Okay. Thank you, Dr. Gore. That was excellent and good. We're a couple minutes behind, but I'd rather stop for questions and get people's involvement and we can fudge a little bit on our break times and catch back up. I don't have any video display in mind, so John set the bar high. I should have put you at the end of the day, John. Oops, that's no good. I can lug in myself. We need our AV help. Yeah, it is. Oh, okay. Good, good. If we're all set. So I want to talk for a session today about adjuvant therapy for kidney cancer. So what does that term adjuvant mean in cancer therapy? So adjuvant therapy is additional treatment that would be given after primary therapy applied, usually for most cancers implying definitive surgical treatments. So you've taken out a tumor surgically. You're leaving the patient without any identifiable measurable disease. And you know historically, depending on the characteristics of the tumor, the staging that's applied to the tumor, usually you have that data after the surgery is complete. You know that there's a risk for future recurrence and the stage distinction is how much risk. And so the questioner then arises, well, can you change that risk? Can you apply a therapy after you recover from surgery that's going to decrease the risk of a future disease recurrence? And typically we're thinking about primary surgical therapy and just as Dr. Gore was speaking about, for kidney cancer, surgery on the kidney, taking out the primary tumor. And for adjuvant therapy, usually we're thinking about modalities like radiation therapy or medical therapy. So as a medical oncologist, primarily thinking about what medicines could be applied that would change your future risk of disease recurrence for kidney cancer. So going back to a slide I showed you at the outset that for kidney cancer diagnoses, the majority of patients, the solid majority, have a localized disease.  So this is going to come up with regularity patients. They're now post-surgery and wanting to know what should come next. If you look at what's the hazard of recurrence of kidney cancer, this is data from a large national database called SEER. So in all commerce across the board, not thinking about the stage distinction, five-year survival rate for kidney cancer is 74%. That's not such a helpful number because we're always going to tease things out in terms of what's your stage of diagnosis. In this data set, they didn't use the stage one, two, three, four distinctions, but local, regional, or distance spread. And so local kidney cancer is basically going to be stage one or stage two tumors. They're only in the kidney. They're not impinging on some of the associated structures like blood vessels and lymph nodes. And the disease control with surgery is excellent. So five years greater than 90% survival in this data set. Regional kidney cancer implies, again, a localized disease process. It's only in the kidney, but now there's something about it that increases the risk of future recurrence. It's beginning to follow the blood vessels. It's in the renal vein. It's growing through the kidney tissue proper. It's into the fat around the kidney. It's showing up in lymph nodes associated with the kidney. So the surgeon is still completely removed the tumor. But now you're looking at typically a stage three kidney cancer diagnosis. And in five years risk of recurrence is about 35 to 40%. There are later recurrences. I generally quote patients about a 50-50 lifetime risk of recurrence with stage three kidney cancer. And then distance disease means the time of diagnosis, you have metastatic disease. And in that setting, in a fairly contemporary cohort, five years survival only 12%. So that falls into the realm of treating metastatic disease, which isn't the primary focus of this talk. But depending on your risk for patients that are considered to have high risk localized kidney cancer, it's a very valid question. Could you not apply a therapy that's going to change that risk? Decrease the risk and save lives because a subset of patients won't have their cancer come back because you apply an effective therapy. There are some terms commonly used in research studies that are slightly different. And so I thought it was worth just going through for a moment. What is meant by disease free survival if you're looking at a study versus overall survival? So disease free survival at any time point after the study begins, a patient that's had surgery, the cancer is removed. And so post-operatively there's no evidence of cancer. And now you start the clock and you watch that patient moving forward in time. What percent of your population of patients remain without any cancer findings? So you've failed, you're no longer in the disease free group if your cancer comes back. Doesn't mean that you're dead. You can be living and treating the recurrent cancer. But as far as the cancer comes back, you're no longer in the disease free population. It's faster to measure disease free survival than overall survival because as patients have recurrence of their cancer, maybe they can have surgery, maybe they're going to get medical therapy. There can be a very long time interval from detecting disease recurrence before that cancer may progress and the patient actually dies of that cancer. And then becomes an overall survival data point. But the problem is, what if you apply therapy that delays the time to cancer recurrence, which seems like a good thing, but doesn't ultimately prevent the cancer from coming back? So if you wait long enough, everyone destined to have their cancer recur, it ultimately all recurs. And is that really getting you anywhere? Have you gained anything? Because maybe the progressing disease, when it grows back and it's been treated with the medical therapy, is now different. It's more aggressive, it's harder to treat. It's intrinsically resistant to the therapy you applied to try and stop the cancer regrowth. And so maybe you do worse treating that cancer when you can see it on scans and you follow it.  And so that is the concern when you look at disease free survival. Is that faithfully giving you insight that you've gained an overall survival? So we prefer to know about overall survival, which is that at any time point, who's alive and who's died. Now death can be from any cause. You're giving up the fact that it's closely linked to the cancer. But it's short time intervals after a cancer diagnosis, one year, two years, three years, even five years, the hazard to the patient is far and away greater for the cancer than for other processes. And if you're doing a randomized study, risk of death from other medical conditions should be balanced between groups. So that generally doesn't come into play as being a major concern. And it's really for an adjuvant therapy, the gold standard applied for most diseases is you want better overall survival if you're truly going to believe that a therapy should be applied and you're really gaining value for the patient. So just one slide on radiation therapy following nephrectomy. It's an issue that has been looked at, although the data sets are not terribly contemporary. Older data, 80s, 1990s, there are two randomized studies and then there's a larger meta-analysis that I think most people kind of refer to as being the definitive statement. The two randomized trials pooled with other studies that were retrospective in nature, 735 patients. And the question is if you apply radiation on recovery from nephrectomy to the surgery bed to come out ahead, do you prevent disease recurrence? The answer is no. There's no clear survival signal. You're not gaining disease control that rises to better survival. And so generally that's not offered and not done as a routine therapy. So thinking about medical therapy and drug development, the drugs that we have available for kidney cancer and applying those in the adjuvant setting, and we're going to look at where we stand with different types of drug therapy. But as you think about the development of a drug for cancer of any kind, including kidney cancer, it has a very stereotypical progression of how the drugs are evaluated. So typically the first time you try a brand new therapy that has a scientific rationale, it seems like a smart thing to do for a certain cancer, but to prove the point that it actually has value and it can treat the cancer, usually you're going to do a first study in patients that have more or less exhausted good therapies for their cancer. You don't know what you're getting into. You don't know the risk. You don't know if it's going to work. And so patients typically are required to have failed at least one or sometimes multiple prior therapies. And for diseases where there are curative therapies, usually the language of a very first study would require you've exhausted all modalities that might cure your cancer. So ethically you really need to be, and unfortunately a bad spot for what's on the table for standard cancer therapy to make it worthwhile to embark on something that's quite investigational. For a drug that looks promising, it works well. Maybe it goes all the way forward and gets approved as a second or third line therapy for a cancer. If it looks quite compelling, then the question is, well, is this actually the best available therapy for this cancer? And should you start off with this drug and use it right off the bat because it's the most potent drug? Treatments that typically begin at the back end of a list of therapies for cancer then come up and get looked at as perhaps the primary therapy and usually in a comparative fashion. Is the new drug better than what's the current standard? Head-to-head comparison study typically large, what are called phase three trials. And so drugs that prove to be potent in that setting will almost always then be looked at in a preventative or the adjuvant setting. So here's a drug that works very well for our cancer. If we've discovered it, we've proven it has value. In fact, it's the most potent drug we have for this cancer. Can it actually work in the preventative setting in patients that have had local therapy and now we're fearful the cancer is going to come back? So that's the general progression, which means the timeline of getting around to the adjuvant questions, usually at the end of the list of doing several studies with drugs. And so it's not usually the first question and drugs that are newly available. Typically you don't know yet what's their role in the adjuvant setting. This is a little schematic that just gives you a broad overview of the drugs that have become available for kidney cancer and how the treatments have changed in their nature in the way they attack the cancer.  It wasn't for lack of trying. There are dozens and dozens of studies of all sorts of chemotherapy agents, hormonal agents, that were very, very ineffective and generally not helpful. In the late 1980s, interferon alpha became available as a therapeutic agent, followed shortly thereafter by interleukin 2. And so those two drugs were called cytokines. They're recombinant versions of hormones your body makes in response to immune stimuli. Worked well enough that they showed benefit and they got FDA approved for treating kidney cancer. And that was standard therapy for a very long time, from early 1990s until 2005.  