Americans Fell for a Theranos-Style Scam 100 Years Ago. Will We Ever Learn?
The huckster understands what people want – an easy route to good health -- and figures out just how to provide it as long as no one asks too many questions.
"Americans are very much prone to this sort of thinking: Give me a pill or give me a magical bean that can make me lose weight!"
The keys to success: Hoopla, fancy technology, and gullibility. And oh yes, one more thing: a blood sample. Well, lots and lots of blood samples. Every testing fee counts.
Sound familiar? It could be the story of the preternaturally persuasive Elizabeth Holmes, the disgraced founder of Theranos who stands accused of perpetrating a massive blood-testing fraud. But this is a different story from a different time, one that dates back 100 years but sounds almost like it could unfold on the front page of The Wall Street Journal today.
The main difference: Back then, watchdogs thought they'd be able to vanquish fake medicine and scam science. Fat chance, it turned out. It seems like we're more likely to lose-weight-quick than make much of a dent into quackery and health fraud.
Why? Have we learned anything at all over the past century? As we sweep into a new decade, experts says we're not as advanced as we'd like to think. But the fight against fraud and fakery continues.
Quackery: As American As America Itself
In the 17th century, British healers of questionable reputation got a new name -- "quack," from the Dutch word "quacksalver," which originally referred to someone who treats others with home remedies but developed a new meaning along the lines of "charlatan." And these quacks got a new place to sell their wares: the American colonies.
By 1692, a Boston newspaper advertised a patent medicine that promised to cure "the Griping of the Guts, and the Wind Cholick" and – for good measure – "preventeth that woeful Distemper of the Dry Belly Ach." A couple centuries later, the most famous woman in the United States wasn't a first lady or feminist but a hawker of nostrums named Lydia Estes Pinkham whose "vegetable compound" promised to banish "female complaints." One advertisement suggested that the "sure cure" would have saved the life of a Connecticut clergyman whose wife killed him after suffering from feminine maladies for 16 years.
By the early 20th century, Americans were fascinated by electricity and radiation, and both healers and hucksters embraced the new high-tech era. Men with flagging libidos, for example, could irradiate their private parts with the radioactive Radiendocrinator or buy battery-powered electric belts equipped with dangling bits to supercharge their, um, dangling bits.
The Rise of the Radio Wave 'Cure'
Enter radionics, the (supposed) science of better health via radio waves. The idea was that "healthy people radiate healthy energy," and sickness could be reversed through diagnosis and re-tuning, write Dr. Lydia Kang and Nate Pedersen in their 2017 book "Quackery: A Brief History of the Worst Ways to Cure Everything."
Detecting illness and fixing it required machinery -- Dynamizers, Radioclasts and Oscillocasts – that could cost hundreds of dollars each. Thousands of physicians bought them. Fortunately, they could work remotely, for a fee. The worried-and-potentially-unwell just needed to send a blood sample and, of course, a personal check.
Sting operations revealed radionics to be bogus. A skeptic sent a blood sample to one radionics practitioner in Albuquerque who reported back with news of an infected fallopian tube. In fact, the blood sample came from a male guinea pig. As an American Medical Association leader reported, the guinea pig "had shown no female characteristics up to that time, and a postmortem examination yielded no evidence of ladylike attributes."
When Quackery Refused to Yield
The rise of bogus medical technology in the early 20th century spawned a watchdog industry as organizations like the American Medical Association swept into action, said medical historian Eric Boyle, author of 2012's "Quack Medicine: A History of Combating Health Fraud in Twentieth-Century America."
"When quackery was recognized as a major problem, the people who campaigned for its demise were confident that they could get rid of it," he said. "A lot of people believed that increased education, the truths of science, and laws designed to protect consumers would ultimately drive quackery from the marketplace. And then throughout the century, as modern medicine developed, and more effectively treated one disease after another, many observers remained confident in that prediction."
There's a bid to "flood the information highway with truth to turn the storm of fake promotional stuff into a trickle."
