andrew_gelman_stats andrew_gelman_stats-2014 andrew_gelman_stats-2014-2205 knowledge-graph by maker-knowledge-mining
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Introduction: Paul Alper writes: You recently posted my moving and widening the goalposts contention. In it, I mentioned “how diagnoses increase markedly while deaths are flatlined” indicating that we are being overdiagnosed and overtreated. Above are 5 frightening graphs which illustrate the phenomenon. Defenders of the system might (ludicrously) contend that it is precisely the aggressive medical care that is responsible for keeping the cancers under control. The prostate cancer graph is particularly interesting because it shows the peaking of the PSA-driven cause of treatment in the 1990s which then falls off as the evidence accumulates that the PSA was far from a perfect indicator. In contrast is the thyroid cancer which zooms skyward even as the death rate is absolutely (dead) flat. And of course here’s the famous cross-country comparison that some find “ schlocky ” but which I (and many others) find compelling :
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1 Paul Alper writes: You recently posted my moving and widening the goalposts contention. [sent-1, score-0.665]
2 In it, I mentioned “how diagnoses increase markedly while deaths are flatlined” indicating that we are being overdiagnosed and overtreated. [sent-2, score-0.853]
3 Above are 5 frightening graphs which illustrate the phenomenon. [sent-3, score-0.391]
4 Defenders of the system might (ludicrously) contend that it is precisely the aggressive medical care that is responsible for keeping the cancers under control. [sent-4, score-1.193]
5 The prostate cancer graph is particularly interesting because it shows the peaking of the PSA-driven cause of treatment in the 1990s which then falls off as the evidence accumulates that the PSA was far from a perfect indicator. [sent-5, score-1.446]
6 In contrast is the thyroid cancer which zooms skyward even as the death rate is absolutely (dead) flat. [sent-6, score-0.871]
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same-blog 1 1.0 2205 andrew gelman stats-2014-02-10-More on US health care overkill
Introduction: Paul Alper writes: You recently posted my moving and widening the goalposts contention. In it, I mentioned “how diagnoses increase markedly while deaths are flatlined” indicating that we are being overdiagnosed and overtreated. Above are 5 frightening graphs which illustrate the phenomenon. Defenders of the system might (ludicrously) contend that it is precisely the aggressive medical care that is responsible for keeping the cancers under control. The prostate cancer graph is particularly interesting because it shows the peaking of the PSA-driven cause of treatment in the 1990s which then falls off as the evidence accumulates that the PSA was far from a perfect indicator. In contrast is the thyroid cancer which zooms skyward even as the death rate is absolutely (dead) flat. And of course here’s the famous cross-country comparison that some find “ schlocky ” but which I (and many others) find compelling :
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Introduction: The (U.S.) “President’s Cancer Panel” has released its 2008-2009 annual report, which includes a cover letter that says “the true burden of environmentally induced cancer has been grossly underestimated.” The report itself discusses exposures to various types of industrial chemicals, some of which are known carcinogens, in some detail, but gives nearly no data or analysis to suggest that these exposures are contributing to significant numbers of cancers. In fact, there is pretty good evidence that they are not. The plot above shows age-adjusted cancer mortality for men, by cancer type, in the U.S. The plot below shows the same for women. In both cases, the cancers with the highest mortality rates are shown, but not all cancers (e.g. brain cancer is not shown). For what it’s worth, I’m not sure how trustworthy the rates are from the 1930s — it seems possible that reporting, autopsies, or both, were less careful during the Great Depression — so I suggest focusing on the r
3 0.18084496 2199 andrew gelman stats-2014-02-04-Widening the goalposts in medical trials
Introduction: Paul Alper writes: I do not believe your blog has ever dealt with the following phenomenon which might be called “(widening) moving the goalposts.” Drug companies and the medical world at large often create powerful drugs and procedures for people who are far (many standard deviations) from the norm (mean) and via randomized clinical trials, the relevant authorities approve. But there aren’t enough of those people to be truly profitable so the next step is to ask for approval to prescribe the same for people who aren’t that far (fewer standard deviations) from the norm. Or, just move the norm (center) so as to pick up a much larger number of patients. Afflictions include hypertension, cholesterol, overweight, osteoporosis. The result is what is often called “the worried well,” who receive little or no benefit but suffer harms from the treatment. H. Gilbert Welch has written extensively on this “goalpost” issue. He is the author of http://www.amazon.com/Overdiagnosed-Ma
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Introduction: Aggressive, fizzing nonconformity .