The world changed in 2005 with the first approval of an oral targeted therapy. Seraphanib was the first drug in class, but rapidly followed by several other drugs that were very similar and in fact mostly replaced by the other drugs that appeared to be incrementally better. So targeted therapy, which right now is front and center and most patients are receiving these drugs and often multiple of these agents in the same drug family. So the era of targeted therapy. And then the world changed again in 2015. So November 2015, the FDA approval of Nevolumab, first in class of what are called immune checkpoint blocking antibodies, the only one so far approved for kidney cancer, but there's several other commercially available similar drugs for other diseases. So an immunotherapy compound, attacking the cancer in a different way, and that's the immunotherapy class of drugs is really dominating clinical developments and research studies in the last several years. So where do these drugs stand in terms of adjuvant therapies? The old cytokine drugs have been looked at and then were tested in well-designed clinical studies looking to see if they have a role in being preventative therapies for kidney cancer. So I show you a couple of these studies listed out that comes from a research paper that shows what's called a force plot, so sort of a tree-like structure, showing you the relative hazard ratio and the statistical variance of those hazard ratios. What that means is what's the relative effect of the treatment arm versus the observation arm. So absolutely no difference. The survival you measure is exactly the same, would be 1.00. A smaller number would imply the interferon treatment did better or the lotus interleukin-tuplis interferon. A number greater than one implies that observation action was better than the therapy applied. And then if the variance around the measured value crosses 1.0, it's judged that these differences are not statistically meaningful. And so there's three independent studies and then they were analyzed in meta-analysis, meaning pooling these results. So 840 patients getting cytokine therapy. And there's a slight increase above 1.0, but a confidence interval that overlaps 1.0. So the interpretation is no meaningful difference between applying cytokine therapy versus doing nothing at all and just watching patients. So not a helpful intervention. Interleukin-tu, back in its day, when it was the only drug available or the only drug with interferon, was experimented in all sorts of regimens and doses. There were low dose regimens that were outpatient administration, very well tolerated. There's a high dose regimen. Some of you in this room may have received far more toxic and unpleasant requires an inpatient hospital stay. That approach, the high dose approach with IL-2 has been tested is in a prophylactic way in a fairly small study, but no positive benefit in patients. And that approach has not been revisited. Certainly not a therapy for everybody would be a selected subset of patients. But no hint that that's moving in the right direction. So the cytokines have been looked at in that context and really abandoned as being a useful modality. What's front and center and data that's beginning to emerge from large clinical studies that take many, many years to organize, to enroll patients and then to wait and see as the data emerges what you've learned. So in one slide really presenting an impossibly large amount of work, hundreds of cancer cells hundreds of cancer centers and data collection spanning a decade or more. So it's really a tremendous amount of efforts. Six studies that have looked at the issue that the new generation of targeted therapies have a prophylactic role in managing high-risk kidney cancer. So the first study of the Assure trial 2006 and the last study of a similar kind the ATLAS study that began in 2012. All studies I believe have enrolled all the patients that they intended and they're all now just tracking the outcomes of those patients. And three of the six have reported results and the most recent I'm going to spend a few minutes on what's called the PROTECT trial was a study that we participated here at SCCA a randomized study where patients either got the drug pisoponib also called votrient or were receiving a placebo. All of these trials except for one of the study drug. And so very very similar structure you're getting a pill you don't know for sure if it's the real medicine you're taking it for a year and then you're being followed by a surveillance calendar very reminiscent of what Dr. Gore talked about that would be consistent with treatment guidelines to see what happens to the two different patient groups. The last trial here the ATLAS trial is going to treat patients for three years with the ACSITNib so a little bit of insight the company that makes ACSITNib own SNITNib and undoubtedly had insight that the one year of SNITNib was proving to be unhelpful and so they decided to do a different experiment and go longer. So we'll see if that's meaningful. But let's just take a look at some of the results this was the ASCO meeting in Chicago June 2017 first public release of results with pisoponib and one figure I particularly liked that I think gives you a graphic impression of what are we asking of you as the patient these medicines are not innocent drugs they come with side effects people don't feel well and this is a quality of life questionnaire patients filled out over the timeline of the PROTECT trial so the placebo patients that were taking nothing just a fake pill are the yellow line here and so they felt normal they felt fine and the score value 0.0 that's your baseline patients taking the true drug pisoponib they felt lousy for a full year on therapy but as therapy ends the side effects go away and they go back to feeling fine but this drop off in quality of life that's given a quantitative metric that's arbitrary I just think that's a lovely graphic representation that it's not a free ride you're taking a year worth of drug that's making you feel lousy for years kind of a long time that's a lot of effort and work and bother and so what is the gain well the gain is so far absolutely nothing at all unfortunately when you look at the survival curves of the two treatments placebo or pisoponib they're almost completely overlapping and there's no statistical difference between these curves so the gold standard test the overall survival benefit of this drug was absolutely nothing the disease free survival which was also captured and measured also was judged to be statistically not different and so unfortunately a negative study not showing benefit for pisoponib and to summarize so yes good question you had to have localized disease and high enough risk to judge it to be worthwhile and so I didn't print out the enrollment eligibility for most of these trials all stage 3 patients were eligible for many of the trials you could be stage 2 but then you had to have other features the nuclear grading scale on your pathology report had to be a high grade tumor usually grade 3 or grade 4 from stage 2 and then any stage 3 is the usual cut points by and large for the different studies so if you look at the three different large trials that have now been presented in terms of outcomes the assured trial actually had three different treatment arms it had a suenitinib which is suetent it had seraphonib, nexivar those were given as separate independent therapies not given together and then placebo so three different treatment groups in that study very very large study, 1900 patients and there was no disease free benefit and no survival benefit so completely negative experience delivering those drugs for one year therapy first reports with this approach very very disappointing for the field I must say people were very optimistic with this approach before the data began to be released last fall the S-track study presented its results and curiously it's a second study with suetent and that did show statistical benefit of disease free survival but so far overall survival shows no difference and so that's the odd dichotomy are you just delaying the inevitable and are you really getting anywhere so I think most people in the field will hold the study to showing a survival benefit before there would be moved to think that you should be recommending suetent for patients but it's very puzzling that the same clinical experiment was done twice and came to a different conclusion and in all honesty there's really no explanation for that people have sort of hemmed and hawed over what was done differently and wasn't meaningful but you know there just isn't an explanation and then the protect trial brand new data from a month ago negative for disease free survival negative overall survival so I think in the bulk of evidence three different experiments, different drugs similar approach, year therapy and it doesn't seem like we're getting anywhere as adjuvant treatment so we certainly have not adopted trying to use any of these drugs in the adjuvant setting a standard of care none of them are FDA approved to be used in that fashion either so you couldn't easily write a prescription for patients even if you wanted to go that route so if we go back to our schematic here so we've crossed cytokines off the list as not being helpful we're right in the thick of learning about the utility of the targeted therapies there's still trials that haven't been complete but we're becoming quite pessimistic that you'd think if any of these drugs work they probably all would work and so a couple of negative trials have really poisoned the field and I think at this point nobody's really expecting that the pending trials are likely to be dramatically positive so what's coming next what's coming next is taking the new class of drugs the immunotherapy drugs and doing the same experiment and seeing what happens there so just a quicky cartoon about what do we think we're doing what's the biology of the new generation immunotherapy drugs starting down here on the left we know that tumors are abnormal cells many of the cells within a tumor mass are dying even though the tumor is growing larger so it's creating material that's picked up by the immune system which is the scavenger system getting rid of dead cells and there are immune cells whose job it is is to show the immune system material that's being chewed up and metabolized to make sure there's nothing there that's abnormal and so the important cell in your immune system that can actually detect an abnormal cell like a tumor cell and turn on and react to it is called the T lymphocyte or T cell so that's central to the biology of what we think is happening spontaneously but just not happening and working to a vigorous degree that's curing the cancer when T cells turn on they turn on a whole organized program of gene expression they become activated where they can recognize and kill off a target which is good but they turn on a mechanism to shut the whole system down so it doesn't go crazy and damage normal tissues and so as T cells activate and go out and find targets they begin to express proteins that can shut them off and one of those is called the PD1 protein that's on activated T cells so T cells that are inside of tumor tissue and crawling around and hopefully giving you an anti-tumor effect can encounter the binding partner for PD1 called the protein PDL1 PDL1 can be made by the tumor itself so the tumor shields itself it defends itself by making a protein that can turn off immune cells right at the point of action where the T cell is bumping up against tumor cells and so blocking this interaction on either side of the equation either blocking the PD1 protein or blocking the PDL1 protein represents this family of what are called immune checkpoint drugs and they're proving to be widely effective across numerous different tumors and becoming some of the most widely used drugs across cancer in general and can work quite well in some kidney cancer patients so what's coming and is going to be looked at now in the next few years is applying these drugs in the adjuvant setting in large studies several hundred patients and trying to prove to point that these drugs do or don't have a prophylactic role in the setting of kidney cancer there's a similar drug that's not listed here a drug called Urvoi or Ipilimumab that's FDA approved for melanoma that has had a positive adjuvant study in melanoma patients so that's definitely encouraging people to think that this drug class may be unique and different and better than the other types of drugs that have been tested and will actually show us a true benefit in this setting but it's going to take several years to collect and then wait and analyze the data there's four studies that are all overlapping each other and open and rolling at the same time the emotion trial is using the drug Etizelizumab the prosper trial a drug called Nevolumab which is an FDA approved drug for kidney cancer the keynote study using Pembalizumab or you may know that as Ketruda and then the checkmate trial is combining Nevolumab with Ipilimumab or