Alzheimer's and Amyloid 4: The Long Mistake

Alzheimer's and Amyloid 4: The Long Mistake

Over the first three parts in this series we followed the rise and fall of the Amyloid Hypothesis. The plaques failed. The idea of toxic precursors failed. The most influential oligomer paper in the field was ultimately retracted. By any ordinary standard of scientific reasoning, this should have marked the end of amyloid as a central explanation for Alzheimer’s Disease. Instead, something remarkable happened: As the scientific case for amyloid weakened, the clinical investment in amyloid accelerated. Drug companies continued developing anti-amyloid therapies. Regulators continued evaluating them. Researchers continued measuring amyloid. Billions of dollars flowed into a treatment strategy increasingly disconnected from the evidence. The result was the modern anti-amyloid drugs. What follows is two short essays I wrote about the clinical trials that won FDA approval for two of them. In both cases drug makers quite literally designed the trials to prove that the drugs DON’T help people with Alzheimer’s, apparently with full confidence that they could spin the results to suggest the opposite. It is among the most brazen examples of FDA game theory, and snake oil sales, that I can recall in decades of reviewing FDA trials. New Alzheimer’s Drugs Are Bringing Back the Wrong Memories Apr 03, 2024 I remember when, in 1999, the FDA approved Vioxx, a pain reliever that went on to kill an estimated 50,000 Americans. According to whistleblowers [https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020209] the FDA not only had the data to prevent the tragedy, they obstructed the investigation. I also remember the inspiring story of Frances Kelsea, an FDA physician who in 1960 refused to approve thalidomide despite approval in dozens of other countries, and industry pressure. The drug caused over 10,000 birth defects worldwide, but just 17 in the US where it was never approved. Now, in 2024, the FDA is on the verge of approving [https://www.nytimes.com/2024/03/08/health/alzheimers-drug-donanemab.html] a third Alzheimer’s Disease drug. The first was Aduhelm in 2021, the second was Leqembi, in 2023. Donanemab, the third, is under review. The three are extremely similar. They’re all monoclonal antibodies, they all reduce amyloid plaques in the brain, and they all don’t work. In the 1980s researchers discovered amyloid plaques were associated with Alzheimer’s, spawning the ‘amyloid hypothesis’. If the plaques cause cognitive decline, it was hoped, removing them may slow or even reverse Alzheimer’s. Unfortunately, the theory has been dashed. First, studies show [https://jamanetwork.com/journals/jamaneurology/fullarticle/2427382] many with Alzheimer’s have no brain amyloid [https://www.alzforum.org/news/research-news/when-theres-no-amyloid-its-not-alzheimers]. Second, scientific reviews [https://www.sciencedirect.com/science/article/pii/S1568163721002439] show at least 72 anti-amyloid agents have been researched, and none have worked. This includes nine monoclonal antibodies, a class that has failed so miserably and consistently a 2021 meta-analysis announced [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8251763/] “the time has come to divert therapeutic efforts away from AAB [amyloid] immunotherapy.” Abject failure is certainly the case for Aduhelm [https://www.aafp.org/pubs/afp/issues/2022/0400/p353.html#afp20220400p353-b1]. Two FDA studies were halted early for futility [https://link.springer.com/article/10.14283/jpad.2022.30], and an expert panel voted 9-1 against approval (the FDA approved it anyway). Meanwhile, Leqembi ‘slowed cognitive decline’ [https://www.nejm.org/doi/full/10.1056/NEJMoa2212948] by just 0.45 points on an 18-point scale, less than half the 1-point minimum deemed meaningful [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3034393/]. Finally, the donanemab trial [https://jamanetwork.com/journals/jama/fullarticle/2807533#note-JOI230087-1] used a 144-point scale and reported a 3-point edge, well below the 9-point minimum determined by the company’s own research [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169866/]. These failures highlight a crucial distinction: statistical versus clinical differences. Studies often find a ‘statistical’—meaning mathematically identifiable—difference between groups. But research is a human task and thus inherently biased, so trial results commonly lean toward the drug. Particularly in large trials (the Alzheimer’s trials enrolled thousands) this often leads to a ‘statistical’ difference. But a clinical difference affects people’s lives. Which is why there are thousands of studies examining and meticulously defining the ‘minimal clinically important difference [https://pubmed.ncbi.nlm.nih.gov/?term=minimal+clinical+difference]’ for scales like those in the Alzheimer’s trials. Those studies tell us the ‘differences’ in the antibody drug trials were so small that people with the disease, their families, and their doctors, would literally never notice them. In other words, they’re not real differences. Another issue