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Tampa, Florida
Measuring PD-L1 expression in patient tumors is a common biomarker that is often used to determine which patients should receive anti-pd1/PD-L1 treatment
Researchers at Moffitt Cancer Center describe in a new article published in the journal JNCI Cancer Spectrum that they have created a predictive model that includes information calculated from computed tomography images that can identify those that may be Patients who do not respond to immunotherapy
Moffitt’s research team did not analyze common tissue-based biomarkers, such as protein expression patterns, but evaluated the potential of using pre-treatment CT scan features combined with clinical data to identify markers related to the outcome of immunotherapy
"Image-based quantitative features, or radiology, reflect the underlying pathophysiology and tumor heterogeneity as biomarkers of dominant tissues, because they can use standard treatments to quickly extract medical images and capture data from the entire tumor, rather than one A small number of tumor biopsies and laboratory tests," said Dr.
The researchers analyzed the clinical and radiological characteristics of 180 patients with anti-pd1/PD-L1 non-small cell lung cancer with or without anti-ctla-4 treatment
They found that among the 16 clinical features considered, serum albumin levels and the number of metastatic sites in patients were significantly correlated with overall survival
The researchers validated their models in two other patient groups, and confirmed that the overall survival rate of the extremely high-risk group after immunotherapy was extremely low, with a 3-year overall survival rate of 0%, while the 3-year overall survival rate of the low-risk group was 0%.
Schabath said: "These results indicate that very high-risk patients should avoid immunotherapy altogether, or use early-stage combination therapy that may produce improved responses
10.