Trading syphilis for malaria: How doctors treated one deadly disease by infecting patients with another
If you had lived one hundred years ago, syphilis – a bacterial infection spread by sexual contact – would likely have been one of your worst nightmares. Even though syphilis still exists, it can now be detected early and cured quickly with a course of antibiotics. Back then, however, before antibiotics and without an easy way to detect the disease, syphilis was very often a death sentence.
To understand how feared syphilis once was, it’s important to understand exactly what it does if it’s allowed to progress: the infections start off as small, painless sores or even a single sore near the vagina, penis, anus, or mouth. The sores disappear around three to six weeks after the initial infection – but untreated, syphilis moves into a secondary stage, often presenting as a mild rash in various areas of the body (such as the palms of a person’s hands) or through other minor symptoms. The disease progresses from there, often quietly and without noticeable symptoms, sometimes for decades before it reaches its final stages, where it can cause blindness, organ damage, and even dementia. Research indicates, in fact, that as much as 10 percent of psychiatric admissions in the early 20th century were due to dementia caused by syphilis, also known as neurosyphilis.
Like any bacterial disease, syphilis can affect kids, too. Though it’s spread primarily through sexual contact, it can also be transmitted from mother to child during birth, causing lifelong disability.
The poet-physician Aldabert Bettman, who wrote fictionalized poems based on his experiences as a doctor in the 1930s, described the effect syphilis could have on an infant in his poem Daniel Healy:
I always got away clean
when I went out
With the boys.
The night before
I was married
I went out,—But was not so fortunate;
And I infected
My bride.
When little Daniel
Was born
His eyes discharged;
And I dared not tell
That because
I had seen too much
Little Daniel sees not at all
Given the horrors of untreated syphilis, it’s maybe not surprising that people would go to extremes to try and treat it. One of the earliest remedies for syphilis, dating back to 15th century Naples, was using mercury – either rubbing it on the skin where blisters appeared, or breathing it in as a vapor. (Not surprisingly, many people who underwent this type of “treatment” died of mercury poisoning.)
Other primitive treatments included using tinctures made of a flowering plant called guaiacum, as well as inducing “sweat baths” to eliminate the syphilitic toxins. In 1910, an arsenic-based drug called Salvarsan hit the market and was hailed as a “magic bullet” for its ability to target and destroy the syphilis-causing bacteria without harming the patient. However, while Salvarsan was effective in treating early-stage syphilis, it was largely ineffective by the time the infection progressed beyond the second stage. Tens of thousands of people each year continued to die of syphilis or were otherwise shipped off to psychiatric wards due to neurosyphilis.
It was in one of these psychiatric units in the early 20th century that Dr. Julius Wagner-Juaregg got the idea for a potential cure.
Wagner-Juaregg was an Austrian-born physician trained in “experimental pathology” at the University of Vienna. Wagner-Juaregg started his medical career conducting lab experiments on animals and then moved on to work at different psychiatric clinics in Vienna, despite having no training in psychiatry or neurology.
Wagner-Juaregg’s work was controversial to say the least. At the time, medicine – particularly psychiatric medicine – did not have anywhere near the same rigorous ethical standards that doctors, researchers, and other scientists are bound to today. Wagner-Juaregg would devise wild theories about the cause of their psychiatric ailments and then perform experimental procedures in an attempt to cure them. (As just one example, Wagner-Juaregg would sterilize his adolescent male patients, thinking “excessive masturbation” was the cause of their schizophrenia.)
But sometimes these wild theories paid off. In 1883, during his residency, Wagner-Juaregg noted that a female patient with mental illness who had contracted a skin infection and suffered a high fever experienced a sudden (and seemingly miraculous) remission from her psychosis symptoms after the fever had cleared. Wagner-Juaregg theorized that inducing a high fever in his patients with neurosyphilis could help them recover as well.
Eventually, Wagner-Juaregg was able to put his theory to the test. Around 1890, Wagner-Juaregg got his hands on something called tuberculin, a therapeutic treatment created by the German microbiologist Robert Koch in order to cure tuberculosis. Tuberculin would later turn out to be completely ineffective for treating tuberculosis, often creating severe immune responses in patients – but for a short time, Wagner-Juaregg had some success in using tuberculin to help his dementia patients. Giving his patients tuberculin resulted in a high fever – and after completing the treatment, Wagner-Jauregg reported that his patient’s dementia was completely halted. The success was short-lived, however: Wagner-Juaregg eventually had to discontinue tuberculin as a treatment, as it began to be considered too toxic.
By 1917, Wagner-Juaregg’s theory about syphilis and fevers was becoming more credible – and one day a new opportunity presented itself when a wounded soldier, stricken with malaria and a related fever, was accidentally admitted to his psychiatric unit.
When his findings were published in 1918, Wagner-Juaregg’s so-called “fever therapy” swept the globe.
What Wagner-Juaregg did next was ethically deplorable by any standard: Before he allowed the soldier any quinine (the standard treatment for malaria at the time), Wagner-Juaregg took a small sample of the soldier’s blood and inoculated three syphilis patients with the sample, rubbing the blood on their open syphilitic blisters.
It’s unclear how well the malaria treatment worked for those three specific patients – but Wagner-Juaregg’s records show that in the span of one year, he inoculated a total of nine patients with malaria, for the sole purpose of inducing fevers, and six of them made a full recovery. Wagner-Juaregg’s treatment was so successful, in fact, that one of his inoculated patients, an actor who was unable to work due to his dementia, was eventually able to find work again and return to the stage. Two additional patients – a military officer and a clerk – recovered from their once-terminal illnesses and returned to their former careers as well.
When his findings were published in 1918, Wagner-Juaregg’s so-called “fever therapy” swept the globe. The treatment was hailed as a breakthrough – but it still had risks. Malaria itself had a mortality rate of about 15 percent at the time. Many people considered that to be a gamble worth taking, compared to dying a painful, protracted death from syphilis.
Malaria could also be effectively treated much of the time with quinine, whereas other fever-causing illnesses were not so easily treated. Triggering a fever by way of malaria specifically, therefore, became the standard of care.
Tens of thousands of people with syphilitic dementia would go on to be treated with fever therapy until the early 1940s, when a combination of Salvarsan and penicillin caused syphilis infections to decline. Eventually, neurosyphilis became rare, and then nearly unheard of.
Despite his contributions to medicine, it’s important to note that Wagner-Juaregg was most definitely not a person to idolize. In fact, he was an outspoken anti-Semite and proponent of eugenics, arguing that Jews were more prone to mental illness and that people who were mentally ill should be forcibly sterilized. (Wagner-Juaregg later became a Nazi sympathizer during Hitler’s rise to power even though, bizarrely, his first wife was Jewish.) Another problematic issue was that his fever therapy involved experimental treatments on many who, due to their cognitive issues, could not give informed consent.
Lack of consent was also a fundamental problem with the syphilis study at Tuskegee, appalling research that began just 14 years after Wagner-Juaregg published his “fever therapy” findings.
Still, despite his outrageous views, Wagner-Juaregg was awarded the Nobel Prize in Medicine or Physiology in 1927 – and despite some egregious human rights abuses, the miraculous “fever therapy” was partly responsible for taming one of the deadliest plagues in human history.
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."