Urvoi so a two drug cocktail the only study that's combining more than one drug in this setting it wouldn't make sense for a single cancer center to have all these studies open because they're redundant they're recruiting the same patients high risk patients high risk stage two and stage three patients with kidney cancer so at our center we have the good fortune of choosing amongst these and are going to open the keynote trial that's Ketruda or Pembalizumab trial that's in process should be opening later in 2017 and so anticipating that study will take anywhere from one to two years to enroll patients we'll have a chunk of time where we'll have the opportunity for patients to participate in this study to maybe get a prophylactic immunotherapy drug recognizing it's randomized and blinded so 50-50 chance you're getting the true drug versus just saline placebo infusion so you have to be okay with that scenario so where do we stand for adjuvant therapy you know there could have been one slide with the big red slash there is no FDA approved proven effective adjuvant therapy for kidney cancer despite lots of well done large studies trying to identify an effective approach so standard of care at this day and age continues to remain ongoing surveillance for patients with no recommended active therapy there are pending studies that are complete and we're just waiting for the data to mature with targeted therapies so there's the chance that one of these drugs will show a benefit and actually come into the field as a possible therapy for patients but so far results are disappointing and so fields getting fairly pessimistic that it's going to bear fruit with targeted therapy and then the immunotherapy trials are just getting up and going so it's going to be several years before we have an answer but that'll be something that's at least available and ready in prime time for patients question so yes nothing unfortunately is risk free you know although we like immunotherapy drugs for our patients and think they're sort of quote well tolerated there is a side effect profile 10 to 12% of patients in the metastatic setting will be forced to stop therapy for so called intolerable side effects there's even the risk of side effects escalating to being a cause of death in upwards of 1 or 2% of patients in the metastatic treatments patients that have metastatic cancer are motivated to do something about their cancer and they're willing to assume a greater risk it's an awful experience to take somebody that is completely healthy has negative scans for cancer put them on a therapy that makes them severely ill or they even die from the attempt to treat their cancer and prevent that because you don't know if they're destined to have their cancer come back so it's a whole different world where your tolerance for risk and toxicity is quite different in an otherwise healthy cancer free group of patients at least at the outset of therapy when it comes into play about this panel of studies there's not a huge amount of difference between the different drugs but perhaps some slight differences but the one approach where you're combining two drugs together clearly increases your chance for bad side effects and so that myself and my colleagues looking at our opportunities was something we discussed and we're fearful about based on our experience with our melanoma patients our convoy therapy for melanoma is given at an unconventional high dose and the side effect profile is fairly extreme and we have had patients that came into that treatment completely healthy and had really terrible problems and that's again that's a very awful situation so we'd like to think Pembrolizumabg only goes pretty smooth but there definitely will be a subset of patients where it causes some pretty unpleasant side effects hopefully not arising to the level of patients actually dying statistically most patients are likely to have mild or no side effects but again it's not risk free question here so the data for that approval came largely from a trial called the checkmate 025 study so randomized phase 3 trial in Pembrolizumabg was compared to an approved drug called Affinitor or Everlymus head to head 50-50 and was the better drug for the antitumor effects was actually the better drug for patient preference and side effects as well so that was most of the data this company bundled smaller precursor studies as well into their filing with the FDA that study probably took about three years to complete I think the timeline of the immunotherapy drugs was really brief the movement through advanced clinical testing was very rapid in part for the enthusiasm with these drugs and in parts for the competition from other companies that had similar drugs and knowing that they were clearly effective and were going to be winners and get through the FDA there was a lot of intense pressure to try and beat the next guy and get your study done so it went very quickly the average timeline from a new drug being tested in the clinic for eight to ten years the FDA has tried to accelerate that and so something more like five to six years in contemporary time is probably more typical so a three to three and a half year timeline is actually really quite short so these studies are all for localized kidney cancer so some stage two and stage three patients trying to be preventative therapy Nivolumab is approved for advanced for stage four kidney cancer and now it says you had to have had a prior therapy that's no longer working like Siu-Tent or Votrient there are studies that have been completed but haven't been reported where Nivolumab has given us primary therapy first therapy for kidney cancer if those studies are positive then it will change its FDA guidance and you'll be able to prescribe it as the initial therapy for patients so that's pending data the word on the street is maybe as early as late 2017 as it was presented publicly and that may change the use of Nivolumab so once the drug is FDA approved as being prescribed to patients there's no active data collection so the broader experience isn't being actively measured and quantified there are mechanisms where physicians can report to the FDA particularly bad or unusual side effects so the FDA does have a reporting mechanism where the FDA physicians get these letters soliciting data entry and data collection for patients that report side effects I believe to the dispensing pharmacy you get a call and if you tell the pharmacy contact that you've had certain side effects that they send off a note to the FDA that triggers a mailing to the prescribing physician trying to collect that data trying to get real world side effect experience that's an obligation for the doctor to actually send that data in I can just throw that in the trash and ignore it so it's highly imperfect question in the back so right for any doctor prescribing a treatment as a standard therapy because of FDA approval what happens to you is not actively collected unless you're participating in a study so for example the company that owns Nivolumab that we participated in that included patients that weren't part of the study that gained FDA approval so that study only allowed for example clear cell histology as your diagnosis they did an add on study and they allowed any kidney cancer diagnosis so papillary kidney cancers, chromophobic kidney cancers could receive the drug even though the FDA doesn't restrict the use to clear cell so you could have prescribed it for a patient but in a study then you know the data is being collected and it'll be analyzed and you'll learn something about patients that weren't part of the patient experience that was the data leading up to FDA approval but you have to be formally enrolled in a study to have the data collected and actually analyzed for most people it's simply standard of care therapy and it's not something that's being collected so yes, so most studies there's active therapy but if that active therapy ends you'll know what happens to patients for disease status new scans overall survival unless the study closes down and simply says okay we're done that's all the data we're going to collect or a lot of times you'll be monitored unless you start on some alternate cancer therapy and then at that point in time you leave the study for any ongoing assessment because they assume now that's going to muddy the waters it's hard to judge what their drug has accomplished because now you're receiving some other treatment for a study you're monitored if you're not doing any active therapy you're part of the study but then if you receive a next treatment then you leave the study formally at that point but ongoing outcome for overall survival as a long long tail for research studies is very common question in the back so I mean a good portal is your doctor but you know most community physicians do clinical trials so they may or may not be very aggressive in helping you find stuff there is an excellent web portal this clinicaltrials.gov is the most comprehensive listing site for clinical trials of all kind it is kind of daunting if you search for something and you get 50 or 100 or 500 clinical trials that populate a list that you pull up how do you weed that down to things that are actually relevant but that might be an area where you could meet with your doctor and help sort through things that you're interested in or things that you've found you know a cancer center like ours where a big part of our mission and our goal is to participate in research ideally we're going to know we're going to have things here but if we don't have it we could tell you in a fairly educated way what might be available to you in the greater northwest in the cards that you travel to some fairly far-off cancer center research trials are always linked to the participating center and so if you went for an opinion at MD Anderson or Sloan Kettering or Cleveland Clinic and they had a trial that sounded really exciting you usually can't export that and come back home and be in the study and be here in Seattle you have to work with that cancer center as you're treating doctors the doctors analyzing your scans you have to either commute or live in that city and so for most people that's not really in the cards but for a few folks you have friends, you have family you can actually come and go to Houston or some city that has a cancer center that's doing something that's interesting to you it might be feasible but that's an unfortunate feature of the clinical trial process question here so that study is for metastatic disease so first line therapy for patients with stage 4 disease this is all for patients with localized kidney cancer so stage 2 or stage 3 so different subset of patients if I can just mix a number of drugs together hopefully that I'll find the right combination to come out do you see the artificial intelligence and machine learning to like take some of these trials and quickly get to the bottom of whether there would be a positive outcome and with the question in the back also I was doing some research and it turns out that usually about studies that come out for a week or more than the research center can digest so some research centers are using IBM Watson to get a more global view of this is the 10,000 trials that happen this week so people have access to all the insurmountable amount of information that needs to be digested and at point to different possibilities for their individual treatments well you touch on a number of issues the idea of how can you quickly figure out what might be the best therapy comes into play so with the immunotherapy drugs that are available there's a zillion similar drugs related drugs other immune stimulating drugs and so right now the field is fascinated with combinations give one of these drugs plus something else and how can you quickly figure out which ones are fruitful which ones are not going anywhere and what is called TASC the company that owns Nevolumab has piloted what they perceive to be a strategy to rapidly work through a whole series of two drug combinations in a more efficient way than the usual mechanism called the fraction protocols for different diseases we'll see how that works out on the one hand investigators