Dual Immunotherapy in Aggressive Lymphoma (DIAL) study, a randomized phase 2 trial of Varlilumab in combination with Nivolumab in patients with relapsed/refractory B-cell non-Hodgkin lymphoma
No container title available | September 24, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Varlilumab is a monoclonal antibody with agonistic activity on CD27. The efficacy of single-agent PD-1 inhibitors on aggressive B-cell non-Hodkin lymphoma is limited. Preclinical and phase 1 data suggest that Varlilumab is safe and may have synergistic activity with PD-1 inhibitors. In the DIAL study, we explored whether dual immunomodulatory therapy with Varlilumab and Nivolumab in patients with relapsed/refractory aggressive B-NHL was safe and effective. We conducted a randomized phase II clinical trial on adult patients with relapsed/refractory aggressive B-NHL. Patients were randomized to receive Nivolumab monotherapy in the control group and Varlilumab combined with Nivolumab in the experimental group. Crossover to the experimental group was allowed upon progression in the control group. The primary endpoint was the overall response rate based on the Lymphoma Response to Immunomodulatory Therapy Criteria (LYRIC). 54 patients underwent randomization, and 51 received assigned intervention and were included in the intention-to-treat analysis. Objective response was observed in 6 out of 51 patients (ORR 12%). There were 4 responders (ORR 16%) in the Nivolumab group and 2 responders (ORR 7.6%) in the Nivolumab and Varlilumab combination group (p = 0.3). None of the 7 patients that crossed over to the experimental group responded to the addition of Varlilumab. The ORR of patients who were previously exposed to CAR-T cell therapy was 13% (5 out of 39) compared to 8.3% (1 out of 12) in the unexposed patients (p > 0.99). The rate of treatment emergent adverse events was similar between groups, and there was no fatal TEAE in the study. The addition of Varlilumab to Nivolumb did not improve outcomes in patients with aggressive B-NHL. Even though this trial was not designed to evaluate immunotherapy as a rescue therapy after CAR-T failure, most patients (76%) had previously received CAR-T therapy, and their outcomes were equally poor.
Development and Validation of a Novel Conditional Event‐Free Survival Tool in Diffuse Large B‐Cell Lymphoma
American Journal of Hematology | June 4, 2026 | Volume: 101 | Issue: 9 | Pages: 2137-2146
ABSTRACT One quarter of patients with diffuse large B‐cell lymphoma (DLBCL) who achieve a complete response following front‐line therapy will eventually experience disease relapse. Existing prognostic models use baseline factors to predict outcomes from the start of initial therapy and are not intended for use following completion of treatment. We developed a conditional event‐free survival (cEFS) tool that predicts a patient's risk of lymphoma recurrence after completing front‐line therapy taking into consideration baseline risk characteristics plus the time the patient has been in remission. Model development used pooled and harmonized data from two observational cohorts and four randomized trials of patients with newly diagnosed DLBCL treated with immunochemotherapy and either achieving a complete response or not experiencing an event within 12 weeks of end of therapy. Cox proportional‐hazards regression modeling with backwards stepwise selection was utilized for model development. External validation was performed using a large independent data registry. In total, data from 2757 patients were used for model development. The risk of experiencing an event at a time point after having survived a period of time could be computed parsimoniously using four basic predictors: age, ECOG performance status grade, Ann Arbor stage, and lactate dehydrogenase level. C‐index in the model development cohort was 0.65 (95% CI, 0.63–0.68), compared to 0.64 (95% CI, 0.62–0.66) in the external validation cohort. We believe that this dynamic risk prediction tool will not only aid clinicians in providing data‐driven recommendations for surveillance, but also assist patients themselves with key decisions, such as family planning.