may also be confusing starry-eyed loyalists. The drugs removed amyloid plaques quite effectively—a finding that closes the door on the amyloid hypothesis. Vanquishing amyloid plaques didn’t help people with Alzheimer’s. The chicanery of parading differences well below the thresholds for true benefit is happening now for a reason: We’re heading into a perfect storm of potential profit for AD drugs. Nearly 7 million in the US have symptomatic Alzheimer’s, with an expected doubling by 2050. This will likely balloon with the use of new, flawed blood tests that severely over-diagnose Alzheimer’s [https://www.nytimes.com/2024/03/04/health/alzheimers-amyloid-diagnosis.html]. And the drug, given through IV infusions, costs nearly $30K per year (not including infusion costs, facility fees, and other charges). A final tidbit: The drugs cause brain swelling, headaches, confusion, and occasionally death—in huge numbers. Donanemab, the latest, caused 24% of people’s brains to swell, while another 9% suffered infusion reactions. That’s 1 in 3 people seriously harmed by the drug, and zero helped. What’s worse, as noted in these pages [https://researchtranslation.substack.com/p/it-just-doesnt-matter-so-it-matters], one can always expect the harms to be greater and the benefits smaller than reported in trials. As the FDA wrestles with the amyloid drugs, it seems natural to remember the agency’s heroic performance on harmful drugs of the past. But an effective Alzheimer’s treatment would bring back different memories. Why the Alzheimer’s Drugs Won’t Make Your Burger Better Feb 04, 2025 I like a burger. With cheese. And lettuce and tomato and maybe onion and ketchup or sauce (house choice). I prefer it rare. Really rare. Like, true blue. This last part is the downfall of many a burger joint where, fearing liability, kitchens won’t make a rare burger. To me, besides corrupting its taste, this means dubious beef. Sushi, steak tartare, and raw bar items are much riskier than anything cooked, but they’re still common menu items. A kitchen that won’t make a rare burger doesn’t trust its sourcing and prep for burger meat. Sad! But crucially, rare burgers aren’t just hard to find, they’re also tricky to make because they must—MUST—be seared on the outside and lightly cooked on the inside. This delicate contrast, a pillowy but juicy inside with a firm outer layer, is the mouth-watering soul of a great burger. So for home burgering, I got a meat thermometer. To my surprise, the first time I used it the reading was 122.68°. Impressive precision! But this number was, as the kids say, TMI (not to mention sus). Because while my gifted palate is a wonder of epicurean virtuosity, I cannot tell a 1° difference in temperature, much less 0.01°. Those decimal points are not helping me. I can tell rare from medium-rare (I think). That’s about 10° different. Which means somewhere between 1° and 10°, for me, the difference becomes perceivable and thus potentially meaningful. If I was bored and curious I might experiment to find the threshold, and in research parlance we would call it the ‘clinically significant’ difference. This principle, also known as the minimal clinically important difference [https://pmc.ncbi.nlm.nih.gov/articles/PMC7366277/] (or ‘MCID’), defines the smallest improvement patients and doctors are able to perceive, a starting point for judging whether treatments provide a meaningful benefit. Curiously, however, all three FDA-approved Alzheimer’s drugs were tested in studies that are the equivalent of a 2-decimal point thermometer. Each trial enrolled way more people than needed to find improvements in dementia. Why? Because the more participants, the smaller a difference a study can find. But my thermometer, for instance, can detect differences that are much too tiny to matter. And so can studies. In research this is called over-powering, but in trials it’s very unusual. After all, genuinely helpful drug effects, even lowly MCIDs, aren’t tiny. So why would researchers go looking for tiny differences? Who even has the money and resources to enroll way too many people in a randomized trial?? Oh. Wait. As discussed in these pages before [https://researchtranslation.substack.com/p/new-alzheimers-drugs-are-bringing], a jarring attribute of the Alzheimer’s drugs is that trials proved they do not make a perceivable difference. One hapless employee at Eli Lilly even spent years studying (and writing at least seven reports [https://pubmed.ncbi.nlm.nih.gov/?term=%22Wessels%20AM%22%5BAuthor%5D]) to establish the MCID for cognitive impairment. He found it was at least 5 points on a 144-point scale for mild disease and 9 points for early Alzheimer’s. But his company’s drug Kisunla produced [https://jamanetwork.com/journals/jama/fullarticle/2807533] scores within 3 points of a placebo—in other words, indistinguishable from placebo. Meanwhile Biogen and Eisai’s drug Leqembi was within [https://www.nejm.org/doi/full/10.1056/NEJMoa2212948] 0.45 points of placebo on an 18-point scale—also less than half the established MCID [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3034393/] of 1 point. How