The Ghost On the Balance Sheet of Cancer Screening

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

Last week 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]

Surgery To Treat Knee Degeneration Increased Knee Degeneration

Dr. Katz, the attending ER doctor, walked ahead of me as we left the bedside of a woman with abdominal pain and vomiting. “What’s the most common reason for emergency surgical admission to the hospital?” Wanting to impress him, I stumbled. “Um, appendicitis?” “In the top three, but no.” Dr. Katz sat down and began typing. I tried again. “Gall bladder?” He didn’t look up. “Also top three—one left.” Defeated, I mumbled. “Small bowel obstruction?” Attending: “Correct. And the most common reason for small bowel obstruction?” This one I knew. “Adhesions from prior surgery.” Dr. Katz kept typing but freed a hand briefly to point at me. “Nailed it. So, in summary, what’s the most common reason for emergency surgery?” Finally understanding, I shook my head in amazement. “Prior surgery.” “Yessssss” he said, still typing. ------ Research Translation is 100% reader supported—to help me continue, become a paid subscriber. This is not just a clever teaching pearl. It goes to the core of modern medicine’s deepest problems. Because medicine has a habit of creating self-sustaining ecosystems. And nowhere is this more visible than orthopedic surgery. Each year in the U.S. hundreds of thousands of people undergo arthroscopic surgery for meniscal tears and degenerated knees. Yet for decades sham-controlled trials have shown the surgeries to be roughly as effective as sham surgery, during which surgeons only pretend to operate. But the surgeries continue. On April 29th the 10-year follow-up of the FIDELITY trial was published [https://www.nejm.org/doi/10.1056/NEJMc2516079]. The trial assigned people to surgery versus fake surgery for meniscal tears of the knee. First reported in 2013, there was no benefit after one year [https://www.nejm.org/doi/full/10.1056/NEJMoa1305189]. Then, same results at two years [https://ard.bmj.com/content/77/2/188] and five years [https://blogs.bmj.com/bjsm/2020/09/09/arthroscopic-partial-meniscectomy-for-degenerative-knee-disease-just-sham-or-does-it-potentially-harm/]. Through it all, the only obvious harms seemed to be the cost, pain, inconvenience, and surgical risk of the procedure itself. By ten years, however, things changed. People in the real surgery group had more arthritis, more knee pain, and needed more surgeries. Major corrective surgery including knee replacement was roughly three times more frequent. Disaster. This is the orthopedic equivalent of the cobra effect. In colonial India British officials, alarmed by venomous cobras, offered bounties for dead snakes. Enterprising citizens promptly began killing cobras. Then they began breeding more of them, in order to kill them. Eventually the government canceled the program. Whereupon the now-worthless cobras were released into the wild. The result: More cobras than ever. Modern orthopedics is eerily similar. Knee pain leads to MRI, which reveals ‘abnormalities’: torn meniscus, ratty cartilage, degeneration. Surgery follows. Then complications, accelerated arthritis, persistent pain, more imaging, more surgery. The system feeds itself. Cardiology has long struggled with what’s called the oculostenotic reflex—the irresistible urge to open any narrowed artery once it’s seen. Orthopedics suffers from its own version: the orthoquixotic reflex, the irresistible urge to heroically repair structural abnormalities. See a tear, repair it. See degeneration, shave it. See asymmetry, align it. Like Don Quixote charging windmills, modern orthopedics often mistakes visible imperfection for an enemy that must be defeated. In a Finnish study I covered recently [https://researchtranslation.substack.com/p/orthopedic-surgerys-big-problem], 96% of MRIs in healthy adults with perfectly functioning shoulders had surgically ‘fixable’ findings. That’s a lot of windmills. And yet trials show we are aggressively tilting at them—roughly a million or more elective surgeries each year in the U.S. that are done to fix ‘abnormalities’ seen on imaging, despite randomized trials repeatedly failing to show meaningful benefit. This includes surgeries for meniscus [https://www.nejm.org/doi/10.1056/NEJMoa1305189] degeneration, acute meniscal [https://evidence.nejm.org/doi/10.1056/EVIDoa2100038] tear, osteoarthritis [https://www.nejm.org/doi/full/10.1056/NEJMoa013259], rotator cuffs [https://pubmed.ncbi.nlm.nih.gov/27385156/], ACL [https://www.nejm.org/doi/full/10.1056/NEJMoa0907797] repair, shoulder decompression [https://www.bmj.com/content/391/bmj-2025-086201], and more. One of the most extraordinary recent examples came not in elderly knees, but in children. In the CRAFFT trial [https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(26)00409-5/fulltext] children with dramatically displaced wrist fractures were randomly assigned to surgical fixation or casting with no manipulation. The result: No important differences between groups including, incredibly, for short-term function. Above is one example of a nine year old’s awful-looking wrist fracture. Pictures A and B are front and side views at the time of injury, showing both bones are displaced and ‘off-ended’. Two years later, panels C and D, there’s no trace of injury—after no manipulation, operation, hardware, or anesthesia of any kind. Kids, man. One would think adults, and degenerating joints, might be different. But adult versions of the CRAFFT trial keep giving us the same answer. To be clear, orthopedic surgery is a crucially important specialty. When bones are shattered and joints disrupted, surgery can be miraculous. But the FIDELITY trial now suggests the orthoquixotic reflex is not merely generating unnecessary surgeries. It may be creating a vast new population of patients harmed by the surgeries themselves. Get full access to Research Translation at researchtranslation.substack.com/subscribe [https://researchtranslation.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]