that are specialists unlimited number of drugs that have enough data that you know they're clearly working and so having a feel for what should be looked at in a definitive large study I don't think is something that you can't sort out fairly easily but what you touch on is the universe of all possible clinical trials is immense every time I go on clinicaltrials.gov and search for something that I know about I hit on all of these studies that I never even knew existed that I look at them and I'm like oh that's pretty cool but we'd like to have that so it is there is this massive world of studies and anyone cancer center can't possibly participate or even really know in completion what's out there and available but you know pragmatics are that you'd have to travel and go to different cancer centers all over the country if you want to participate in these different studies I mean there is what's available in your own backyard but then there's this massive world of other things you might be interested in so for the person that they're not limited you know and travel in time and could actually truly search the entire country for an interesting study that is a very daunting task and even your local oncologist probably isn't completely up on every last thing you could find in a web portal like this and that's I don't have a perfect answer for that there are commercial clinical search services that will help you identify relevant studies and help contact centers find out if they're actually open and rolling I have had a few patients bring in lists provided by services to help them try to identify studies so that might be something useful but most people are limited by the reality that if they saw things in other places it's not feasible yeah this can be something that you invent so we'll see you in Shark Tank spinning your idea I mean it is it's a great topic I don't have a perfect answer so for any study you participate in if you're actively working with us and we know results have been published we try to tell you that you know there's public announcement of your study and what things look like I don't think the study mechanism itself necessarily contacts you and like would send you a participant letter announcing that you know here's the results of your trial they've just been published I think it's kind of on the doctor to tell you well yes the goal of these studies is to identify an effective therapy that then gains FDA approval that everyone can use it and prescribe it so every oncologist should be on guard for new definitive studies that are going to change practice and new FDA approvals so they can change the care for their patients and so that should be something that any good oncologist is aware of but actually participating in a research study you know in advance the study is coming and maybe you're even involved in it as the participant versus the day that there's the FDA announcement of an approval you know people already expecting that and know that and know the study was complete and results were discussed so that's kind of late in the game that shouldn't be brand new shocking news to anybody when that announcement finally comes along that just opens the door that you can now prescribe it and insurance will pay for it so we're a couple minutes behind our target why don't we take ten minutes eleven oh five we'll come back and jump into the next two sessions before the lunch break


Hi, my name is Matt Lloyd-Jones and today I'll be talking to you about some ways of dealing with proportion data and meta-analysis. So what is proportion data? Well, proportion data is simply data that is presented as parts of a whole. So it could be proportions, percentages or prevalences, they're limited to 0 to 1 or 0 to 100%. And some of the research questions you might have relating to proportion data are demonstrated here. So my one was how does the proportion of resistant bacteria in the fecal microbiome differ between antibiotic-treated and untreated cattle? How does proportion data typically manifest in the scientific literature? Well, typically we don't have the raw data and we're limited by what studies present. Typically studies only present proportion data in their figures. Some studies won't even present that proportion data directly and they'll present figures of the numerator and denominator data from which we have to calculate proportions. And then alongside that a few studies after a long hard battle will provide raw data. And so we're left with these different levels of detail in terms of data that we have to combine into a meta-analysis. Okay, so with all that in mind, I'm going to be taking you through three problems that I came across when dealing with proportion data in my meta-analysis and the proposed solutions that I implemented in the hope that they can help you. I'm going to be highlighting the r packages and functions I used in blue on my slide. So keep a pen handy for writing those down if you're trying to do something similar. So perhaps the most obvious problem with proportion data is that they are restricted to a 0 to 1 or 0 to 100% range, which means they don't meet the assumptions of normality. So given that proportion data do not immediately meet the assumptions of normality, if we're going to use parametric tests for meta-analysis, then we need to do something to the data in order to deal with this. And one common way of dealing with this is to transform the data to get it into a format which more closely approximates a normal distribution. And there are many options for transformation, including log, logit, arcsign, and double arcsign transformations. And there's a lot of chatter about the relative merits of these different types. And it's often confusing to the meta-analysis which type is the best to use in their case. So which one did I use? Well, I used the arcsign transformation and I implemented this transformation using the transfer arcsign function of the metaphor package. So the arcsign transformation has benefits over the log or logit transformation in terms of dealing with sampling variances better, and also over the double arcsign transformation in terms of back transformation and interpretability. To be fair, the arcsign transformation has its own criticisms, so one of the criticisms is around its interpretability. So if you use this in a conventional modeling context, you can get predictions over or outside of the 0-1 range. But I argue that actually when you're using this in a meta-analysis context, what you actually do is you generate effect sizes first, which you then put into your models. And so it implicitly deals with this problem. And actually if you go back to some of Cohen's early work, he provides even guidance on how to transfer all the effect sizes back into approximate differences in proportions between your control and treatment groups. So I argue that that's less of an issue in meta-analysis. The other argument is that GLMMs, accounting for binomial distribution, are better at dealing with proportion data. But this in a meta-analytical context is perhaps less relevant because as I demonstrated earlier, you don't have the underlying numerator and denominator data. You just have proportions presented. So you can't even use these methods. And there are other issues with these methods in terms of dealing and model fitting with sparse data, which we often have problems with in meta-analysis anyway. So I think the arc's transformation is a good pragmatic choice in terms of dealing with proportion data. So problem two is even before you've got to the question of how to deal with your proportion data in modeling, you may not have your proportions directly presented in the paper that you're trying to incorporate into your meta-analysis. So while some studies will only report proportions, you'll come across other studies that don't report proportions at all. And they actually just report the numerator and denominator variables that would make up that proportion. And in these cases, almost always you've only got some measure of the mean and variance of those proportions rather than individual data points. And this makes calculating that a proportional mean and variance quite challenging. So how do you calculate the mean and variance of the proportion based on this data alone? Well, the only way of dealing with this problem that I can see is to simulate the underlying data based on those means and variances of the numerator and denominator that you do have, and then to divide them by each other in order to estimate the mean and variance of the proportion. And this is fairly easy to implement using base functions in R. You can plug in your means and standard deviations of your numerator and denominator variables and simulate vectors of simulated data. And then what you can do with those is you divide one by the other to calculate a simulated vector of proportions. And then from that, you can calculate a simulated mean and variance of a proportion. Of course, this is not ideal, but then most things in match analysis are not. And you're kind of bound to getting everything into this proportion format by the fact that many studies only report things in proportions, as I mentioned earlier. With this kind of thing, I'd recommend a sensitivity analysis based on removing the simulated data just to check that it's not having a disproportionate influence on your overall results. And the final problem that I want to highlight is the lack of interpretability of proportional differences in metro analysis. So by their very nature, proportions obscure what is happening in the underpinning numerator and denominator data. So the proportion of your numerator can change either because it's absolute value changes or because the proportion of the corresponding denominator changes. So, for example, the proportion of resistant bacteria in a population may increase because the resistant bacteria grow and increase in number. Or alternatively, the proportion may increase because the absolute value of the denominator decreases. And these obviously have very different implications in terms of interpreting what's going on in our data. And I actually think this is a bigger interpretability problem than some of those I mentioned earlier. And the way I propose to deal with it is to use absolute count data where it is available alongside your proportion data on which your main analysis is built.  But I think you should also alongside those plot and model the absolute counts where they are available. And this can give you a sense of whether what you're seeing is an actual increase in your numerator or associated with a change in the denominator. So for example, if we plot effect sizes based on the absolute number of resistant bacteria alongside those based on the proportions, we can see if the resistant bacteria are growing and increasing in number, or it's just the fact that your susceptible bacteria are being wiped out. And this can really aid the interpretation of your meta analysis, which can be very abstract as we know. So in summary, we often have to deal with outcomes reported as proportions, whether we like it or not. I proposed some potential pragmatic solutions for dealing with this data in the form in which we often encounter it when we're doing meta analysis. But of course, the real problem here is that people don't publish their data and are now allowing us to fully make use of it. And the real solution of course is for journals, universities and funders to enforce and or reward data sharing. So we can do more rich analysis. So finally, I'd like to thank the whole evidence synthesis team that was involved, not just in the meta analysis, but the wider systematic review project. In terms of the meta analysis, I'd like to thank Alfredo Sanchez Toha, who was my main meta analyst, who'll collaborate. I'd also like to thank Shinichi Nakagawa, who provided some useful email correspondence on the transformations part of this. And Dan Padfield, my colleague, who came across similar problems outside of meta analysis and sort of influenced my thinking on this a bit. And finally, here's a brief bibliography slide in case you want to follow up on any of the resources I presented. Thanks for listening.