could this happen? Were the studies purposefully over-powered? Or did they stumble upon tiny differences while seeking meaningful ones? In the Kisunla report [https://jamanetwork.com/journals/jama/fullarticle/2807533] Eli Lilly says they aimed to find a 3-point difference (!!!). The authors calculated that 1,000 participants would give them a 95% chance, or ‘power’, to find it. So they enrolled 1,000 people. Then they enrolled 736 more. What about Leqembi? The FDA approval trial [https://www.nejm.org/doi/full/10.1056/NEJMoa2212948] also, amazingly, targeted 0.4 points better than placebo (!!!). This, they found, required 1,566 participants—and they enrolled nearly 1,800. This is over-over-powering. The original plans were over-powered, and then each study ADDED extra enrollments. These are confessions, hidden in plain sight in the methods sections of the papers, and they mean the companies knew before the trials started that their drugs don’t help. So they targeted statistical—not perceivable—differences, then convinced the FDA to approve the drugs.1 [https://researchtranslation.substack.com/p/why-the-alzheimers-drugs-wont-make#footnote-1] Bonus question: How could the companies feel confident the studies would generate a statistical advantage for their drug? Answer: The double-dog placebo [https://researchtranslation.substack.com/p/antidepressants-tamiflu-and-the-double]. In their brilliant, deeply researched investigation [https://www.levernews.com/the-deadly-secrets-behind-breakthrough-alzheimers-drugs/] Jeanne Lenzer and Shannon Brownlee describe a woman who was convinced, and whose friend was convinced, Leqembi was rapidly improving her memory. But she was receiving a placebo. As placebo researcher Irving Hirsch explains in his wonderful book [https://www.amazon.com/Emperors-New-Drugs-Exploding-Antidepressant/dp/0465022006], placebo effects are common, but they’re reliably larger when people experience drug side effects. Side effects effectively unblind study participants, letting them know they’re on a real drug and amplifying their expectations, excitement, and thus placebo effects. One of the great ironies of modern scientific rigor, therefore, is that ineffective drugs in double-blinded trials can generate statistical advantages if they have harmful side effects. People given Leqembi in trials had infusion reactions 19% more often than those given placebos, and brain swelling 11% more often. That’s a lot of unblinding, easily enough double-dog placebo to virtually guarantee an advantage.2 [https://researchtranslation.substack.com/p/why-the-alzheimers-drugs-wont-make#footnote-2] My burger thermometer gives me too much information, and so did the trials for the new Alzheimer’s drugs. Deliberately over-powered trials are a smoking gun, telling us what the companies knew all along: Their drugs don’t work. The story of the anti-amyloid drugs is often presented as a story of disappointing results. Placed within the chronology of amyloid research they are better described as a story of entirely predictable results. By the time these drugs entered clinical trials, the Amyloid Hypothesis was decimated. Plaques did not track with disease. Dementia could appear before plaques. Removing plaques did not stop dementia. The proposed replacement—the Amyloid Precursor Hypothesis—fared no better, collapsing under a combination of failed replication, failed trials, and outright fraud. The drug trials therefore did not rescue the theory. They confirmed its failure. This is why the central mystery of the Alzheimer’s story is not scientific, it is etiologic: How did this happen and why? If the plaques failed, why did amyloid remain the target? When the precursors failed, how could amyloid still be of interest? If removing amyloid then failed to help patients, why are we still chasing it? The answer lies in one of the most successful acts of disease redefinition in modern medicine. Next time we’ll examine the blood tests, PET scans, and diagnostic criteria that transformed amyloid from a failed explanation into the disease itself. Get full access to Research Translation at researchtranslation.substack.com/subscribe [https://researchtranslation.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]

Alzheimer's and Amyloid 3: The Mistake of the Invisible Friend

Neuroscientists are not famous for being dumb. So when the following timeline unfolded, they should have understood exactly what it meant: First, autopsy studies in 1991 [https://onlinelibrary.wiley.com/doi/abs/10.1002/ana.410300410] and 1992 [https://www.neurology.org/doi/10.1212/wnl.42.3.631] found that amyloid plaques—supposedly the cause of Alzheimer’s, as the centerpiece of the Amyloid Hypothesis—did not scale with the disease. Then, in 2001 [https://www.jneurosci.org/content/21/2/372] and 2002 [https://www.jneurosci.org/content/22/5/1858], researchers published data showing that an Alzheimer’s mouse model developed dementia—before ever developing plaques. Finally, in 2004 [https://www.neurology.org/doi/10.1212/01.WNL.0000159740.16984.3C] a vaccine successfully removed plaques from the brains of Alzheimer’s