Weill Cornell Medicine

Two Medicaid policies together play vital roles in drawing more Black and Hispanic patients to enroll in cancer clinical trials, according to a new analysis. Black and Hispanic patients are historically underrepresented in cancer clinical trials, which provide essential information to researchers and give patients access to the latest treatment options. This study led by Dr. William Schpero of Weill Cornell Medicine and Dr. Samuel U. Takvorian of the University of Pennsylvania School of Medicine, examined the effect of the interaction between two Medicaid policies on the rates of enrollment for Black or Hispanic adults in cancer clinical trials in the United States: Medicaid expansion under the Affordable Care Act (ACA) and pre-existing state-level mandates requiring Medicaid coverage of the routine costs of clinical trial participation. The study team analyzed deidentified national enrollment data for nearly 50,000 participants in cancer clinical trials from 2012 to 2019 from Medidata’s Rave electronic data capture archives. Only 12 states and the District of Columbia mandated Medicaid coverage of clinical trial costs during the study period. It was not until 2022 that all state Medicaid programs were federally mandated to cover the routine costs of clinical trials. Researchers found that expanding Medicaid combined with mandates to cover clinical trial costs led to more Black and Hispanic patients participating in trials. https://bit.ly/4bRQdUE

A blood test that measures the number of lymphocytes, a type of white blood cell in the body, may predict if people who have relapsed multiple myeloma are going to respond well to CAR-T immunotherapy, according to new research. The study found that patients who had an increase in absolute lymphocyte count (ALC) during the first 15 days after receiving a CAR-T infusion had a higher chance of a complete response and better progression-free survival than patients with a lower ALC at day 15. Knowing that the treatment may not work allows doctors to try other options more quickly. The research team was led by Dr. Mateo Mejia Saldarriaga and Dr. Mark Bustoros of Weill Cornell Medicine and teams from NewYork-Presbyterian Hospital, Columbia University and Icahn School of Medicine at Mount Sinai. Full story: https://bit.ly/4dfMNMm

The stethoscope may be a doctor's most iconic and recognizable instrument. The tool helps doctors listen to internal body processes, such as your heartbeat or breathing. Dr. Anaïs Rameau of Weill Cornell Medicine thinks diagnostic listening can go further. An expert in voice, airway and swallowing dysfunction, Dr. Rameau is now investigating how acoustic analysis can detect changes in swallowing to screen for aspiration — which puts people with age-related conditions at risk for pneumonia — and how vocal changes may provide biomarkers for diagnosing and monitoring conditions ranging from cancer to Alzheimer's. "The voice is connected to so many physical and mental processes," Dr. Rameau said. "We think it is a window into illness and dysfunction." To test her hypothesis, Dr. Rameau has turned to a team of experts ranging from Cornell ornithologists studying birdsong and whale calls to computer scientists and AI experts. The Bridge2AI Voice project explores the use of machine learning to analyze voice recordings for biomarkers. Unlike other AI projects that rely on readily available text or images to train models, the team has to start from scratch. Dr. Olivier Elemento estimates they will need 40,000 samples from recruited and consenting participants. As arduous as it may be, it's also an opportunity to avoid biases that have compromised other medical AI projects. Read more in our summer issue of IMPACT: https://bit.ly/3Wi47JV

Researchers have developed a preclinical model with visual impairment similar to that seen in patients with Parkinson's to better understand the development of the disease, which affects an estimated one million Americans. Although it is popularly known as a movement disorder, its effects on the brain and body can include early vision problems, dementia, sleep disorders, and reduced intestinal function. Findings from the team at Weill Cornell Medicine point to a potential new strategy for detecting Parkinson’s disease, understanding the disease's mechanisms and testing potential therapies. Read more: https://bit.ly/4cLMlFY

The Weill Cornell Medicine Human Resources and Flourish program hosted the first Well-Being Week & Expo to create an environment where our staff can thrive. Our benefit vendors supported the event and featured virtual well-being webinars focusing on emotional, financial and physical wellness. Additionally, the Well-Being Expo provided an interactive opportunity for staff to explore wellness, meet clinical departments, and learn more about health and retirement benefits. It was a fantastic opportunity for everyone to dive into what makes us all feel great!

"I'm a tough guy and I can handle pain, but it got to the point where I couldn't leave the house. It was happening too often and too intensely; it was interfering with my quality of life," said Pat Pesce, a retired NYPD detective turned security driver. Pat faced a formidable opponent in trigeminal neuralgia, a debilitating condition that was causing him severe facial pain. Despite his toughness, the pain threatened to sideline him, prompting a search for relief. Dr. Matthew Fink of Weill Cornell Medicine and NewYork-Presbyterian Hospital diagnosed him and prescribed medication, but the pain persisted. That's when he decided to explore surgical options. Trigeminal neuralgia causes severe pain along the trigeminal nerve pathway and can be caused by nerve compression. Dr. Philip Stieg, a neurosurgeon at Weill Cornell Medicine and NewYork-Presbyterian Hospital, suggested microvascular decompression surgery. Still, Pat opted for a radiofrequency lesioning procedure, which provided temporary relief, but the pain returned. This delicate procedure involved relocating blood vessels compressing the nerve, offering Pat a new lease on life. After his surgery, Pat experienced profound relief from the pain that once hindered his everyday joys. He now enjoys retirement with his family and is grateful for his skilled and compassionate medical team. Pat's journey highlights the importance of early intervention and trust in healthcare providers. His resilience and confidence in his medical team demonstrate the transformative power of professional care in overcoming debilitating conditions. Patrick, now 74, enjoys a pain-free retirement and spends time with his family. However, he has not lost his old habits and is back driving, picking up his two-and-a-half-year-old great-granddaughter. After reflecting on his experience, Pat encourages others who face similar challenges to seek prompt medical guidance and trust in their physicians. He expresses immense gratitude for his care team and embraces each day with renewed vigor, celebrating his freedom from pain.

Our researchers have used machine learning to define three subtypes of Parkinson’s disease, a finding that may inform the development of customized treatment strategies for patients. “Parkinson’s disease is highly heterogeneous, which means that people with the same disease can have very different symptoms,” said Dr. Feng Wei of Weill Cornell Medicine. “This indicates there is not likely to be a one-size-fits-all approach to treating it." Using deep learning-based approaches to analyze database records, a team led by Dr. Wang and Dr. Chang Su have identified three subtypes based on disease progression. They named them the Inching Pace subtype (PD-I, about 36% of patients) for disease with a mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M, about 51% of patients) for cases that have mild baseline severity but advance at a moderate rate; and Rapid Pace subtype (PD-R), for cases with the most rapid symptom progression rate. They also explored the molecular mechanism associated with each subtype and found distinct brain imaging and cerebrospinal fluid biomarkers for the three subtypes. https://bit.ly/4cH5jOb