A New Test Aims to Objectively Measure Pain. It Could Help Legitimate Sufferers Access the Meds They Need.
"That throbbing you feel for the first minute after a door slams on your finger."
This is how Central Florida resident Bridgett Willkie describes the attacks of pain caused by her sickle cell anemia – a genetic blood disorder in which a patient's red blood cells become shaped like sickles and get stuck in blood vessels, thereby obstructing the flow of blood and oxygen.
"I found myself being labeled as an addict and I never was."
Willkie's lifelong battle with the condition has led to avascular necrosis in both of her shoulders, hips, knees and ankles. This means that her bone tissue is dying due to insufficient blood supply (sickle cell anemia is among the medical conditions that can decrease blood flow to one's bones).
"That adds to the pain significantly," she says. "Every time my heart beats, it hurts. And the pain moves. It follows the path of circulation. I liken it to a traffic jam in my veins."
For more than a decade, she received prescriptions for Oxycontin. Then, four years ago, her hematologist – who had been her doctor for 18 years – suffered a fatal heart attack. She says her longtime doctor's replacement lacked experience treating sickle cell patients and was uncomfortable writing her a prescription for opioids. What's more, this new doctor wanted to place her in a drug rehab facility.
"Because I refused to go, he stopped writing my scripts," she says. The ensuing three months were spent at home, detoxing. She describes the pain as unbearable. "Sometimes I just wanted to die."
One of the effects of the opioid epidemic is that many legitimate pain patients have seen their opioids significantly reduced or downright discontinued because of their doctors' fears of over-prescribing addictive medications.
"I found myself being labeled as an addict and I never was...Being treated like a drug-seeking patient is degrading and humiliating," says Willkie, who adds that when she is at the hospital, "it's exhausting arguing with the doctors...You dread them making their rounds because every day they come in talking about weaning you off your meds."
Situations such as these are fraught with tension between patients and doctors, who must remain wary about the risk of over-prescribing powerful and addictive medications. Adding to the complexity is that it can be very difficult to reliably assess a patient's level of physical pain.
However, this difficulty may soon decline, as Indiana University School of Medicine researchers, led by Dr. Alexander B. Niculescu, have reportedly devised a way to objectively assess physical pain by analyzing biomarkers in a patient's blood sample. The results of a study involving more than 300 participants were published earlier this year in the journal Molecular Psychiatry.
Niculescu – who is both a professor of psychiatry and medical neuroscience at the IU School of Medicine – explains that, when someone is in severe physical pain, a blood sample will show biomarkers related to intracellular adhesion and cell-signaling mechanisms. He adds that some of these biomarkers "have prior convergent evidence from animal or human studies for involvement in pain."
Aside from reliably measuring pain severity, Niculescu says blood biomarkers can measure the degree of one's response to treatment and also assess the risk of future recurrences of pain. He believes this new method's greatest benefit, however, might be the ability to identify a number of non-opioid medications that a particular patient is likely to respond to, based on his or her biomarker profile.
Clearly, such a method could be a gamechanger for pain patients and the professionals who treat them. As of yet, health workers have been forced to make crucial decisions based on their clinical impressions of patients; such impressions are invariably subjective. A method that enables people to prove the extent of their pain could remove the stigma that many legitimate pain patients face when seeking to obtain their needed medicine. It would also improve their chances of receiving sufficient treatment.
Niculescu says it's "theoretically possible" that there are some conditions which, despite being severe, might not reveal themselves through his testing method. But he also says that, "even if the same molecular markers that are involved in the pain process are not reflected in the blood, there are other indirect markers that should reflect the distress."
Niculescu expects his testing method will be available to the medical community at large within one to three years.
Willkie says she would welcome a reliable pain assessment method. Well-aware that she is not alone in her plight, she has more than 500 Facebook friends with sickle cell disease, and she says that "all of their opioid meds have been restricted or cut" as a result of the opioid crisis. Some now feel compelled to find their opioids "on the streets." She says she personally has never obtained opioids this way. Instead, she relies on marijuana to mitigate her pain.
Niculescu expects his testing method will be available to the medical community at large within one to three years: "It takes a while for things to translate from a lab setting to a commercial testing arena."
In the meantime, for Willkie and other patients, "we have to convince doctors and nurses that we're in pain."
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.