patients—yet their dementia continued to spiral, unabated. RT is fully reader-supported. For the price of a cup of coffee once a month from you, I can continue RT—please become a paid subscriber. It is hard to imagine a more obvious demise for the Amyloid Hypothesis. Some researchers, however, particularly those with funding and livelihoods tied to it, concentrated on the possibility that amyloid precursors might still be involved. If true, such a finding could preserve a role for amyloid researchers and their laboratories. But most precursors, detailed above, were well known, well studied, and stubbornly non-toxic. They could not explain the Alzheimer’s hallmarks of damaged tissue, lost synapses, and tangled detritus. Except, perhaps, for one, which remained a mystery. ‘Soluble oligomers’, theoretically the building blocks of fibrils, are exceedingly difficult to isolate because they are transient, tiny, and live in a dissolved state. Few labs had ever found them, much less studied their effects. Which is why it was blockbuster news in 2006 when Sylvain Lesné, at the University of Minnesota lab, pulled off a miracle with the potential to energize (read: fund) amyloid theorists everywhere. Despite the world’s prior work yielding—at best—messy, shaky evidence of oligomers, Lesné reported a clean, concrete, and copious yield of a new oligomer named beta-amyloid-*56, or ‘star-56’. Based on gel photos in Lesné’s paper [https://www.nature.com/articles/nature04533] the oligomer was clearly detectable in a mouse’s brain just days before the onset of dementia. Based entirely on this 2006 paper (since no other lab has ever reproduced the star-56 finding), for 16 years the star shone bright, offering an exciting new offshoot: The Amyloid Precursor Hypothesis. Then, barely in its adolescence, the new star flickered—and died. Matthew Schrag, an MD/PhD neuroscientist at Vanderbilt University, was hired by investors who suspected that an anti-amyloid drug maker’s claims were exaggerated. Schrag dug deep into the Amyloid Hypothesis and its derivatives, and came to Lesné’s study. In 2022, on a geeky post-publication review site called PubPeer [https://pubpeer.com/publications/8FF7E6996524B73ACB4A9EF5C0AACF], Schrag posted the following images and coolly accused the report of being a fraud. Soon, other super-sleuths jumped in. By the end, multiple forensic investigators and leading researchers flagged over 70 images from Lesné papers as likely to have been tampered with. For those interested in a full anatomy of the fraud, you can find it in Science [https://www.science.org/content/article/potential-fabrication-research-images-threatens-key-theory-alzheimers-disease], where the story [https://www.science.org/content/article/potential-fabrication-research-images-threatens-key-theory-alzheimers-disease] broke. On PubPeer you can also read the often cringe-worthy, years-long dialogue [https://pubpeer.com/publications/8FF7E6996524B73ACB4A9EF5C0AACF] between the researchers, Schrag, and others. In 2024 the paper was retracted after the Minnesota group (sans Lesné) finally conceded it had to be. Then, in a real head-scratcher, the senior author Dr. Ashe published a new paper [https://www.cell.com/iscience/fulltext/S2589-0042(24)00460-7?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2589004224004607%3Fshowall%3Dtrue] purporting to show that the original claims were all correct. The whole saga, she seemed to suggest, was just a silly misunderstanding. Who cares if you can’t see our friend Snuffleupagus—we can! The response from the research community was a collective eye roll. Dr. Schrag, for one, wasn’t having it. When Ashe touted their new paper in the PubPeer string [https://pubpeer.com/publications/8FF7E6996524B73ACB4A9EF5C0AACF], Schrag eviscerated each and every claim, concluding that the new version “objectively falls short of reproducing the earlier result.” Awkward. In any case, with the Amyloid Hypothesis dead, the crucial question was whether the Amyloid Precursor Hypothesis was viable, and the best answer is this: It’s been two decades, and no other research group has been able to even confirm the existence of star-56, much less replicate its effects. The few other oligomers that have been isolated suffer the same problem. The cherry on this debunking pie is the story of the BACE and GSI drugs, which inhibit the ‘secretase’ enzymes and therefore reduce virtually every precursor: monomers, oligomers, fibrils, and plaques. In clinical trials comparing them to a placebo, neither [https://www.nejm.org/doi/full/10.1056/NEJMoa1210951] drug class improved dementia—they both worsened [https://www.nejm.org/doi/full/10.1056/NEJMoa1812840] it. So, um, no. The Amyloid Precursor Hypothesis is no more viable than its fallen father. Next week, we’ll examine the unblushing audacity of anti-amyloid drug makers, who continue to make it clear that for them, amyloid IS the disease. Get full access to Research Translation at researchtranslation.substack.com/subscribe [https://researchtranslation.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]

Alzheimer’s and Amyloid 2: Mistakes Of Mice and Men

