Gustave Roussy Immune Score Validation in Patients Treated with Bispecific CD3 T-cell Engagers in Phase I Clinical...

The Gustave Roussy Immune (GRIm) score, based on the neutrophil-to-lymphocyte ratio, serum albumin, and lactate dehydrogenase, is a validated prognostic marker in patients receiving immune checkpoint blockers (ICB). We evaluated its prognostic value in patients treated with bispecific CD3 T-cell engagers (TCE) in phase I trials. We retrospectively analyzed prospectively collected data from 150 patients treated with TCEs alone or combined with ICBs across 11 phase I trials at the Drug Development Department, Gustave Roussy (June 2016-February 2025). Overall survival (OS) and progression-free survival (PFS) were estimated using Kaplan-Meier methodology and Cox regression models. Discriminatory performance was assessed using Harrell C-index. Among 150 patients, 127 (85%) had solid tumors, and 23 (15%) had hematologic malignancies; 81% were classified as low-risk GRIm score. Low GRIm score was associated with improved OS [hazard ratio (HR), 0.29; 95% confidence interval (CI), 0.17-0.47; P < 0.001; median OS, 17.6 vs. 5 months] and PFS (HR, 0.57; 95% CI, 0.36-0.89; P = 0.01; median PFS, 2.8 vs. 1.6 months). In solid tumors, the GRIm score remained prognostic for OS (HR, 0.41; P = 0.002) but not for PFS. In hematologic malignancies, it strongly predicted both OS (HR, 0.04; P < 0.001) and PFS. Multivariable analyses confirmed the GRIm score as independently prognostic for OS (HR, 0.29; P < 0.001) and PFS (HR, 0.60; P = 0.035). Similar findings were observed in patients receiving TCE in monotherapy. The GRIm score independently predicts outcomes in patients receiving TCEs in phase I trials and may support patient selection, particularly in hematologic malignancies.

This study validates the use of the GRIm score as a prognostic tool for patients treated with TCE in early-phase trials. It discriminates between low- and high-risk patients across solid and hematologic malignancies and supports the integration of simple biomarkers into patient selection and risk stratification for bispecific CD3 therapies, improving trial design and remaining feasible in routine clinical practice settings.