Paxlovid: A Requiem

Paxlovid is dead. Again. Last month Pfizer’s pill for Covid failed in two large trials [https://www.nejm.org/doi/full/10.1056/NEJMoa2502457] published together in the New England Journal of Medicine. The bigger one, with roughly 1,700 participants per group, found 14 people assigned to Paxlovid were hospitalized versus 11 in the control group. No benefit—and leaning in the wrong direction. This was a long time coming. But it’s definitely been coming. I’ve written [https://researchtranslation.substack.com/p/the-secret-studies-of-paxlovid] a handful of pieces [https://researchtranslation.substack.com/p/secret-study-revealed] on Paxlovid, including the hidden studies, nasty side effects [https://researchtranslation.https://researchtranslation.substack.com/p/fact-checking-the-times-on-paxlovid], FDA path [https://researchtranslation.substack.com/p/secret-study-revealed], and more. Which is why a post-mortem might tell us something about our information ecosystem, and how careful translation of research has the potential to change the world. To illustrate, below is a timeline of Paxlovid’s major trials. Green dots indicate a trial that found benefit, red dots mean a trial in which the drug failed. RT is 100% reader-supported, and I’d love to keep doing it. To help that happen, please become a paid subscriber. The first trial, a green dot from 2022, represents the trial that led to the FDA’s Emergency Use Authorization. It was preliminary, rushed, and never intended as a final answer. In it, researchers tested the drug exclusively in people who were unvaccinated and had never been exposed to Covid—a group that no longer exists. In every trial since then, done in populations relevant to today, the drug has failed. The red dots, representing six additional trials, all found no benefit. To my mind the key moment occurred in July 2022 (the dashed vertical line). This is the date of a press release notifying Pfizer’s investors that Paxlovid’s second trial, which enrolled people vaccinated or previously exposed to Covid, was stopped early for futility. The drug failed to reduce hospitalization or death, and failed to reduce symptoms of Covid. No benefit in any outcome. This result should have forced everyone to wonder: Can Paxlovid help people in the current world? The answer was no. Paxlovid failed not just for high-risk people with Covid, it also failed as Covid prevention, for severe Covid, and in Long Covid. By mid-2023 the data were consistent. Worse yet, the evidence for rebound, a relapse illness commonly caused by Paxlovid, was piling up [https://www.acpjournals.org/doi/10.7326/M23-1756]. With that in mind, now look at the blue dots. These are NY Times headlines, which were telling a starkly different story. Paxlovid, according to the Times, was beneficial and underused. Which raises a critical point about medical evidence. For serious research translators, randomized trials are not one input among many. They are at the top of a hierarchy. They are the method we use to strip away bias—to neutralize the hidden distortions that make ineffective treatments appear useful. This is why when randomized trial evidence is available, it replaces weaker forms of evidence. It doesn’t sit beside them. It supersedes them. And yet with Paxlovid the NY Times repeatedly used weaker studies to rhetorically discredit randomized trials. Their 2025 headline, “Paxlovid Improved Long Covid Symptoms In Some Patients” is shocking, partly because it was based on a 13-person case series [https://www.nature.com/articles/s43856-024-00668-8]. Case series are—literally—the lowest form of scientific evidence available. Two years earlier, Paxlovid had failed in a double-blinded randomized trial [https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2819901] for Long Covid. In fact, just months after the headline, it