Last week [https://researchtranslation.substack.com/p/alzheimers-and-amyloid-part-1-the] we reviewed two seminal studies from the 1990s, both showing mathematically that amyloid plaques are, at best, an inconsistent bystander in Alzheimer’s Disease. Plainly, they are not the driving cause. Hardcore believers may have ignored or rationalized the findings from these small but pivotal autopsy studies. A decade later however, there would be no refuge and no rescue when two trials shook the neurology community, forcing even the most avid and invested supporters to abandon ship. Of Mice To test dementia treatments, researchers needed test subjects. In the early ‘90s geneticists made a game-changing discovery [https://www.nature.com/articles/349704a0]: A tiny fraction of people (roughly 1%) possess a rare genetic mutation directly linked to amyloid processing. Star-crossed and dementia-bound, those who carry the mutation typically develop early-onset Alzheimer’s and massive amounts of amyloid plaque. In 1996, researchers at the University of Minnesota famously [https://www.science.org/doi/10.1126/science.274.5284.99] spliced these defective genes into a mouse, creating the Tg2576 animal model—a transgenic mouse with early cognitive decline and heavy accumulations of amyloid. Recognizing the goldmine this could represent to a pharmaceutical industry that had for years been stalking amyloid researchers for an animal model, the Minnesota group patented their technique. Each time it was used in labs around the world, they would reap rewards. Equipped with an Alzheimer’s model for lab testing, the establishment, and drug companies everywhere, smelled victory: They finally had dementia in a cage. But when they tested the mice in memory mazes, there was a problem. A big one. From a 2004 paper [https://www.jneurosci.org/content/24/15/3801] by the Minnesota researchers, conceding the timeline for pathological developments in their mouse model: “…memory deficits appear at 6 months, whereas amyloid plaques first appear at 8 months.” Here it is in the original paper (‘Swedish mutation’ is shorthand for their transgenic mice): In other words, the mice had dementia before they ever had plaques. To state the obvious, a cause cannot arrive after its effect. Of Men Despite complete biological failure, first in autopsy studies and then in the only validated animal model, the pharmaceutical industry pushed forward into human trials of treating amyloid plaques. In 1999, Elan Pharmaceuticals launched a clinical trial injecting 300 Alzheimer’s patients with synthetic amyloid to provoke their immune systems, and allow their own antibodies to scrub the plaques from their brains. It worked. In what can only be considered an ingenious feat of bio-engineering, amyloid was successfully vanquished from the brains of the vaccinated. There were, however, two issues—and they were doozies. First, the trial was halted [https://www.neurology.org/doi/10.1212/01.WNL.0000159740.16984.3C] abruptly when 6% of people developed life-threatening brain swelling. But second—the true nightmare for amyloid believers—came in the form of autopsy reports [https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(08)61075-2/fulltext] from trial subjects. Under the microscope it was clear the vaccine had scrubbed massive patches of the brain clean of amyloid. Yet people with clean brains had progressed to profound dementia, dying of Alzheimer’s. From the autopsy study: In other words, getting rid of amyloid failed to achieve its only mission: helping people with Alzheimer’s. Instead, it inflamed and endangered their brains. Of the Invisible At this point, the Amyloid Hypothesis was dead. Observational data showed plaques didn’t correlate with dementia. Animal models proved the plaques came too late to be a cause. And a human vaccine proved that clearing them was both dangerous, and fruitless. By every standard of scientific reasoning the hypothesis was debunked. But billions of dollars in pharmaceutical development and countless careers were chained to it. The establishment needed a loophole. And who better to provide it than the researchers who crafted the mouse model, patented its use, and continued to work feverishly on amyloid. The Minnesota researchers were believers, and they found a pivot: Perhaps, they decided, plaques were not the cause, but the fallout—ashes of a fire that devastated the synapses. The real flame, they now proposed, was not the mature plaque but ‘soluble oligomers’, early-stage toxic clumps of amyloid that lived invisibly in the brain’s cellular fluid. The Minnesota group tweaked their failed theory and presented the new version publicly—before telling the world they had disproved the old one. Before anyone knew what was happening the Amyloid Hypothesis had died, and come back as a ghost. Like a ghost, the new version was invisible— including to the people who proposed it. Until someone could directly or indirectly visualize them, soluble oligomers were little more than an idea, making them impossible to disprove. But that knife cut both ways. With the original theory debunked, a mutated vestige was all that remained. Hanging by a thread, the Amyloid Hypothesis was speeding toward the waste bin of scientific history. To save it, the establishment would need indisputable proof of one thing: Toxic pre-plaque clumps, floating in the brains of mice, perfectly timed to the onset of dementia. Guess what they found. Next week, you’ll see how a doctored photo became the most disastrous scientific fraud of the century. 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Alzheimer's and Amyloid Part 1: The First Mistake

