly And we had sort of an interesting group of patients And I'll show you some graphs who who didn't have a tumor burden increase Offsunit and who were able to sort of maintain that off period for longer a longer period of time I'll show you this sort of soft-tooth patterns. There's different and you can see here again We sort of just crunched some numbers basically saying that we gave you know about a third A third reduction or so of the Sunit and that normally would have been given So we're giving let less drug yet able to control disease for a reasonable period of time So here just some representative tumor burden changes mostly what we saw was what we call this stable sawtooth pattern So if you take this is just one patient Here's a baseline tumor burden not quite seven centimeters It's very typical Sunit and in response most of the tumor shrinkage after two cycles a little bit more after four cycles Then we hold their drug they grow by about you know a centimeter or so Then we started again. They shrink again. They grow again. They shrink again So they're going up and down, but the the pattern of their tumor burden is generally stable over time We saw some patients who had a declining sawtooth pattern again. The name says it all it's going up and down But it's generally getting less over time So I think you could make an argument that this particular patient probably Could take longer breaks than the eight or ten weeks that we gave them everybody got the same break Of course in a prospective study, but in retrospect you could say gee if we want to keep this patient's tumor burden Sort of that you know where they were at their at their response point. We could probably take longer break Some patients had an increasing sawtooth pattern This is obviously more worrisome and when we saw this when we saw this repeated in this kind of patient We would take them off the internet and or we would shorten it So we'd say gee eight to ten weeks is too much Let's try four to six weeks and then in some patients obviously for clinical reasons We said this is not for you. You just need to be on standard drug And then we had some interesting patients This is probably our most interesting who had biopsy proven metastatic disease had had a metastasectomy Previously had some pancreatic meths came down after two cycles and four and held and has really been in this holding pattern now for Four I believe a couple years. So these are patients. I don't understand. They're obviously the most interesting But they're not not typical And this is just the aggregate over the first three-stop start period is basically saying that for most patients They come down and are in the stable pattern, but I showed you the individual patients just now So in conclusion kidney cancers are very biologically unique disease It has a wide spectrum including I think a fairly significant subset of patients with inherently indolent growth I think we can better take advantage of that natural biology Including observing some patients and some for a long period of time if that patients on our observations study I believe for at least three to four years and some of the longest patients and also intermittent therapy And really it's all about balancing risk and benefit, right? These drugs aren't curative these current options aren't curative And so we're trying to balance control of disease with the day-to-day toxicity And I think there's more work to do for defining the appropriate Subset for how we can sort of apply what I told you today. Thanks for your attention