Tales of the Texas Rangers starring Joel McRae as Ranger Jase Pearson. Another authentic re-enactment of a case transcribed in the files of the Texas Rangers. This is in the following story are fictitious for obvious reasons. The events themselves are a matter of record. Before we bring you today's Tales of the Texas Rangers, let's turn on our microphones down the hall in Studio A here at NBC's Hollywood Radio City, where rehearsal for the Phil Harris Alice Faye show is in progress. Yeah, now that's the way we'll do it on the show. It sounded great, fellas. Phil, would you like to talk to the listeners during this break and rehearsal? Yeah, Bill, I'd love to. Folks, I'd just like to take a few seconds here to remind you about part of the fine lineup of entertainment for the rest of the evening right here on NBC. Right after Tales of the Texas Rangers, listen to the big show with Tallulah Bankhead and all of her darling guest stars. I know you'll want to hear the music and comedy. The big show is lined up for you today. And then we come on to keep you entertained with our show, starring Alice Faye, Frankie Remly, Julius Abruzio, and some band leader, Phil, what's his name?  It's the Phil Harris Alice Faye show right after the big show today, and I hope you'll listen, folks. And now let's return to Tales of the Texas Rangers. And now, from the files of the Texas Rangers, the case called Dream Farm. It is 7.40 p.m. June 12, 1941. On a deserted stretch of highway through a thinly populated area of Texas, a sedan pushes to the southwest, towing behind it a small, heavily loaded two-wheeled trailer. In the front seat of the car, there are three people, a man, his wife, and their 12-year-old son. Don't seem to be much in the way of people out here. Why an open country, all right? I think we're gonna like it here, Edel. Oh, I hope so. Here's waiting to see you. While last month when I was out here to close the deal, I swear I just wanted to start plowing right off. I got a feeling this farm's gonna be lucky for us. Well, I just hope we can make a go of it, that's all. Now, Ethel, we've been all through that.  After all, we spent our lives in Iowa. Here we are, moving to a strange place where we don't know a soul. Well, we'll make friends soon enough.  Pa, I'm hungry. Well, that's one thing that ain't changed much from Iowa to Texas. We ought to be coming to a town soon, don't you think? Yeah, yeah, a town called Coronaville, not too far from here. We'll find a rest here pretty soon, Bobby. Just hold on a while longer. We're gonna keep driving all night, Pa. Well, I figure it might be best rather get the farm in the morning so as we can move in the daylight. Can I sleep on the back seat tonight? Sure you can. Hey, what's that? What? There's some fella signalling up again. Why, yes, there is someone. Now, what do you suppose? Looks like he's having car trouble.  Well, sure, why not? Will you look at that rear wheel? Hey, that must have been some blowout. You need some help? Yeah. John, I just as soon as you kept going. Now, Ethel, where's your Texas hospitality? Sure, it's all right, ma. How about a ride in the next gas station? Sure glad to take you. Get in the back. Never mind that. What? Get out. What you saying? You heard me. Get out of car, Holly. Hey, is that a real gun? Bobby, be quiet. Yeah, Bobby, be quiet. You won't get hurt. All right, I should go.  Well, we're getting out. Be careful with that thing. Yeah, yeah, I'll be real careful. What are you gonna do?  Me? I'm talking to no one else. Well, I don't get you, mister. What are you gonna do with us? Ain't you figured it out yet? Come on, lady, give me a purse.  Hurry up. John, do what he tells you. Well, I... Yeah, that's more like it. All right, now back away in the car. You're just leaving us out here? What do you think? You ain't going nowhere with my car. John, be quiet. I won't. Everything we got in the world's in there. Be quiet, John, please. Yeah, yeah, do what the lady tells you. I'll show you what I'll do. You can't get away with you. I'm taking our car with you. You should listen to me. I thought you should have listened.  No, please. The following morning, the three bodies were discovered by a state highway patrolman. The two adults were dead, but the boy, although unconscious, was still alive. He was rushed to the hospital in Coronaville and Sheriff King of Corona County was notified. The sheriff requested aid from the Texas Rangers. Ranger Jase Pearson was assigned. Yes, Sheriff. Oh, I don't mind telling you, I'm glad to see you. It's a bad one. Yeah, I heard. Why are they... Oh, come on, I'll show you. J.P. been out yet? Yeah, he ought to be along soon. Well, there they are, Jase. Not very pretty. No, never is. You've been over the area yet? Yeah, didn't find much. Went over the car for prints. Looks like there might be a couple of good ones there. Well, our lab crew will be out pretty soon. They'll check them. Hold your flash on the body, Sheriff. I want to have a look. How's that? Okay. Hmm. Powder burns on the clothing. He was shot from pretty close up. Yeah, same with the woman, Jase. The boy, too. You talk to him yet? The boy? Last I heard he was still unconscious. Is he gonna be all right? That's hard to tell you. Doc says he may come through okay. It's a tough break for the kid. These his folks? Yeah, I reckon they are. Aren't you sure? Not exactly. The hospital found this wallet in the boy's pocket, but these two had nothing on him. No papers, drivers, license, nothing. No money either, I suppose. Yeah, that's right. Let's see what you got from the kid. A library card from Clinton, Iowa, made out to Robert L. Wood. And here's a card from the Boy Scouts. True 47, Clinton, Iowa, made out to Robert L. Wood. I already notified the Clinton police, Jase. They're trying to find out if the boy was traveling with his folks. Hmm. What about this car, Sheriff? I noticed it's got Texas plates. Yeah. It's on the hot car last. Stolen a knife before last rindle. Killer could have taken their car when this one broke down. Rindville, you said. Mm-hmm. Up north. Figured the killer's heading south, Jase. Up to this point, he was. I think I'll go into town, Sheriff. The boy's conscious. I want to talk to him. Make the talk to him myself. I'll go along. On the way to the hospital, Austin radioed that the murder victims were probably the L. Wood's. The Clinton police had learned from a former neighbor that the family was moving to Texas. The Iowa Division of Motor Vehicle Registration supplied the make and license number of the L. Wood car and trailer. We relayed this information to all Texas law enforcement agencies. It was 3.40 a.m. when the sheriff and I arrived at the hospital. Robert L. Wood was out of his coma, but was still very weak. Robert, we want to ask you some questions. This is Sheriff King, and I'm Ranger Pearson. Texas Ranger. That's right. Tell me, son, do you remember what happened last night? Yeah. Man killed my pa. Where's Ma? I want to see her. Well, you can't right now, Robert. Why? I want to talk to her. Can you tell us what happened, son? He had a gun. He made pa take everything out of his pocket. He was going to take the car, and pa tried to stop him. Was it just one man? Uh-huh. Do you think you'd know him if you ever saw him again? I think so. Was he a tall man? Oh, wait. He thought he was as tall as pa. It'd be about 5.8, Jason. How about his hair, Robert? What color was it? He was dark.  Do you notice anything different about him? Any scars or anything like that? No. I don't remember anything. You remember what he was wearing? Uh-uh. Well, there's just one more thing, Robert. What about his voice? Was it high or low? I don't know. A guy in between. He was real. I reported Robert Elwood's description of the killer to headquarters and then turned in for some sleep. Two hours later, a phone call from Austin woke me up. The Elwood card had been found abandoned on highway 346 near Burton, Texas, about 100 miles away. Sheriff and I were there by 845. Patrolman Hartnett reported that when he'd found the card, about 7, it was out of gas. The trailer was missing. We started checking. I think I'll take a look through the glove compartment. When are you supposed he did with that trailer, Jason? Must have been slowing him down so he unhitched it. In fact, it'll turn up in the brush somewhere between here and Coronaville. Yeah, I reckon so. That patrolman said when he found the card, the motor was still warm. Yeah, killer must have left at around 6.30, maybe a little later. Yeah, and he's only a couple of hours ahead of us then. Hmm. Find something? Yeah. A bank book from the state bank in Clinton. The account was closed just four days ago on the 9th. $608.40. Hmm. Did he have it with him? I know he had it with him. The killer's probably got it. Look at this slip. It was stuck in the bank book. List of numbers. Serial numbers, record of traveler's checks. It's supposed to be filled out and kept in a safe place in case any of the checks are lost. He had 1050s. $500. Yeah, but you can see where he's checked off the top two numbers. Now he would probably cash those checks himself. And the killer's still got $400 worth. You don't think he'd take a chance and try to cash them? He might. $400.  