Note: If you haven’t, please read Jeanne Lenzer’s recent piece, “The Campaign to Turn Healthy People into Alzheimer’s Patients [https://www.levernews.com/the-campaign-to-turn-healthy-people-into-alzheimers-patients/?ref=lever-weekly-newsletter].” Jeanne is a brilliant and ferocious journalist, and her piece prompted me to dig into the research history behind it. The next few weeks will be like the Cholesterol Mistake Series [https://researchtranslation.substack.com/p/the-first-cholesterol-mistake]: short pieces describing precisely how Alzheimer’s research has been misinterpreted and distorted. The Alzheimer’s Mistake Series is my attempt to explain how we got here. “Is it some weird poison??” Nicole, our PA, held up a catheter bag. The urine in it was purple—bright purple. “I drew bloods, started a line, and paged renal. Antibiotics?” She added, grimacing, “This can’t be good.” I looked first at the chart, then at the man, who sat comfortably, sipping ginger ale and giggling at The Price is Right. “No need,” I said. “And you can cancel the consult.” RT is entirely reader-supported. I’d like to keep doing it, so please become a paid subscriber. Purple Urinary Bag Syndrome, as it’s known, is a thing—and it is something to behold. The enzymes and bacteria in urine can, on rare occasion, blend to form a witch’s brew that looks like grape soda. But the color, which lasts hours to days, is typically the only ‘problem’ in PUBS. The condition is all bark, and no bite. Which means there’s no reason to risk antibiotic resistance and side effects, or a monster hospital bill for a monster work-up. In essence, PUBS is little more than a master class in visual distraction. Purple urinary bag syndrome Unfortunately, that is a pitfall that has historically sent modern medicine into convulsions of self-defeat. Today, for instance, we are living with the fallout from a distraction first glimpsed [https://onlinelibrary.wiley.com/doi/10.1002/ca.980080612] in 1906 by a German researcher named Alois Alzheimer. Dr. Alzheimer first identified the amyloid plaque, a nasty looking clump of waste found in the brain of a woman who had died of severe, early-onset dementia. That plaque spawned a neurology obsession. Later named Alzheimer’s Disease, the condition is a syndrome of clinical dementia with memory loss that was eventually https://jamanetwork.com/journals/jamaneurology/article-abstract/584730defined [https://jamanetwork.com/journals/jamaneurology/fullarticle/584730] partly by the detection and measurement of those clumps, which are often present on autopsy. Amyloid plaques But they’re not always present. Autopsy data [https://jamanetwork.com/journals/jamaneurology/fullarticle/2737282] show that amyloid plaques are an inconsistent presence in Alzheimer’s—nowhere near the kind of reliable presence that might suggest amyloid as the main cause of Alzheimer’s. Yet sadly, much like cholesterol and the Lipid Hypothesis [https://researchtranslation.substack.com/p/the-first-cholesterol-mistake], in the 1990s dementia researchers bypassed the most fundamental rule of epidemiology: Before you crown a risk factor the main cause, you must prove it IS a risk factor. The rule is unforgiving. If a single factor causes a disease, it should mathematically and reliably predict the disease. With smoking and lung cancer, that association is ironclad. With blood pressure and strokes, it does not falter. But with Alzheimer’s Disease and its supposed culprit—beta-amyloid protein—the association failed from the beginning. (Sound familiar?). Two seminal papers, one by Terry [https://onlinelibrary.wiley.com/doi/abs/10.1002/ana.410300410] in 1991 and a second by Arriagada [https://www.neurology.org/doi/10.1212/wnl.42.3.631] in 1992, are among the most cited studies in the history of the field. Both are autopsy studies, and both found zero statistical relationship between amyloid plaque burden and clinical dementia. Title page and a scatterplot from Arriagada et al, 1992, showing no association (‘NS’ = nonsignificant) between amyloid plaque—the target of current Alzheimer’s drugs—and Alzheimer’s Disease In late 1991 Terry et al. found memory loss had no connection to amyloid plaques, and a year later Arriagada’s scatterplots (above) confirmed the same finding visually. Despite these landmark reports being fundamentally inconsistent with amyloid plaques as a cause of Alzheimer’s, the neurology research community swept them aside and plowed forward with the Amyloid Hypothesis. Why? Perhaps, in part, because under a microscope the plaques look like wreckage—they are visually striking. But