Mulvey, Erin

Abstract Introduction: Epcoritamab (epcor) was the first CD3xCD20 bispecific antibody approved for treatment of R/R DLBCL in May 2023 based on its efficacy and safety in EPCORE NHL-1. Patients (pts) enrolled in clinical trials are highly selected, and those with high-risk features, such as primary refractory disease, early post-CAR T relapse, poor Eastern Cooperative Oncology Group (ECOG) performance status (PS), and CD20+ status are often underrepresented or excluded. As epcor use expands in more heterogeneous, real-world populations, there is increasing interest in understanding pt characteristics and response outcomes associated with its use outside of clinical trials. In particular, pts with DLBCL that is resistant to, or relapse soon after, CAR T are left with limited treatment options and often present with rapidly progressive, resistant disease, making them especially challenging to manage. Generating real-world evidence is critical for informing optimal use of epcor in routine practice. Methods: Real-EPCOR is a multicenter US retrospective chart review study at >8 academic and community oncology centers designed to evaluate the real-world use of epcor. Eligible pts are adults (≥18 years) with R/R DLBCL and ≥2 prior lines of therapy (LOT) who initiated epcor outside of a clinical trial after 5/19/23. Pt demographic, clinical, and treatment data were collected, including ECOG PS, refractory status, prior CAR T, and CD20+ status. Overall response rate (ORR) was evaluated during epcor treatment and defined as the proportion of pts achieving complete response (CR) or partial response among pts with ≥1 evaluable response assessment or who died due to disease progression before response assessment. ORR and CR rate were calculated for the entire cohort, for pts receiving ≥2 cycles of epcor (full cycle is 28 days), and for pts who received prior CAR T. Results: This interim analysis included 34 pts from 2 centers. Data collection and analysis is ongoing and updated results with additional pts and longer follow-up may be included at time of presentation. Median age was 67 years; 68% pts were male and 85% were White. Median time from DLBCL diagnosis to initiation of epcor was 15.5 months. The most common comorbidities were cardiovascular disease (59%) and diabetes mellitus (29%). ECOG PS was ≥2 in 29% of pts, and 85% of pts had Ann Arbor stage 3-4 disease. Nearly all (97%) had CD20+ DLBCL. High-risk features were common at time of epcor initiation, including 53% with International Prognostic Index (IPI) ≥3, 26% with double-hit, and 24% with non-GCB subtype. Among pts who received ≥2 cycles of epcor (n=15), 20% had ECOG PS ≥2 and 33% had IPI ≥3; in post-CAR T pts, 22% had ECOG PS ≥2 and 57% had IPI ≥3. Median number of prior LOT was 3 (range: 2–9); 44% of pts initiated epcor as 3L therapy. Prior to epcor, 41% had primary refractory disease. Following their most recent therapy, 72% had refractory disease, and 43% had DLBCL that was refractory to all prior LOT in those with known refractory status. Most pts (68%) received prior CAR T, with a median interval of 4.6 months from infusion to epcor initiation, and 23% initiated epcor ≤2 months from CAR T. 15 pts (44%) received CAR T in the LOT immediately prior to epcor, 9 (60%) of whom were refractory to CAR T. The ORR was 50% and CR rate was 29% in the overall evaluable population (n=24). 10 pts were not evaluable, as they did not undergo a response assessment either because they remained alive without assessment or experienced a non-progression-related event. Among pts who received ≥2 cycles of epcor, ORR was 85% and CR rate was 54% in the evaluable population (n=13). Among 23 post-CAR T pts, ORR was 53% and CR rate was 33% in the evaluable population (n=15). Conclusion: In this real-world interim analysis, pts with R/R DLBCL treated with epcor had a high proportion of CD20+ disease, higher-risk clinical features, greater comorbidity burden, and more complex treatment histories, including a substantial proportion with prior CAR T, compared to pts in EPCORE NHL-1. Therefore, the ORR remains highly meaningful in the overall cohort despite being lower than the trial. Encouraging ORRs among those who received ≥2 cycles of epcor or had prior CAR T suggest that epcor monotherapy may provide clinical benefit even in difficult-to-treat pts in the real-world setting. Ongoing real-world survival analyses will inform the optimal use of epcor within the evolving treatment landscape of R/R DLBCL.