Introduction: Paul Alper writes: You recently posted on graphs and how to convey information. I don’t believe you have ever posted anything on this dynamite randomized clinical trial of 90,000 (!!) 40-59 year-old women over a 25-year period (also !!). The graphs below are figures 2, 3 and 4 respectively, of http://www.bmj.com/content/348/bmj.g366 The control was physical exam only and the treatment was physical exam plus mammography. The graph clearly shows that mammography adds virtually nothing to survival and if anything, decreases survival (and increases cost and provides unnecessary treatment). Note the superfluousness of the p-values. There is an accompanying editorial in the BMJ http://www.bmj.com/content/348/bmj.g1403 which refers to “vested interests” which can override any statistics, no matter how striking: We agree with Miller and colleagues that “the rationale for screening by mammography be urgently reassessed by policy makers.” As time goes
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Introduction: Paul Alper writes: You recently posted my moving and widening the goalposts contention. In it, I mentioned “how diagnoses increase markedly while deaths are flatlined” indicating that we are being overdiagnosed and overtreated. Above are 5 frightening graphs which illustrate the phenomenon. Defenders of the system might (ludicrously) contend that it is precisely the aggressive medical care that is responsible for keeping the cancers under control. The prostate cancer graph is particularly interesting because it shows the peaking of the PSA-driven cause of treatment in the 1990s which then falls off as the evidence accumulates that the PSA was far from a perfect indicator. In contrast is the thyroid cancer which zooms skyward even as the death rate is absolutely (dead) flat. And of course here’s the famous cross-country comparison that some find “ schlocky ” but which I (and many others) find compelling :
Introduction: Paul Alper writes: You recently posted on graphs and how to convey information. I don’t believe you have ever posted anything on this dynamite randomized clinical trial of 90,000 (!!) 40-59 year-old women over a 25-year period (also !!). The graphs below are figures 2, 3 and 4 respectively, of http://www.bmj.com/content/348/bmj.g366 The control was physical exam only and the treatment was physical exam plus mammography. The graph clearly shows that mammography adds virtually nothing to survival and if anything, decreases survival (and increases cost and provides unnecessary treatment). Note the superfluousness of the p-values. There is an accompanying editorial in the BMJ http://www.bmj.com/content/348/bmj.g1403 which refers to “vested interests” which can override any statistics, no matter how striking: We agree with Miller and colleagues that “the rationale for screening by mammography be urgently reassessed by policy makers.” As time goes
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Introduction: The (U.S.) “President’s Cancer Panel” has released its 2008-2009 annual report, which includes a cover letter that says “the true burden of environmentally induced cancer has been grossly underestimated.” The report itself discusses exposures to various types of industrial chemicals, some of which are known carcinogens, in some detail, but gives nearly no data or analysis to suggest that these exposures are contributing to significant numbers of cancers. In fact, there is pretty good evidence that they are not. The plot above shows age-adjusted cancer mortality for men, by cancer type, in the U.S. The plot below shows the same for women. In both cases, the cancers with the highest mortality rates are shown, but not all cancers (e.g. brain cancer is not shown). For what it’s worth, I’m not sure how trustworthy the rates are from the 1930s — it seems possible that reporting, autopsies, or both, were less careful during the Great Depression — so I suggest focusing on the r
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Introduction: The Organisation for Economic Co-operation and Development reports that the following project from Krisztina Szucs and Mate Cziner has won their visualization challenge, “launched in September 2012 to solicit visualisations based on the OECD’s data-rich Education at a Glance report”: (The graph is interactive. Click on the above image and click again to see the full version.) From the press release: Entries from around the world focused on data related to the economic costs and return on investment in education . . . [The winning entry] takes a detailed look at public vs. private and men vs. women for selected countries . . . The judges were particularly impressed by the angled slope format of the visualisation, which encourages comparison between the upper-secondary and tertiary benefits of education. Szucs and Cziner were also lauded for their striking visual design, which draws users into exploring their piece [emphasis added]. I used boldface to highlight a p
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Introduction: Paul Alper writes: You recently posted my moving and widening the goalposts contention. In it, I mentioned “how diagnoses increase markedly while deaths are flatlined” indicating that we are being overdiagnosed and overtreated. Above are 5 frightening graphs which illustrate the phenomenon. Defenders of the system might (ludicrously) contend that it is precisely the aggressive medical care that is responsible for keeping the cancers under control. The prostate cancer graph is particularly interesting because it shows the peaking of the PSA-driven cause of treatment in the 1990s which then falls off as the evidence accumulates that the PSA was far from a perfect indicator. In contrast is the thyroid cancer which zooms skyward even as the death rate is absolutely (dead) flat. And of course here’s the famous cross-country comparison that some find “ schlocky ” but which I (and many others) find compelling :
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Introduction: Cassie Murdoch reports : A 47-year-old woman in Uxbridge, Massachusetts, got behind the wheel of her car after having a bit too much to drink, but instead of wreaking havoc on the road, she ended up lodged in a sand trap at a local golf course. Why? Because her GPS made her do it—obviously! She said the GPS told her to turn left, and she did, right into a cornfield. That didn’t faze her, and she just kept on going until she ended up on the golf course and got stuck in the sand. There were people on the course at the time, but thankfully nobody was injured. Police found a cup full of alcohol in her car and arrested her for driving drunk. Here’s the punchline: This is the fourth time she’s been arrested for a DUI. Assuming this story is accurate, I guess they don’t have one of those “three strikes” laws in Massachusetts? Personally, I’m a lot more afraid of a dangerous driver than of some drug dealer. I’d think a simple cost-benefit calculation would recommend taking away
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Introduction: John Cook writes : When I hear someone say “personalized medicine” I want to ask “as opposed to what?” All medicine is personalized. If you are in an emergency room with a broken leg and the person next to you is lapsing into a diabetic coma, the two of you will be treated differently. The aim of personalized medicine is to increase the degree of personalization, not to introduce personalization. . . . This to me is a statistical way of thinking, to change an “Is it or isn’t it?” question into a “How much?” question. This distinction arises in many settings but particularly in discussions of causal inference, for example here and here , where I use the “statistical thinking” approach of imagining everything as being on some continuous scale, in contrast to computer scientist Elias Bareinboim and psychology researcher Steven Sloman, both of whom prefer what might be called the “civilian” or “common sense” idea that effects are either real or not, or that certain data can
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