they are a distraction. In neurology this discrepancy [https://jamanetwork.com/journals/jamaneurology/fullarticle/2737282] is called the ‘clinico-pathologic disconnect’ and in the research community it is widely known: The brains of many who die with Alzheimer’s have little or no plaque, and most who die with plaque have little or no Alzheimer’s. In fact, autopsies show that the brains of cognitively normal elderly people are often riddled with amyloid plaques. And yet, even as this disconnect became obvious, the die had already been cast. Starting in the late 1980s billions of research dollars and pharmaceutical budgets were being chained to the Amyloid Hypothesis, the unassailable premise that amyloid plaques cause Alzheimer’s Disease. This bizarre conclusion, unsupported by the most basic standards of evidence, spawned careers, research centers, and massive clinical trials, all laser focused on preventing and removing amyloid plaques. Therefore, predictably, when the research from these endeavors began rolling in, the amyloid chickens came home to roost. Next week, in Part 2, I’ll show you how demented mice and the trial of a highly toxic vaccine led unscrupulous researchers to invent a savior for their failed Hypothesis. And how it became one of the most famous, and disastrous, scientific frauds of the century. Get full access to Research Translation at researchtranslation.substack.com/subscribe [https://researchtranslation.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]

The Ghost On the Balance Sheet of Cancer Screening

Cancer screening has always hidden its dark side. Behind the simple messaging and pink ribbons is a long history of complicated truths, failed trials, and titanic spending. Now, with a novel blood test flooding [https://www.zacks.com/stock/news/2919135/hims-hers-expands-digital-healthcare-platform-via-new-care-offerings] the market and media misrepresenting [https://www.theguardian.com/society/2026/may/15/prostate-cancer-screening-save-lives-benefit-small-study] new data, it’s a good time to clarify the simplest truth of all about cancer screening: the balance sheet. To read it correctly, however, you must first learn a jargon term: all-cause mortality. Let us start with a scenario described in the book Hippocrates’ Shadow [https://www.simonandschuster.com/books/Hippocrates-Shadow/David-H-Newman/9781416551546] (ahem, my book): Imagine a treatment so effective that no heart attack patient ever dies—we call it the HeartSaver 3000. When the HeartSaver touches a patient’s chest their heart attack is immediately halted. Historically, up to 10% of such people die but with the HS-3000, heart attack mortality drops to zero. Unfortunately, the Heartsaver also induces fatal strokes—in about 10% of people. The good news is ‘heart attack mortality’ drops by 10%. The bad news is ‘stroke mortality’ rises by 10%. And all-cause mortality stays the same. In trials, cancer screening is like a Heartsaver. Mammograms have never reduced [https://www.bmj.com/content/352/bmj.h6080] all-cause mortality in any trial or combination of trials. The same is true for PSA and colonoscopy screening. Advocates for screening know this and instead tout reductions in breast cancer mortality or prostate cancer mortality (see, for instance [https://www.statnews.com/2026/05/14/psa-tests-reduce-risk-prostate-cancer-deaths-new-study-cochrane-review/], this week [https://www.pulsetoday.co.uk/news/clinical-areas/cancer/cochrane-reviewers-conclude-psa-testing-reduces-deaths-from-prostate-cancer/]’s ebullient headlines [https://www.thetimes.com/uk/healthcare/article/study-benefits-psa-prostate-cancer-screening-9rdnqx0zv] on PSA). But all-cause mortality is the endpoint that matters because it measures deaths, not death-certificate labels. Breast cancer mortality asks whether fewer women died with breast cancer listed as a cause. All-cause mortality asks whether fewer women died. If screening improves the first but not the second, the benefit may be a reshuffling of causes rather than a reduction in deaths. So why, in trials of screening, does breast and prostate cancer mortality go down but NOT all-cause mortality? What other deaths balance out the ledger? Frustratingly, we don’t know. Researchers did not painstakingly account for each exact cause of death in millions of participants, so all we know is that overall deaths did not drop, but breast and prostate cancer mortality did. Which means we’re left to guess about why. And, predictably, those guesses run in two opposing directions. Here’s the guess most popular among screening advocates: There aren’t enough people in screening trials. Since only 2% of people die of breast or prostate cancer, the argument goes, it is very difficult for that 2% to sway the overall numbers. Advocates often argue, therefore, that all-cause mortality is an unfair metric, because even 600,000 women in mammogram trials and 800,000 men in PSA trials isn’t enough. The benefit, they argue, is so small that it would take millions of people in studies before enough breast or prostate cancer deaths accrued to move the needle on all-cause mortality. For