Abstract Purpose: Polatuzumab vedotin (polatuzumab) was approved for up-front treatment of diffuse large B-cell lymphoma in combination with chemoimmunotherapy (Pola-R-CHP) based on the POLARIX trial. However, when stratified by cell of origin (COO), polatuzumab seems to have greater efficacy in activated B-cell than germinal center B-cell (GCB) subtype disease. Most studies of polatuzumab used RNA expression to assess COO, whereas in routine clinical practice, the immunohistochemistry-based Hans algorithm is used. Experimental Design: To assess the impact of COO by immunohistochemistry on polatuzumab efficacy, we conducted a multicenter real-world study of adults with large B-cell lymphoma (LBCL) receiving polatuzumab from 2015 to 2024, split by receipt of polatuzumab in first-line versus relapsed/refractory settings. The primary endpoint was overall response rate (ORR) to polatuzumab-based treatment in GCB versus non-GCB relapsed/refractory LBCL. Results: Of 740 patients, 305 received polatuzumab in the first-line setting and 435 in the relapsed/refractory setting. In the relapsed/refractory cohort, the ORR in non-GCB versus GCB LBCL was 59.7% versus 36.3% [OR, 2.6; 95% confidence interval (CI), 1.77–3.84; P < 0.0001], with a complete response rate of 35.7% versus 17.7% (OR, 2.6; 95% CI, 1.66–4.02; P < 0.0001). Progression-free survival was longer for patients with non-GCB versus GCB COO (HR, 0.64; 95% CI, 0.5–0.83; P = 0.0006). In the first-line cohort, ORR, complete response rate, and progression-free survival were similar in non-GCB versus GCB LBCL, as hypothesized based on outcomes in the Pola-R-CHP arm of POLARIX, suggesting that the addition of polatuzumab overcomes the adverse risk of non-GCB COO in patients receiving R-CHOP. Conclusions: Based on these data, COO classification by the Hans algorithm is a strong predictor of polatuzumab efficacy in LBCL, informing real-world treatment decisions.

Background: Polatuzumab vedotin (Pola) is an antibody drug conjugate targeting CD79b that incorporates the microtubule disrupting monomethyl auristatin E payload. Pola was approved in 2023 for the upfront treatment of diffuse large B cell lymphoma (DLBCL) in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (polaRCHP) based on the POLARIX trial. However, the activity of pola appears to vary based on DLBCL cell of origin (COO) subtype, with greater efficacy in activated B cell (ABC) DLBCL compared to germinal center B cell (GCB) DLBCL (Russler-Germain Blood 2023). When outcomes in POLARIX are stratified by COO, polaRCHP demonstrated progression free survival (PFS) and overall survival (OS) benefits over RCHOP in patients with ABC but not GCB subtype DLBCL (PFS HR 0.34 ABC vs 1.03 GCB, OS HR 0.27 ABC vs 1.64 GCB; Morschhauser ASH 2023 and FDA data). Most prospective studies of pola used gene expression to assess COO, which is not readily clinically available. This study aims to examine if COO subtype by Hans algorithm (based on CD10, BCL6, and MUM1 expression by immunohistochemistry) is predictive of pola responses and outcomes in patients with large B cell lymphoma (LBCL). Methods: We conducted a retrospective, multicenter observational study of adults with LBCL who received pola (monotherapy or in combination) from 2015-2024 with Hans algorithm COO data and response assessment available. Patients were stratified by receipt of pola in the frontline vs relapsed/refractory (R/R) setting. The primary endpoint was overall response rate (ORR) to pola-based treatment in GCB vs non-GCB subtypes. Secondary endpoints included complete response rate (CRR), PFS, and OS. For time to event endpoints, patients responding to pola who received CAR T or stem cell transplantation prior to progression were censored at time of cellular therapy. Demographics were summarized by descriptive statistics. Comparative and survival analyses used Chi squared/Fischer exact tests and Kaplan Meier analysis. Data cutoff was July 1, 2024. Results: 718 patients were included. