Tapping into the Power of the Placebo Effect
When Wayne Jonas was in medical school 40 years ago, doctors would write out a prescription for placebos, spelling it out backwards in capital letters, O-B-E-C-A-L-P. The pharmacist would fill the prescription with a sugar pill, recalls Jonas, now director of integrative health programs at the Samueli Foundation. It fulfilled the patient's desire for the doctor to do something when perhaps no drug could help, and the sugar pills did no harm.
Today, that deception is seen as unethical. But time and time again, studies have shown that placebos can have real benefits. Now, researchers are trying to untangle the mysteries of placebo effect in an effort to better treat patients.
The use of placebos took off in the post-WWII period, when randomized controlled clinical trials became the gold standard for medical research. One group in a study would be treated with a placebo, a supposedly inert pill or procedure that would not affect normal healing and recovery, while another group in the study would receive an "active" component, most commonly a pill under investigation. Presumably, the group receiving the active treatment would have a better response and the difference from the placebo group would represent the efficacy of the drug being tested. That was the basis for drug approval by the U.S. Food and Drug Administration.
"Placebo responses were marginalized," says Ted Kaptchuk, director of the Program in Placebo Studies & Therapeutic Encounters at Harvard Medical School. "Doctors were taught they have to overcome it when they were thinking about using an effective drug."
But that began to change around the turn of the 21st century. The National Institutes of Health held a series of meetings to set a research agenda and fund studies to answer some basic questions, led by Jonas who was in charge of the office of alternative medicine at the time. "People spontaneously get better all the time," says Kaptchuk. The crucial question was, is the placebo effect real? Is it more than just spontaneous healing?
Brain mechanisms
A turning point came in 2001 in a paper in Science that showed physical evidence of the placebo effect. It used positron emission tomography (PET) scans to measure release patterns of dopamine — a chemical messenger involved in how we feel pleasure — in the brains of patients with Parkinson's disease. Surprisingly, the placebo activated the same patterns that were activated by Parkinson's drugs, such as levodopa. It proved the placebo effect was real; now the search was on to better understand and control it.
A key part of the effect can be the beliefs, expectations, context, and "rituals" of the encounter between doctor and patient. Belief by the doctor and patient that the treatment would work, and the formalized practices of administering the treatment can all contribute to a positive outcome.
Conditioning can be another important component in generating a response, as Pavlov demonstrated more than a century ago in his experiments with dogs. They were trained with a bell prior to feeding such that they would begin to salivate in anticipation at the sound of a bell even with no food present.
Translating that to humans, studies with pain medications and sleeping aids showed that patients who had a positive response with a certain dose of those medications could have the same response if the doses was reduced and a dummy pill substituted, even to the point where there was no longer any active ingredient.
Researchers think placebo treatments can work particularly well in helping people deal with pain and psychological disorders.
Those types of studies troubled Kaptchuk because they often relied on deception; patients weren't told they were receiving a placebo, or at best there was a possibility that they might be randomized to receive a placebo. He believed the placebo effect could work even if patients were told upfront that they were going to receive a placebo. More than a dozen so call "open-label placebo" studies across numerous medical conditions, by Kaptchuk and others, have shown that you don't have to lie to patients for a placebo to work.
Jonas likes to tell the story of a patient who used methotrexate, a potent immunosuppressant, to control her rheumatoid arthritis. She was planning a long trip and didn't want to be bothered with the injections and monitoring required in using the drug, So she began to drink a powerful herbal extract of anise, a licorice flavor that she hated, prior to each injection. She reduced the amount of methotrexate over a period of months and finally stopped, but continued to drink the anise. That process had conditioned her body "to alter her immune function and her autoimmunity" as if she were taking the drug, much like Pavlov's dogs had been trained. She has not taken methotrexate for more than a year.
An intriguing paper published in May 2021 found that mild, non-invasive electric stimulation to the brain could not only boost the placebo effect on pain but also reduce the "nocebo" effect — when patients report a negative effect to a sham treatment. While the work is very preliminary, it may open the door to directly manipulating these responses.
Researchers think placebo treatments can work particularly well in helping people deal with pain and psychological disorders, areas where drugs often are of little help. Still, placebos aren't a cure and only a portion of patients experience a placebo effect.
Nocebo
If medicine were a soap opera, the nocebo would be the evil twin of the placebo. It's what happens when patients have adverse side effects because of the expectation that they will. It's commonly seem when patients claims to experience pain or gastric distress that can occur with a drug even when they've received a placebo. The side effects were either imagined or caused by something else.
"Up to 97% of reported pharmaceutical side effects are not caused by the drug itself but rather by nocebo effects and symptom misattribution," according to one 2019 paper.
One way to reduce a nocebo response is to simply not tell patients that specific side effects might occur. An example is a liver biopsy, in which a large-gauge needle is used to extract a tissue sample for examination. Those told ahead of time that they might experience some pain were more likely to report pain and greater pain than those who weren't offered this information.
Interestingly, a nocebo response plays out in the hippocampus, a part of the brain that is never activated in a placebo response. "I think what we are dealing with with nocebo is anxiety," says Kaptchuk, but he acknowledges that others disagree.
Distraction may be another way to minimize the nocebo effect. Pediatricians are using virtual reality (VR) to engage children and distract them during routine procedures such as blood draws and changing wound dressings, and burn patients of all ages have found relief with specially created VRs.
Treatment response
Jonas argues that what we commonly call the placebo effect is misnamed and leading us astray. "The fact is people heal and that inherent healing capacity is both powerful and influenced by mental, social, and contextual factors that are embedded in every medical encounter since the idea of treatment began," he wrote in a 2019 article in the journal Frontiers in Psychiatry. "Our understanding of healing and ability to enhance it will be accelerated if we stop using the term 'placebo response' and call it what it is—the meaning response, and its special application in medicine called the healing response."
He cites evidence that "only 15% to 20% of the healing of an individual or a population comes from health care. The rest—nearly 80%—comes from other factors rarely addressed in the health care system: behavioral and lifestyle choices that people make in their daily life."
To better align treatments and maximize their effectiveness, Jonas has created HOPE (Healing Oriented Practices & Environments) Note, "a patient-guided process designed to identify the patient's values and goals in their life and for healing." Essentially, it seeks to make clear to both doctor and patient what the patient's goals are in seeking treatment. In an extreme example of terminal cancer, some patients may choose to extend life despite the often brutal treatments, while others might prefer to optimize quality of life in the remaining time that they have. It builds on practices already taught in medical schools. Jonas believes doctors and patients can use tools like these to maximize the treatment response and achieve better outcomes.
Much of the medical profession has been resistant to these approaches. Part of that is simply tradition and limited data on their effectiveness, but another very real factor is the billing process for how they are reimbursed. Jonas says a new medical billing code added this year gives doctors another way to be compensated for the extra time and effort that a more holistic approach to medicine may initially require. Other moves away from fee-for-service payments to bundling and payment for outcomes, and the integrated care provided by the Veterans Affairs, Kaiser Permanente and other groups offer longer term hope for the future of approaches that might enhance the healing response.
This article was first published by Leaps.org on July 7, 2021.
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.