skeptics, a different guess is more popular: Either screening doesn’t save lives, or it kills enough people to balance out any lives saved. This argument is grounded in the fact that biopsies, chemotherapy, and major surgeries like mastectomy are substantially increased by screening. Fatal complications of these treatments, even if rare, thus counterbalance any lives saved. These are guesses, not facts. But they highlight a point that is irrefutable, and must be dealt with: Either trials haven’t been large enough to show screening saves lives, or screening doesn’t save lives. Those are the only options. With this fact established, the pro versus con ledger for cancer screening takes on a different hue. On the ‘pro’ side there is a single claim, and it is hypothetical. On the ‘con’ side there are proven harms, and they are legion. For example, more than half of women experience a false cancer scare in ten years of mammograms. MORE THAN HALF. Meanwhile, even if you believe the claimed benefit is real, it amounts to roughly 1 person per thousand. Below is a table of benefits and harms with screening mammography per 1,000 women over ten years, according to the United States Preventive Services Task Force: This balance sheet is, I think, worth putting price tags on. False positives leading to biopsy cost roughly $3,000 each. Unnecessary cancer diagnosis checks in at about $78,000 each. Also of note: More than half of women will suffer the personal cost of weeks to months of anxiety when they’re told they may have cancer (though 95% of the time [https://www.bcsc-research.org/index.php/statistics/screening-performance-benchmarks/performance-measures] or more testing will show this was wrong). For prostate cancer screening in men, this number is roughly a quarter, or 1 in 4. Here is a similar table for prostate cancer screening: Each false positive is, again, about $3,000. Each needle biopsy episode is roughly $10,000. One unnecessary cancer diagnosis costs about $100,000. In addition, treating impotence costs in the range of $5,000 each, while urinary incontinence generates an average bill of $15,000 each. And while that’s an astonishing amount of money, here is the expense virtually no one says out loud: Screening does not merely find disease, it manufactures patients. A woman with a false-positive mammogram becomes a patient until the extra images, ultrasound, MRI, biopsy, pathology report, and follow-up visit say otherwise. A man with an elevated PSA becomes a patient through repeat blood tests, MRI, prostate biopsy, pathology, urology visits, and sometimes a cancer diagnosis—that would never have harmed him. Many then become surgical patients, radiation patients, incontinence patients, impotence patients, surveillance patients. This is not free, and it is not even close. The screening test is just the first bill of many. The real business model in cancer screening is the cascade. A positive screen creates appointments. Appointments create images. Images create biopsies. Biopsies create diagnoses. Diagnoses create procedures. Procedures create complications. Complications create more appointments. The cancer screening machine does not consume one dollar at a time. It consumes in cascades of care that cost thousands to hundreds of thousands each. One estimate is that cancer screening directly costs the U.S. about $43 billion a year. [https://www.eurekalert.org/news-releases/1053067] Add the downstream fallout—false-positives, workups, biopsies, complications, overdiagnosis, overtreatment, surgery, radiation, chemotherapy, surveillance, and treatment of harms—and the total rises to an estimated $70 billion in medical spending. Cancer screening is often sold as a cheap front door to prevention. It is not. The real bill is in the same neighborhood as stroke care—less like a preventive service and more like a chronic care industry. And of course, these numbers do not include anxiety, or lost work, or travel, or the hours spent on hold with billing departments (the most American cancer of all?). The usual response to all of this from screening advocates is that screening is worth it because it saves lives. But the best evidence has found no such thing. What it shows is a small shift in cancer-specific death certificates, purchased with a gargantuan increase in false alarms, procedures, diagnoses, and treatments. This is the difficult truth behind the easy math: When a medical intervention does not clearly reduce all-cause mortality, but clearly creates millions of downstream medical events, the affordability problem is not mysterious. We are not paying to prevent deaths—that is a wishful ghost that cannot be found on the balance sheet. We are paying to diagnose, chase, biopsy, irradiate, cut out, monitor, and medically manage vast numbers of manufactured ‘patients’. That is not prevention. It is a multi-billion-dollar ghost story that sells reassurance, manufactures disease, and then bills for the cleanup. Get full access to Research Translation at researchtranslation.substack.com/subscribe [https://researchtranslation.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]