But he'd have to sign Elwood's name when he cased him. Match the signatures already on the checks. Well, he might even need identification. He's got identification. Don't forget the killer took Elwood's wallet. As for the signatures, well, a lot of people can be fooled. Yeah. One thing's certain. If he's going to cash them at all, he'll try to do it in a hurry. He's not going to hang on to them any longer than he has to. Then you reckon he's already good rid of them? I don't think so. He hasn't had much of a chance. Why not? He could have cashed them anywhere between here and Coronaville. He'd have a hard time cashing $400 worth of checks in an all-night restaurant. Banks is best bet. Yeah, but what bank? There'll be 50 of them in this county, opening in five minutes. If he left here at about 6.30 and got into Burton around 7, he might just wait for the banks to open there. We better get to Burton and fast. There were two banks in Burton. At approximately 9.10, I dropped the sheriff at the Burton National and headed for the Burton Loan and Savings Bank a block away. Cashier there told me the checks hadn't come in, so I left instructions for him to contact me if any turned up, and I went back to the Burton National for the sheriff. Sheriff? Hey, Chase, come here. Find anything? I sure did. There was a mighty good hunch you had. He's gonna find him for me now. She says her puller came in at 9 o'clock as soon as the door opened. He had the checks all right, all $400 worth. Could she give you a description of the man? Description? She knows him. Follow named Al Walker. He says we can find him at the sales bar in a couple of blocks away. In just a moment, we will continue with Tales of the Texas Rangers starring Joel McCray as Ranger Jase Pearson. Every minute of every day, someone, somewhere calls on the Red Cross for help. Last July, the nation's most devastating floods since 1937 smashed through four Midwestern states. Property damage in Kansas and Missouri alone exceeded $1 billion. Tens of thousands were made homeless. When the floods came, the Red Cross was ready with rescue teams and first aid stations. For the homeless, the Red Cross set up shelters and feeding points. But the biggest job came when the waters receded, and began the rebuilding and repairing of homes, the rehabilitation of broken lives. The total cost of relief in this operation was almost $14 million. This was only one of the 300 domestic disasters in which the Red Cross gave aid last year. To answer the call when help is needed again this year, the Red Cross needs your support. Give and give generously to the 1952 Red Cross Fund Campaign. And now back to tonight's adventure with the Texas Rangers. We continue now with Tales of the Texas Rangers and our authentic story, Dream Farm. We found Al Walker at the sales barn a couple of blocks away. Sign over the entrance read Al Walker, proprietor. There was no loft and all the feed was neatly stacked at one end of the building. A small glassed-in office was at the other end. Walker was watering a couple of horses in the corral at the rear. Howdy, gents. Be right with you. All right. Blonde hair, Sheriff. He doesn't fit the description Robert Elwood gave us. Oh, but he had the checks. And he was in an oil-fired hurry to catch him. Might be best not to mention the killing, Sheriff. Well, that's what I was thinking. Now then, gents, you're Al Walker. It's me, all right. Can I help you? You can answer some questions. All right. This is Sheriff King. I'm Ranger Pearson. Well, right, please, to meet you. Come on in the office, gents. What kind of questions? You cashed some travelers' checks at the Burton National Bank a little while ago. Yeah, that's right. $400 worth. Something wrong? Where'd you get them? Oh, fellow brought them in this morning. He'd come in about 8 o'clock just so I was open enough. Have a seat, Ranger, Sheriff. No thanks. Did he say his name was John Elwood? Well, that's what he said. Can you describe the man, Mr. Walker? I reckon so. Big fellow? About your height, anyway. He's kind of heavy, too. What color was his hair? Oh, he had... Let me see now. He had light hair. Would you say it was as light as yours? Yeah. He'll come to think of it as it was. Uh-huh. What time did you say he came in, Mr. Walker? Just about 8. You always open that early? Oh, I generally open at 6. Sell a lot of feed to the farmers around here, and they do business pretty early. I was eating last night, though. I was out of town and stayed out late, so I kind of overslept this morning. What time do you leave here? Oh, it was 8.30 or so. I closed up about 20 minutes later, so I could go down to the bank and cash the checks. He was here about a half an hour, then. That's right. It'd take you that long to cash the checks for him? Uh-huh. Well, he bought something. He'd come in here to buy a horse, to keep a little stock, you know, was, uh, $150? You got a record of the sale, Mr. Walker? Well, yeah. No, no, as a matter of fact, I didn't have time to end it in my book. What about the rest of the checks? Well, after he paid me for the stuff he bought, he asked me to cash some other checks. I give him $250 in cash. You had that much cash at 8 o'clock in the morning? No, I always keep a few hundred dollars overnight, on account of opening up before the bank does. Mr. Walker, did he sign those checks in front of you? Well, yeah. Well, sure. He signed them in front of me. Uh-huh. Let me see the checks, Sheriff. Yeah. Here you are, J. See the two signatures on this check, Mr. Walker? Yeah. They don't match very well. They don't? What's wrong with them? I'll take a look. You see the difference here and here? Well, they look all right to me. I couldn't tell the difference. You mean it ain't... It ain't his right signature? The checks were stolen, Mr. Walker. This isn't John Elwood's signature at all. Stolen? How told you say that fellow was? Why? Oh, he was a big fella. How big? I don't know. He was six feet, maybe taller. You mean these checks are no good? I ain't going to lose my $400, am I? Wrecking your will unless we catch up to the fellow who's got it. What color hair did you say he had? It was light-colored, blonde. I didn't know they were stolen. You should have checked the signatures.  Oh, excuse me, Ranger. Hello, Walkers. What? Well, yeah. Yeah, he's here just a minute. It's for you, Ranger. Pearson speaking. What time did they come in? All right, we'll be right over. Thanks. Mr. Walker, we'll have to pick up our conversation a little later. You stick around. I'm sure I ain't going nowhere. Come on, Cheryl. What's up, Jason? He's a highway patrol. He's been identified a fingerprint from the car found at the scene of the killing. Yeah? Who's was it? Fellow named Sam Bradley got his mug shots at the patrol office. Bradley's description fit the one given us by Robert Elwood. A set of photographs had already been sent at the sheriff's office in Coronaville, and a deputy took them to Young Elwood at the hospital for positive identification. Short time later at the highway patrol office, I telephoned the boy. Yeah, Ranger, I got the picture. Do you recognize any of the men in the pictures? Yeah. Which one is it, Robert? Thanks, Robert. You've been a big help. What do you say? It's Bradley, all right. The boy picked his picture out a half a dozen the deputy brought up at the hospital. Well, that settles it then, but what about Walker? The description he gave us sure doesn't fit Bradley. In case you know he was lying. Yeah, but I can't figure out why. His only stake in this is $400 with the traveler's checks. He tried to cash them openly, so it's a sense he figured they wouldn't bounce. I don't think he knew they were stolen. Maybe not, Jayce, but he knew the man who gave him the checks wasn't John Elwood. Now, why'd he lie about that? Just as puzzled as you are. Come on. Well, where you going now, Jayce? Out to Walker's. I still want a written statement from him. You want to bring him back here? Uh-huh. Well, I reckon I'll mostly around town in the meantime. Maybe I can find someone to saw Bradley go into Walker's barn. Good idea. I'll meet you back here. I want to see if Walker's going to stick to his story. When I got to Walker's, the barn was closed up tight. I got his home address from a telephone book in a store nearby and walked back to the barn. At the time I got to my car, Walker was just driving up. Walker? Yeah? I thought I told you to stick around. Where you been? Well, no police ranger. I had to make the delivery. In your car? I didn't have much room there to haul feed. Oh, it was just a sack of oats, that's all. I want you to come down to the patrol office with me. What for? To get your statement about the fellow who gave you those checks. Well, what about the barn? I mean, you know if any customers come. They'll have to wait a while. You know where the highway patrol office is? Yeah. You can take your car. I'll follow you. At the station, Walker's story began to change slightly. His statement said that the man who cashed the checks was 8-10 inches tall. Earlier, he told us that the man was over 6 feet. It was 12 noon when the stenographer completed typing the statement and I took it into Walker to sign. Here's the statement, Mr. Walker. Are you sure you don't want to make any changes