An international research team led by Dr. Patrick Starlinger, a hepatobiliary and pancreas surgeon from Mayo Clinic Comprehensive Cancer Center, developed a risk prediction model that can be calculated with a smartphone app. It provides an individualized risk assessment for patients before liver resection to evaluate the safety of liver surgery. Compared to standard preoperative tests, the research suggests the model offers a predictive model for postoperative liver failure.
The model's effectiveness is documented in a paper that involved more than 14,000 patients from 10 different institutions and the National Surgery Quality Improvement Program (NSQIP), an algorithm-based database from the U.S. The study is published in the Annals of Surgery.
Surgical removal of parts of the liver remains the only curative approach for patients with liver-specific cancer. Normally, the liver can tolerate the surgical removal, also known as resection, of up to 75% of its volume and maintain its functions after surgery. However, depending on the underlying chronic liver disease, the type of cancer or the extent of resection, patients may be at higher risk of inadequate postoperative liver regeneration or even postoperative liver failure, the main cause of mortality after liver surgery.
The team of researchers developed a multivariable risk prediction model using basic patient characteristics such as age, sex, tumor type and planned type of liver resection, as well as the APRI+ALBI score. The APRI+ALBI score is an established liver function test, calculated using only routine laboratory parameters (aspartate aminotransferase (AST), platelets, albumin, bilirubin). It has already been shown to be closely related to preoperative liver function and chemotherapy-induced liver injury, and it has significant predictive potential for the development of postoperative liver failure. The APRI+ALBI score provides a comprehensive assessment of liver function, especially compared to classic liver function tests, which usually only assess the excretory capacity of the liver.
"We have taken an important step in translating this into clinical practice by developing a freely available smartphone application that allows us to calculate our score and thus individualize the risk assessment of patients before liver resection," says Dr. Starlinger, senior author of the study. "This sets a new standard in preoperative risk assessment and will significantly increase the safety of liver surgery for patients worldwide."
Details about the app and a full list of centers involved in the research are available in the news release by the Medical University of Vienna.
