New Prediction Model Could Slash Unnecessary Pancreatic Cancer Biopsies

Researchers have developed a new prediction model capable of “reliably detecting” pancreatic cancer in its early stages. The prediction model leverages regularly measured biomarkers in the blood to sharpen diagnostic processes for pancreatic cancer and reduce the need for unnecessary biopsy procedures by 6%.

Pancreatic cancer is difficult to diagnose in its early stages because the pancreas is generally hidden by other organs and is located deep in the abdomen. Furthermore, pancreatic cancer often displays no physical symptoms until the cancer has metastasized to other organs, which makes the condition easy to miss during physical exams or through analyzing symptoms.

This type of cancer accounts for 3% of all cancers in America, has an overall five-year survival rate of 7.2%, and takes around 50,000 lives in the U.S. every year.

To develop the new prediction model for pancreatic cancer, the researchers used data collected from four academic hospitals in the United Kingdom, Italy and the Netherlands on adults diagnosed with pancreatic cancer or benign periampullary disease from 2014 to 2022. Their aim was to see if they could use biomarkers in the blood such as bilirubin and carbohydrate antigen 19-9 [CA19-9] to determine the clinical utility, calibration and discrimination of the prediction model.

The research team found that the novel prediction model could diagnose early-stage pancreatic cancer more effectively than other diagnostic measures and reduced the need for taking patients through invasive diagnostic procedures.

At the moment, physicians use a mix of examining carbohydrate antigen 19-9 (CA19-9) serum levels and clinical symptoms, radiological findings, brush cytology or fine-needle aspiration to diagnose early-stage pancreatic cancer. And while this process is quite time consuming and involves invasive and uncomfortable procedures, it often provides inconsistent results.

As such, diagnosing early-stage pancreatic cancer calls for a faster, less invasive and more effective diagnostic procedure. Prior research efforts to develop diagnostic tools using biomarkers such as bilirubin failed to reach clinical practice even though they presented a suitable alternative to current diagnostic practices. The recent study was the first to develop such a pancreatic prediction model and have it externally validated, finally opening the door to much more effective and less invasive diagnostic procedures for pancreatic cancer.

The study authors say the predictive model exclusively relied on data from lab tests and exhibited high discriminative performance in patients with benign periampullary diseases and early-stage pancreatic cancer. However, they acknowledged that their study had several limitations due to the small sample size and noted that larger randomized clinical studies would be necessary to fully understand the predictive model’s capabilities.

If this predictive model proves its efficacy, the pancreatic cancer drugs that are being developed by several companies such as Renovaro BioSciences Inc. (NASDAQ: RENB) could deliver better clinical outcomes when treatment begins after an early diagnosis of the disease.

NOTE TO INVESTORS: The latest news and updates relating to Renovaro BioSciences Inc. (NASDAQ: RENB) are available in the company’s newsroom at https://ibn.fm/RENB

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