We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
PURITAN MEDICAL

Download Mobile App




AI Identifies Advanced Lung Cancer Patients Who Respond to Immunotherapy

By LabMedica International staff writers
Posted on 10 Oct 2023

Lung cancer treatment planning is often complex due to the variations in evaluating immune biomarkers. More...

In a new study, researchers utilized artificial intelligence (AI) and digital pathology techniques to improve the accuracy of such evaluations.

The study by scientists at the Yale School of Medicine (New Haven, CT, USA) focused on how AI-based digital assessment could fare against traditional manual methods in scoring the PD-L1 immune biomarker. The goal was to see if a novel immunotherapy treatment called atezolizumab could be beneficial for patients suffering from advanced non-small cell lung cancer (NSCLC). To undertake this research, they drew upon data from the IMpower 110 phase III trial, which examined the effectiveness of atezolizumab against chemotherapy for treating advanced NSCLC. Through both manual and AI-guided evaluations of tumor cells, the team discovered that the AI system was more efficient at identifying patients as PD-L1 positive than manual methods.

Moreover, the study found that both AI-based and traditional manual scoring techniques were equally competent at predicting patient results, including how long patients lived and how long it took before the cancer progressed. Additionally, the AI system aided in confirming that for patients with a particular subtype of NSCLC known as squamous histology, the existence of PD-L1+ lymphocytes was linked to better outcomes in terms of slowing down disease progression when treated with atezolizumab.

“Our study suggests that artificial intelligence has the ability to improve the identification of PD-L1 positive patients by providing a predictive accuracy that was better than manual scoring,” said Roy S. Herbst, lead study author and deputy director of Yale Cancer Center. “The research underscores the potential of digital pathology and AI tools in enhancing PD-L1 scoring accuracy for both clinical practice and clinical trials.”

“The insights gained with AI and digital scoring could make diagnosing and choosing the right treatment easier,” added Herbst. “Our data shows that this AI technology can help refine strategies for treating advanced non-small cell lung cancer.”

Related Links:
Yale School of Medicine 


Gold Member
Automatic Hematology Analyzer
CF9600
Online QC Software
Acusera 24•7
All-in-One Molecular System
AIO M160
Prefilled Tubes
Prefilled 5.0ml Tubes
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Hematology

view channel
Image Credit: Shutterstock

New Biomarkers Predict Resistance to Targeted Therapy in Rare Blood Cancer

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and aggressive leukemia with limited treatment options and a poor prognosis. Although tagraxofusp is the first approved targeted therapy for... Read more

Immunology

view channel
Image:Proteomic tear-fluid analysis revealed abnormal patterns in proteins that regulate nerves and T cells in individuals with eye problems (Image Credit: Adobe Stock)

Diagnostic Models Detect Hidden Eye Abnormalities After Mild COVID-19

Persistent ocular symptoms after COVID-19 can severely affect reading, work, and daily tasks, yet standard eye exams often reveal no clear abnormalities. Patients experiencing photophobia, eye pain, and... Read more

Industry

view channel
Photo courtesy of Natera

Natera’s Signatera Earns IVDR Certification for Solid Tumor MRD Testing

Natera’s Signatera has received certification as a Class C device under the European Union’s In Vitro Diagnostic Regulation (IVDR), becoming the first personalized MRD test for solid tumors to achieve... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.