failed again in a second randomized trial [https://www.thelancet.com/journals/laninf/article/PIIS1473-3099%2825%2900073-8/fulltext], which the Times neither covered nor even acknowledged. In this way, quietly, the NY Times inverted the evidence hierarchy, trumpeting weaker studies in order to discredit and eclipse the results of much stronger ones. But the Times is not alone. They simply co-opted and amplified the opinions of ‘experts’, the CDC, the FDA, the AMA, and more. How did these people and institutions get Paxlovid so wrong? Institutions optimize for their own incentives: Media organizations optimize for engagement. Pharmaceutical companies optimize for sales. Professional societies optimize for relevance and authority. Public health agencies optimize for actionable guidance. Conventional wisdom is therefore held hostage by the institutions with the power and influence to sculpt it—even when they prefer the opposite of truth. But this is the path to irony, because science will always move toward truth, and falsehoods will be revealed. And when they are the institutions that used their influence for self interest will find that influence slipping away. Which is how we got here. The real lesson, therefore, is not that medicine gets things wrong. Of course it does. Urgent first studies of potentially profitable pandemic cures will often be wrong. Think remdesivir, molnupiravir, and others. But rigorous evidence translation sees those errors in real time, and can hold institutions accountable before they dig in—saving them, and the rest of us, from themselves. Which raises an interesting question for today: The mad scramble to restore institutional influence is now underway—who will blink first? Which major institution will formally correct before the others? It has been four years since Pfizer announced [https://www.fiercepharma.com/pharma/pfizer-stops-paxlovid-work-less-vulnerable-covid-19-patients-after-no-benefit-symptom-relief] their drug failed in the only relevant population. Two years since those data were formally published [https://www.nejm.org/doi/full/10.1056/NEJMoa2309003]. And two weeks since large new trials beat a dead horse by burying Paxlovid yet again. As of this writing, perhaps unsurprisingly, the NY Times has offered zero news coverage of the new trials. Nor is the Times unusual. Yale Medicine still strongly promotes [https://www.yalemedicine.org/news/13-things-to-know-paxlovid-covid-19] Paxlovid on its public website. Google’s AI overview [https://www.google.com/search?q=paxlovid&client=firefox-b-d&hs=QBqp&sca_esv=97234541236c36f9&biw=1102&bih=665&sxsrf=ANbL-n7SteRs_8ncFyVC8xI_dEOcEkzBwg%3A1778084612575&ei=BGv7aeDcItO5mtkP4KjRkQ8&ved=0ahUKEwjg7tmtiaWUAxXTnCYFHWBUNPIQ4dUDCBE&uact=5&oq=paxlovid&gs_lp=Egxnd3Mtd2l6LXNlcnAiCHBheGxvdmlkSMcoUABYAHABeAGQAQCYAQCgAQCqAQC4AQPIAQCYAgCgAgCYAwCIBgGSBwCgBwCyBwC4BwDCBwDIBwCACAE&sclient=gws-wiz-serp] still says the drug reduces hospitalization and death. The first page of a google search is dominated by FDA, CDC, Pfizer, and Wikipedia entries, all presenting Paxlovid as a lifesaver. Which helps to clarify the lesson of the Paxlovid timeline. Bad science is not the greatest danger. Science usually self-corrects. The greater danger is institutional pride and inertia: the years-long gap between when science settles a question and when institutions are willing to absorb the answer. That gap is costing billions, distorting public understanding, and exposing millions to a harmful drug that simply did not—and does not—work. But the evidence was there all along. Research Translation is totally reader-supported. If you dig it, please become a paid subscriber so I can keep it up! Get full access to Research Translation at researchtranslation.substack.com/subscribe [https://researchtranslation.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]