before you sign it? No. No, I've been telling you the truth, ranger. Uh-huh. Oh, one more thing. Before you sign it, I want to show you some pictures. Pictures? Yeah. Look at them carefully, Mr. Walker. Here are pictures of three men. Was one of these the man who cashed the checks? No. No, it wasn't any of these, fellas. How about this one? Could he be the man? No, no, no. The fellow who cashed the checks was an altogether different kind of man. This ain't him. Mr. Walker, this man's already been identified by one person as the man who killed John Elwood and his wife. What'd you say, ranger? Elwood was the man the checks belonged to. He was killed last night. Killed? First deal and now kill him. You didn't say nothing before about a murder? Two murders. This man, Bradley, killed two people and wounded a 12-year-old boy. He stole two cars that we know of. Well, I... I didn't know about all them things. Uh-huh. What about the picture? Is this the man who cashed the checks? No. No, that ain't him. I'm sure it ain't. All right, Mr. Walker, sign the statement. Walker was afraid. He couldn't miss it. But I didn't know what was bothering him or why. After he signed the statement, I let him go. A few minutes later, the sheriff came into the office. He had a newspaper in his hand. Jayce, is that Walker I just saw pulling away? Yes, Sheriff. He signed the statement, so I let him go. Well, we'd better get him right back again. Take a look at this newspaper. Burton Harold, what about it? But did Walker identify the picture of Bradley? Well, take a look at that item on mark. He'll tell you why he didn't. Mrs. Nancy Walker, wife of Al Walker, proprietor Walker Sales Barn, is in Fort Worth visiting her sister. Mrs. Walker is the former Nancy Bradley. Get it, Jayce? I checked around as soon as I got a load of this item, and it fits. Mrs. Walker has a brother named Sam Bradley. Walker's his brother-in-law. We raced out to Walker Sales Barn, but it was still closed, so we headed out toward his home in the farm section west of town. Half a mile from there, we spotted Walker's car turning into the driveway, and saw him rush into the house. We parked a short distance away and covered the rest of the ground on foot, approaching the house from the rear. Let's move up to that open window, Sheriff. Right, Jayce. Nothing in the house, do you? Sam, you fool, where you been? I've been looking all over for you. I took a bus over to Hazel, bought me a new suit. What's bothering you now? Well, I don't care, you can take the money, but you just got to get right out here as fast as you can. Now, wait a minute. What do you mean, spending your money? I thought you told me you got them checks from a friend of yours. Why, sure. What about it? You and your stories. It's just like I told you. You were playing cards last night, and the place was raided. I just thought I was afraid if he showed it to himself, he'd get caught. That's why I asked me to cast a check. I knew you wouldn't mind. Sam, don't you lie to me. You didn't have no friend. Use on them checks. They were stolen. I know all about it.  Then I find you stole the checks. Now, I find there's a couple of killings besides, and I'm mixed up in it. Now, you get out of here. Look, who you've been talking to? There's been a ranger out asking questions. That's who. Do you tell him anything? Not yet, but if I didn't have to lie to save my own hide, I'd have turned you in. Brother-in-law, I know Brother-in-law. I'll get in and tell him. I'll get out of here right away. I'll get out of here right now. I'm not getting myself home for you. All right, Bradley. Don't move. Throw your gun over here. Okay, James. Yeah, I'm okay, Sheriff. Save it, Walker. A jury will want to know why you didn't tell us where he was. Come on, get up, Bradley. You better have some of that $400 left for a good lawyer. You'll need one. In just a moment, we will tell you the results of the case you have just heard. This is George Hicks reporting. I'm now in New Hampshire for NBC. The names are Taft, Eisenhower, Truman, Kefauver, and Stassen. We'll bring you the reports soon on this first state presidential primary. This evening, NBC will present a broadcast of great interest to you in this election year. This is W.W. Chaplin inviting you to follow the campaign of the next president on NBC. Yes, from Concord, New Hampshire, the scene of the important New Hampshire primary election, NBC brings you surveys, reports, and comments by New Hampshire voters and party leaders. NBC is going to bring you full coverage of the New Hampshire primary, a primary which will not only decide the delegates to the Republican and Democratic national conventions, but also give a pretty good indication as to the strength of the leading presidential candidates. This is Leon Pearson inviting you to follow the campaign of the next president on NBC. Here are the New Hampshire primary special broadcast tonight on NBC. And now, back to the Texas Rangers. And now, here are the results of the case you have just heard. For harboring a fugitive from justice, Al Walker received a five-year suspended sentence. Sam Bradley was identified by Robert L. Wood as the man who shot and killed John and Ethel L. Wood. Ballistics confirmed that Bradley's gun was the murder weapon. He was convicted of murder in the first degree. And on August 4th, 1942, was electrocuted at Huntsville, Ben attention. Sweet Joel McCrae and another authentic re-enactment of the case from the files of the Texas Rangers. A Warner Brothers release. The part of Robert L. Wood was played by Richard Beals. Ethel and John L. Wood were Barbara Luddy and Tom Tully. Tony Barrett was Sam Bradley. And Barney Phillips was Al Walker. Ken Christie played the part of the sheriff. Technical advisor was Captain M. T. Lone Wolf Gonzalez of the Texas Rangers. This story was transcribed and adapted by Shelby Gordon. And the program was produced and directed by Stacey Keach. Hal Gibney speaking. Next, the big show brings you 90 minutes of drama, comedy and music on NBC.


The next is email segmentation. I particularly like this because I live in CRM systems right for work. So I think about data structure and custom information that's being collected by this organization that's different from this other organization. We are sending more and more emails all the time. What like 300 billion emails every day is the latest stat. Fortunately, they're not all in your inbox, but globally. So that's a lot of email that if we could translate that into mail that we get, like right now or somehow, maybe someone stole my identity, I get a lot of mail about Medicare. And I mean, you can judge my appearance. I'm not eligible for Medicare yet. I don't know how I got on that list. The junk mail that we get, if we think about that from a digital perspective, there's a lot of emails that are filling our inbox, even from organizations that we care about that we are not opening and we're not reading. And so that means it's time to really look at your email lists. One, always make sure that you're honoring often, that that's an actual, that's a law, a federal law that people need to opt in in order to see certain kinds of notifications from you. And then besides that, the way that you can further segment to then personalize your message. Why are you sending this message to this group of people? You know, maybe that message would be better suited to another group of people. And so the, I see the question, the only way that you can really act on this is to take a look at your data. How is your data structured? Can you put together folks that attended at events that gave you donations that have engaged in some sort of campaign, have signed up for special communications from you? Can you put all of those pieces of data together in one place? You have a CRM system that allows you to do reporting and filtering in order to actually see and this relatively homogenous groups put in your people together to then have target communications. I know that one of the organizations we work with the International Mountain Bicycling Association, their end of year campaign, every single year, they are segmenting more and more and more. And I think they ended up creating something like 12 or 13 different online donation forms at the end of last year for the end of year giving campaign that then they were sending that had slightly different language, a slightly different default donation value on the form that were quick to set up, you know, it's just sort of a copy of the same form over and over and then making tweaks to those forms and then having a lot of different emails that are going to a smaller group of people but instead of asking all donors for a base gift of $50, maybe this group of donors should be asked for a base gift of $250 and this other group of donors, a $5 recurring donation. So that's the benefit of segmenting and you can only do that if you look at your data structure. So there's a lot of work required and a lot of review required before you can take advantage of this, but you know, I mean, count at the end of the day, how many new deleted emails you have within your folder and that can be a motivation to take, take this one especially serious in terms of how you're interacting with your audience.