But fake medicine persisted as Americans continued their quest to get- healthy-quick… or get-rich-quick by promising to help others to get- healthy-quick. Even radionics refused to die. It's still around in various forms. And, as the Theranos scandal reveals, we're still hoping our blood can offer the keys to longevity and good health.
Why Do We Still Fall for Scams?
In our own era, the Theranos company rose to prominence when founder and CEO Elizabeth Holmes convinced journalists and investors that she'd found a way to cheaply test drops of blood for hundreds of conditions. Then it all fell apart, famously, when the world learned that the technology didn't work. The company has folded, and Holmes faces a federal trial on fraud charges this year.
"There were a lot of prominent, very smart people who bought into the myth of Elizabeth Holmes," a former employee told "60 Minutes," even though the blood tests never actually worked as advertised.
Shouldn't "prominent, very smart people" know better? "People are gullible," said Dr. Stephen Barrett, a psychiatrist and leading quack-buster who runs the QuackWatch website. But there's more to the story. According to him, we're uniquely vulnerable as individuals to bogus medicine.
Scam artists specifically pinpoint their target audiences, such as "smart people," desperate people and alienated people, he said.
Smart people, for example, might be overconfident about their ability to detect fraud and fall for bogus medicine. Alienated people may distrust the establishment, whether it's the medical field or government watchdogs, and be more receptive to alternative sources of information.
Dr. Barrett also points a finger at magical thinking, which comes in different forms. It could mean a New Age-style belief that our minds can control the world around us. Or, as professional quack-buster Alex Berezow said, it could refer to "our cultural obsession with quick fixes."
"Americans are very much prone to this sort of thinking: Give me a pill or give me a magical bean that can make me lose weight! But complex problems need complex solutions," said Berezow, a microbiologist who debunks junk science in his job as a spokesman for the American Council on Science & Health.
American mistrust of expertise makes matters worse, he said. "When I tell people they need to get vaccinated, I'm called a shill for the pharmaceutical industry," he said. "If I say dietary supplements generally don't work, I'm a shill for doctors who want to keep people sick."
What can ordinary citizens do to protect themselves from fake medicine? "You have to have a healthy skepticism of everything," Berezow said. "When you come across something new, is someone trying to take advantage of you? It's a horrible way to think about the world, but there's some truth to it."
"Like any chronic disease, we will have to live with it while we do our best to fight it."
The government and experts have their own roles to play via regulation and education, respectively. For all the criticism it gets, the Food & Drug Administration does serve as a bulwark against fakery in prescription medicine. And while celebrities like Gwyneth "Goop" Paltrow hawk countless questionable medical products on the Internet, scientists and physicians are fighting back by using social media as a tool to promote the truth. There's a bid to "flood the information highway with truth to turn the storm of fake promotional stuff into a trickle," said Dr. Randi Hutter Epstein, a writer in residence at Yale School of Medicine and author of 2018's "Aroused: The History of Hormones and How They Control Just About Everything."
What's next? Like death, taxes and Cher, charlatans are likely to always be with us. Boyle quoted the late William Jarvis, a pioneering quack-buster in the late 20th century who believed health fraud would never be eradicated: "Like any chronic disease, we will have to live with it while we do our best to fight it."
New Tech Can Predict Breast Cancer Years in Advance
Every two minutes, a woman is diagnosed with breast cancer. The question is, can those at high risk be identified early enough to survive?
New AI software has predicted risk equally well in both white and black women for the first time.
The current standard practice in medicine is not exactly precise. It relies on age, family history of cancer, and breast density, among other factors, to determine risk. But these factors do not always tell the whole story, leaving many women to slip through the cracks. In addition, a racial gap persists in breast cancer treatment and survival. African-American women are 42 percent more likely to die from the disease despite relatively equal rates of diagnosis.
But now those grim statistics could be changing. A team of researchers from MIT's Computer Science and Artificial Intelligence Laboratory have developed a deep learning model that can more accurately predict a patient's breast cancer risk compared to established clinical guidelines – and it has predicted risk equally well in both white and black women for the first time.
