Researchers have created a tool that uses machine learning to assess a non-Hodgkin lymphoma (NHL) patient’s likely response to chimeric antigen receptor (CAR) T-cell therapy before starting the treatment, according to study results published today in Nature Medicine.
The tool, an unsupervised quantitative model named InflaMix (Inflammation Mixture Model), was developed to assess inflammation, a potential cause of CAR-T failure, by testing for a variety of blood biomarkers in 149 patients with NHL. The model integrates 14 pre-CAR-T infusion laboratory and cytokine measures capturing inflammation and end-organ function.
After training, InflaMix was able to identify an inflammatory signature associated with a high risk of CAR-T treatment failure, including increased hazard of death or relapse (HR, 2.98; 95% CI, 1.60–4.91; P< 0.001).
“InflaMix consistently and reproducibly identified patients with a higher likelihood of disease relapse and mortality, and it provided supplementary predictive value beyond established prognostic markers, including tumor burden,” the authors wrote.
Studies of three independent cohorts comprising 688 patients with NHL who had a wide range of clinical characteristics and disease subtypes and used different CAR-T products were also used to validate the team’s initial findings.
“These studies demonstrate that by using machine learning and blood tests, we could develop a highly reliable tool that can help predict who will respond well to CAR T cell therapy,” said Marcel van den Brink, MD, PhD, the president of City of Hope Los Angeles and City of Hope National Medical Center and a senior author of the paper, in a press release.
“Prior studies had hinted that inflammation might be a risk factor for poor CAR T cell efficacy,” said Sandeep Raj, MD, of Memorial Sloan Kettering Center, lead author of the paper, in the press release. “Our goal was to refine this concept and build a robust and reliable clinical tool that characterizes inflammation in the blood and predicts CAR-T outcomes.”
References
Raj SS, Fei T, Fried S, et al. An inflammatory biomarker signature of response to CAR-T cell therapy in non-Hodgkin lymphoma. Nat Med. 2025. doi:10.1038/s41591-025-03532-x