In the last two and a half years, I've had 65 people in my life die. Yeah, 65. And I keep getting asked to do videos about grief and loss, but I keep avoiding it. But today we're going to be talking about it. And hopefully I can provide you or someone you know, with some tips, suggestions, and tools so you can work through it. All right, so make sure that you stay tuned. What's up, everybody? This is Chris from the Rewired Soul, where we talk about the problem, but focus on the solution.  But most of all, grief is inevitable. Like sometimes we latch on to this idea or we just avoid the topic of death or you know, we think that maybe the people we know aren't going to die and maybe we'll never die. And we just don't even got to think about it. But this is an inevitable part of life.  It really does. And that's one of the reasons why we don't talk about it. Hey, it's one of the reasons why you guys keep asking me to make videos on it. And I never make videos on it, right? But anyways, like I mentioned in the beginning of this video, like I've dealt with 65 people in the last two and a half years dying around me. And I wanted to make this video to hopefully help you out. So please, please, please, if you get anything of value from this video, like please share it, share it on social media, because someone you know is dealing with this or they're going to deal with this, you know, we never know when it's going to happen. So please share it so maybe we can help some more people. But anyways, like I was talking to a buddy of mine, Dr. Alex, he's done some guest videos on my channel. He's a vet. He has a channel called our pets health. I will link to it in the description and in the info card. Go check it out and subscribe to your pet owner.  All right, but I don't like doing videos unless I'm well versed on therapeutic techniques and all these things to deal with it. And this is something I'm not well versed in with like, you know, scientific solutions.  And I guess I am, I guess I'll talk about it.  And I hope that this video can help you out.  I immediately entered a world where people were going to die around me. But I also work my day job at a drug and alcohol treatment center. So in this video, I'm going to be focusing on those deaths, but I will make some other videos for those of you out there who have lost friends and family members and things like that. I've dealt with that as well. One of my best friends passed away at 24 years old, my grandma, who I love more than anything she passed away a couple years ago. But I do want to talk about addiction and all the people I've lost to both overdoses and alcohol related deaths, as well as suicide. Like when I make these videos, I hope you guys enjoy them and watch them and try to learn more about topics that may not include your specific issues because I try to create some empathy.  The survival part of our brain is hijacked and tells us you need drugs and alcohol to have some sort of a decent life, right? But it destroys our life. So a lot of people after you take away the drugs and alcohol, some of them can't see far enough ahead into the future to realize that their life can get better. And unfortunately, sometimes they take their own life. You know what I mean? And I get that. Like if I'm being honest with you, my first month, two months of being clean and sober, I was very suicidal. I was like, how am I going to survive? Like I didn't want to do it. You know what I mean? So like I get it. And like I want to talk to you guys about some of the things that have greatly helped me avoid sitting in self pity, sitting in grief. You know, like I always say, we talk about the problem, but we focus on the solution. So the first thing I want to suggest to all of you, and it's something that was very hard for me, is like I have to be able to feel my feelings. I have to let my feelings run their course. This is one of the main reasons why I tell you all to go out there and just start meditating, even five or 10 minutes a day, because not so much the meditation practice, but understanding what meditation is about. Meditation is about non-judgmental awareness. So whether we're sad or angry or confused or whatever it is, like we just feel our feelings. If we don't feel our feelings, they manifest in other ways. Maybe it's isolation and I'm not being a friend to my friends. I'm not coming around. Maybe I'm sleeping on the couch all day when my son wants to play all these other things. Maybe I'm having violent outbursts or anger and things like that because I'm not feeling my feelings. Like it's okay to feel feelings. Like I'm a grown-ass man and like sometimes I don't want to feel sad, but sometimes like I just have to cry. And on the other hand too, I have to acknowledge that I'm not in control of this thing and my brain is going to feel what it wants, when it wants, and sometimes I just feel nothing and I can't judge myself for not feeling anything. Like some of these people who have died around me, I talked to them less than 24 hours before they passed away. I think about that for a second. I talked to them on the phone or through a text message or on Facebook or Twitter or something like that and within less than 24 hours, I find out that they're dead, you know? And sometimes it's just a shock to me and sometimes I don't react the way I think I should react and it's not crying and it's not feeling anything, but maybe later it just, it hits me, right? But meditation and mindfulness allows me to just acknowledge what's happening right now and not judge myself for it, okay?  The next suggestion I have for you is to cut yourself some slack. Like this is why I've made videos a lot, a lot of videos, about really focusing on the things that you can and cannot control, okay? Like I would not be able to do what I do. I wouldn't be able to work at a rehab. I wouldn't be able to make these YouTube videos and talk to you all in private messages and other people in my life who deal with depression or addiction or anything like that. If I had a false idea that I'm in control of the situation, I understand within the depths of my being that I cannot make anybody stay clean. I cannot make anybody stay sober. I cannot prevent anybody from committing suicide, but I hyper-focus on the things I can control because some of us can just look at that and say, oh, I can't control that, right? I just won't do anything about it. No, that's not what it's about. It's about hyper-focusing on what I can control. And that's why I go to work. I go to work every single day with a huge smile on my face and having a good time because I live an amazing life and that's why I make these videos and they're energetic and they're fun and I try to intertwine jokes and things like that because what I can control is let all of you know that five and a half years ago, I was trying to kill myself. I was suicidal. I was taking handfuls of pills every single night, hoping I wouldn't wake up in the morning, but for some reason I kept waking up. So I've been there. I've been suicidal. I've wanted to die, but now I live this incredible life. I hope that some of you out there are watching this or some of you who are in my groups that rehab and stuff. I hope that people see me and say, you know what? That guy used to be a hot mess.  What do I have to do to get that?  That's what's in my control. That's why I try to do all of these things with 100% passion. I have so many people who talk to me. They see what I'm doing on YouTube. They see what I'm doing on Instagram and Twitter and all these other things. They see how much I work. They see all the things I do with my son and my girlfriend, that Chris, how are you not burnt out because I am so passionate about maybe maybe giving one of you out there just a little bit of hope, just a little bit of hope that maybe your life can get better. That's how I never get burnt out. That's why I'm always telling you to share my videos, because maybe someone is just sitting there completely hopeless and they'll watch one of these things and say, you know what? If that guy can do it, so can I. These are the things that are in my control, all right?  Like things that might be in your control, calling your depressed friend once a day or texting them and saying, how are you doing? That is in your control. Like being there for people. If you walk past somebody at work who looks like they're down in the dumps, like go talk to them. Ask them how they're doing. See if there's anything you might be able to help with.  One of the things that drives me to keep helping more and more people is that I don't want to have any regrets. If somebody dies tomorrow or commits suicide in the next week, like I want to know that I did something. You know what I'm saying? Because if all these deaths have taught me anything, it's that life is precious and life is short.  So I want to make sure that I'm out there doing my best to help people in any way that I can. And the last suggestion I have for all of you is honor their memory. Honor their memory. And here's what I mean by that. Like for all the people I've lost, I honor their memory by living life.  And yes, that's okay. I know I was just saying, feel your feelings, but there's got to be a limit on it too. Like I feel, for me personally, it's disrespectful to their memory. Like so many people, so many people I've lost, we're talking about most of them were in their 20s, young, young people, right? Some of them in their 30s, some of them a bit older, but I try to live my life to the fullest every single day in honor of them, in honor of the opportunity that they weren't given. I'm a father to my son. I play with him. I have fun with him. I talk to him. I love when he calls me when he's over at his mom's house. We do things. I honor their memory by living life. I'm there with my girlfriend.  I try to live life because I realize that if I curl up in a ball and I shut down, I cannot help anybody. And that to me, that to me personally is disrespecting their memory. You know, something that kind of motivates me when I am down, when the grief is really hitting me. Like I imagine like what if they were here like I was like a ghost right now. I'm like, what would they tell me to do? Would they be looking at me and say, yeah, Chris, you know what? I think they used to lay there in a ball right there and just not leave your room for days. Like, no, they would want me to go out and take advantage of this opportunity that they didn't have. All right. But anyways, like I said, like please share this video, please share it because someone you know is dealing with this or they're going to deal with this. We never know what's going to happen. All right. But I also want to hear from all of you.  What have what has helped you with grief? What would you tell somebody who's lost somebody? Leave them down in the comments. So we have like a whole database of things that might be able to help other people. Okay. But anyways, if you liked this video, please give it a thumbs up. And if you're new here, I'm always making videos about mental health. Make sure you subscribe. Most of the videos are here to help you anxiety and depression and things like that, but this was an important topic. And you can click or tap right there if you want to check out some other videos. But thanks for watching and I'll see you next time.