The Lowdown
Study results published in Radiology described how the AI software read mammogram images from more than 60,000 patients at Massachusetts General Hospital to identify subtle differences in breast tissue that pointed to potential risk factors, even in their earliest stages. The team accessed the patients' actual diagnoses and determined that the AI model was able to correctly place 31 percent of all cancer patients in the highest-risk category of developing breast cancer within five years of the examination, compared to just 18 percent for existing models.
"Each image has hundreds of thousands of pixels identifying something that may not necessarily be detected by the human eye," said MIT professor Regina Barzilay, one of the study's lead authors. "We all have limited visual capacities so it seems some machines trained on hundreds of thousands of images with a known outcome can capture correlations the human eye might not notice."
Barzilay, a breast cancer survivor herself, had abnormal tissue patterns on mammograms in 2012 and 2013, but wasn't diagnosed until after a 2014 image reading, illustrating the limitations of human processing alone.
MIT professor Regina Barzilay, a lead author on the new study and a breast cancer survivor herself.
(Courtesy MIT)
Next up: The MIT team is looking at training the model to detect other cancers and health risks. Barzilay recalls how a cardiologist told her during a conference that women with heart diseases had a different pattern of calcification on their mammograms, demonstrating how already existing images can be used to extract other pieces of information about a person's health status.
Integration of the AI model in standard care could help doctors better tailor screening and prevention programs based on actual instead of perceived risk. Patients who might register as higher risk by current guidelines could be identified as lower risk, helping resolve conflicting opinions about how early and how often women should receive mammograms.
Open Questions: While the results were promising, it's unknown how well the model will work on a larger scale, as the study looked at data from just one institution and used mammograms supplied by just one hospital. Some risk factor information was also unavailable for certain patients during the study, leaving researchers unable to fully compare the AI model's performance to that of the traditional standard.
One incentive to wider implementation and study, however, is the bonus that no new hardware is required to use the AI model. With other institutions now showing interest, this software could lead to earlier routine detection and treatment of breast cancer — resulting in more lives saved.
Sarah Mancoll was 22 years old when she noticed a bald spot on the back of her head. A dermatologist confirmed that it was alopecia aerata, an autoimmune disorder that causes hair loss.
Of 213 new drugs approved from 2003 to 2012, only five percent included any data from pregnant women.
She successfully treated the condition with corticosteroid shots for nearly 10 years. Then Mancoll and her husband began thinking about starting a family. Would the shots be safe for her while pregnant? For the fetus? What about breastfeeding?
Mancoll consulted her primary care physician, her dermatologist, even a pediatrician. Without clinical data, no one could give her a definitive answer, so she stopped treatment to be "on the safe side." By the time her son was born, she'd lost at least half her hair. She returned to her Washington, D.C., public policy job two months later entirely bald—and without either eyebrows or eyelashes.
After having two more children in quick succession, Mancoll recently resumed the shots but didn't forget her experience. Today, she is an advocate for including more pregnant and lactating women in clinical studies so they can have more information about therapies than she did.
"I live a very privileged life, and I'll do just fine with or without hair, but it's not just about me," Mancoll said. "It's about a huge population of women who are being disenfranchised…They're invisible."
About 4 million women give birth each year in the United States, and many face medical conditions, from hypertension and diabetes to psychiatric disorders. A 2011 study showed that most women reported taking at least one medication while pregnant between 1976 and 2008. But for decades, pregnant and lactating women have been largely excluded from clinical drug studies that rigorously test medications for safety and effectiveness.
An estimated 98 percent of government-approved drug treatments between 2000 and 2010 had insufficient data to determine risk to the fetus, and close to 75 percent had no human pregnancy data at all. All told, of 213 new pharmaceuticals approved from 2003 to 2012, only five percent included any data from pregnant women.
But recent developments suggest that could be changing. Amid widespread concerns about increased maternal mortality rates, women's health advocates, physicians, and researchers are sensing and encouraging a cultural shift toward protecting women through responsible research instead of from research.
