Coronavirus Risk Calculators: What You Need to Know
People in my family seem to develop every ailment in the world, including feline distemper and Dutch elm disease, so I naturally put fingers to keyboard when I discovered that COVID-19 risk calculators now exist.
"It's best to look at your risk band. This will give you a more useful insight into your personal risk."
But the results – based on my answers to questions -- are bewildering.
A British risk calculator developed by the Nexoid software company declared I have a 5 percent, or 1 in 20, chance of developing COVID-19 and less than 1 percent risk of dying if I get it. Um, great, I think? Meanwhile, 19 and Me, a risk calculator created by data scientists, says my risk of infection is 0.01 percent per week, or 1 in 10,000, and it gave me a risk score of 44 out of 100.
Confused? Join the club. But it's actually possible to interpret numbers like these and put them to use. Here are five tips about using coronavirus risk calculators:
1. Make Sure the Calculator Is Designed For You
Not every COVID-19 risk calculator is designed to be used by the general public. Cleveland Clinic's risk calculator, for example, is only a tool for medical professionals, not sick people or the "worried well," said Dr. Lara Jehi, Cleveland Clinic's chief research information officer.
Unfortunately, the risk calculator's web page fails to explicitly identify its target audience. But there are hints that it's not for lay people such as its references to "platelets" and "chlorides."
The 19 and Me or the Nexoid risk calculators, in contrast, are both designed for use by everyone, as is a risk calculator developed by Emory University.
2. Take a Look at the Calculator's Privacy Policy
COVID-19 risk calculators ask for a lot of personal information. The Nexoid calculator, for example, wanted to know my age, weight, drug and alcohol history, pre-existing conditions, blood type and more. It even asked me about the prescription drugs I take.
It's wise to check the privacy policy and be cautious about providing an email address or other personal information. Nexoid's policy says it provides the information it gathers to researchers but it doesn't release IP addresses, which can reveal your location in certain circumstances.
John-Arne Skolbekken, a professor and risk specialist at Norwegian University of Science and Technology, entered his own data in the Nexoid calculator after being contacted by LeapsMag for comment. He noted that the calculator, among other things, asks for information about use of recreational drugs that could be illegal in some places. "I have given away some of my personal data to a company that I can hope will not misuse them," he said. "Let's hope they are trustworthy."
The 19 and Me calculator, by contrast, doesn't gather any data from users, said Cindy Hu, data scientist at Mathematica, which created it. "As soon as the window is closed, that data is gone and not captured."
The Emory University risk calculator, meanwhile, has a long privacy policy that states "the information we collect during your assessment will not be correlated with contact information if you provide it." However, it says personal information can be shared with third parties.
3. Keep an Eye on Time Horizons
Let's say a risk calculator says you have a 1 percent risk of infection. That's fairly low if we're talking about this year as a whole, but it's quite worrisome if the risk percentage refers to today and jumps by 1 percent each day going forward. That's why it's helpful to know exactly what the numbers mean in terms of time.
Unfortunately, this information isn't always readily available. You may have to dig around for it or contact a risk calculator's developers for more information. The 19 and Me calculator's risk percentages refer to this current week based on your behavior this week, Hu said. The Nexoid calculator, by contrast, has an "infinite timeline" that assumes no vaccine is developed, said Jonathon Grantham, the company's managing director. But your results will vary over time since the calculator's developers adjust it to reflect new data.
When you use a risk calculator, focus on this question: "How does your risk compare to the risk of an 'average' person?"
4. Focus on the Big Picture
The Nexoid calculator gave me numbers of 5 percent (getting COVID-19) and 99.309 percent (surviving it). It even provided betting odds for gambling types: The odds are in favor of me not getting infected (19-to-1) and not dying if I get infected (144-to-1).
However, Grantham told me that these numbers "are not the whole story." Instead, he said, "it's best to look at your risk band. This will give you a more useful insight into your personal risk." Risk bands refer to a segmentation of people into five categories, from lowest to highest risk, according to how a person's result sits relative to the whole dataset.
The Nexoid calculator says I'm in the "lowest risk band" for getting COVID-19, and a "high risk band" for dying of it if I get it. That suggests I'd better stay in the lowest-risk category because my pre-existing risk factors could spell trouble for my survival if I get infected.
Michael J. Pencina, a professor and biostatistician at Duke University School of Medicine, agreed that focusing on your general risk level is better than focusing on numbers. When you use a risk calculator, he said, focus on this question: "How does your risk compare to the risk of an 'average' person?"
The 19 and Me calculator, meanwhile, put my risk at 44 out of 100. Hu said that a score of 50 represents the typical person's risk of developing serious consequences from another disease – the flu.
5. Remember to Take Action
Hu, who helped develop the 19 and Me risk calculator, said it's best to use it to "understand the relative impact of different behaviors." As she noted, the calculator is designed to allow users to plug in different answers about their behavior and immediately see how their risk levels change.
This information can help us figure out if we should change the way we approach the world by, say, washing our hands more or avoiding more personal encounters.
"Estimation of risk is only one part of prevention," Pencina said. "The other is risk factors and our ability to reduce them." In other words, odds, percentages and risk bands can be revealing, but it's what we do to change them that matters.
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.