Colon polyps, illustration
Credit: Sebastian Kaulitzki/Science Photo Library/Getty Images

A machine-learning algorithm detected potential signs of colorectal cancer (CRC) in patients identified as high-risk who had missed a routine colonoscopy, according to a new study led by Geisinger and Medial EarlySign.

The findings, published this month in NEJM Catalyst Innovations in Care Delivery, present a noninvasive method to increase screening among those who may have CRC.

In the study, Geisinger identified a group of 25,610 patients who were overdue for CRC screening, and used a machine-learning algorithm to flag those at highest risk for developing cancer. The algorithm, developed by EarlySign, identified patients as high-risk by analyzing age, gender, and a recent outpatient complete blood count (CBC). A nurse then called the patients to inform them of their risk and offer to schedule a colonoscopy.

Of the patients flagged as high-risk, 68% were scheduled for a colonoscopy, and of those, approximately 70% had a significant finding.

“When carefully implemented and supported by healthcare providers, machine learning can be a low-cost, noninvasive supplement to other colorectal cancer screening efforts,” said Keith Boell, chief quality officer for population initiatives at Geisinger and a co-author of the study. “This technology can act as a safety net, potentially preventing missed or delayed diagnosis among some patients who may already have undiagnosed signs of disease.”

According to the American Cancer Society (ACS), in the United States, colorectal cancer is the third leading cause of cancer-related deaths in men and in women, and the second most common cause of cancer deaths when numbers for men and women are combined. It’s expected to cause about 52,580 deaths during 2022.The ACS estimates for the number of colorectal cancer cases in the United States for 2022 are; 106,180 new cases of colon cancer and 44,850 new cases of rectal cancer.

But despite evidence of the benefits of regular CRC screening and significant efforts among providers and healthcare systems to increase screenings, approximately 32% of age-eligible adults in the United States do not follow current CRC screening guidelines, according to the National Cancer Institute. Serious illness and death from CRC can be prevented if asymptomatic polyps and other early-stage cancers are detected and treated early.

“Our partnership with Geisinger has focused on addressing the devasting impact of CRC with predictive  algorithms that can impact early detection, coupled with integration into clinical workflows that lead to a personalized approach to care that engages patients in prevention and treatment,” said Ori Geva, EarlySign co-founder and CEO.

Founded in 2013, and headquartered in Tel Aviv, Medial’s EarlySign says its solutions allow for early detection of complications from serious disease and help more accurately identify and prioritize patients for multiple conditions for interventions to halt or prevent the serious complications from the onset of disease. The company says its machine learning platform and development environment enables fast and high-quality development of both custom models and pre-built models.

In late 2021, EarlySign inked a deal with Roche. The agreement calls for a multi-stage collaboration in which the parties develop and validate clinical data solutions designed to help global healthcare organizations accelerate their efforts for early detection of serious disease through personalized digital health technology.

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