"The question is not whether to do research with pregnant women, but how," Anne Drapkin Lyerly, professor and associate director of the Center for Bioethics at the University of North Carolina at Chapel Hill, wrote last year in an op-ed. "These advances are essential. It is well past time—and it is morally imperative—for research to benefit pregnant women."
"In excluding pregnant women from drug trials to protect them from experimentation, we subject them to uncontrolled experimentation."
To that end, the American College of Obstetricians and Gynecologists' Committee on Ethics acknowledged that research trials need to be better designed so they don't "inappropriately constrain the reproductive choices of study participants or unnecessarily exclude pregnant women." A federal task force also called for significantly expanded research and the removal of regulatory barriers that make it difficult for pregnant and lactating women to participate in research.
Several months ago, a government change to a regulation known as the Common Rule took effect, removing pregnant women as a "vulnerable population" in need of special protections -- a designation that had made it more difficult to enroll them in clinical drug studies. And just last week, the U.S. Food and Drug Administration (FDA) issued new draft guidances for industry on when and how to include pregnant and lactating women in clinical trials.
Inclusion is better than the absence of data on their treatment, said Catherine Spong, former chair of the federal task force.
"It's a paradox," said Spong, professor of obstetrics and gynecology and chief of maternal fetal medicine at University of Texas Southwestern Medical Center. "There is a desire to protect women and fetuses from harm, which is translated to a reluctance to include them in research. By excluding them, the evidence for their care is limited."
Jacqueline Wolf, a professor of the history of medicine at Ohio University, agreed.
"In excluding pregnant women from drug trials to protect them from experimentation, we subject them to uncontrolled experimentation," she said. "We give them the medication without doing any research, and that's dangerous."
Women, of course, don't stop getting sick or having chronic medical conditions just because they are pregnant or breastfeeding, and conditions during pregnancy can affect a baby's health later in life. Evidence-based data is important for other reasons, too.
Pregnancy can dramatically change a woman's physiology, affecting how drugs act on her body and how her body acts or reacts to drugs. For instance, pregnant bodies can more quickly clear out medications such as glyburide, used during diabetes in pregnancy to stabilize high blood-sugar levels, which can be toxic to the fetus and harmful to women. That means a regular dose of the drug may not be enough to control blood sugar and prevent poor outcomes.
Pregnant patients also may be reluctant to take needed drugs for underlying conditions (and doctors may be hesitant to prescribe them), which in turn can cause more harm to the woman and fetus than had they been treated. For example, women who have severe asthma attacks while pregnant are at a higher risk of having low-birthweight babies, and pregnant women with uncontrolled diabetes in early pregnancy have more than four times the risk of birth defects.
Current clinical trials involving pregnant women are assessing treatments for obstructive sleep apnea, postpartum hemorrhage, lupus, and diabetes.
For Kate O'Brien, taking medication during her pregnancy was a matter of life and death. A freelance video producer who lives in New Jersey, O'Brien was diagnosed with tuberculosis in 2015 after she became pregnant with her second child, a boy. Even as she signed hospital consent forms, she had no idea if the treatment would harm him.
"It's a really awful experience," said O'Brien, who now is active with We are TB, an advocacy and support network. "All they had to tell me about the medication was just that women have been taking it for a really long time all over the world. That was the best they could do."
More and more doctors, researchers and women's health organizations and advocates are calling that unacceptable.
By indicating that filling current knowledge gaps is "a critical public health need," the FDA is signaling its support for advancing research with pregnant women, said Lyerly, also co-founder of the Second Wave Initiative, which promotes fair representation of the health interests of pregnant women in biomedical research and policies. "It's a very important shift."
Research with pregnant women can be done ethically, Lyerly said, whether by systematically collecting data from those already taking medications or enrolling pregnant women in studies of drugs or vaccines in development.
Current clinical trials involving pregnant women are assessing treatments for obstructive sleep apnea, postpartum hemorrhage, lupus, and diabetes. Notable trials in development target malaria and HIV prevention in pregnancy.
"It clearly is doable to do this research, and test trials are important to provide evidence for treatment," Spong said. "If we don't have that evidence, we aren't making the best educated decisions for women."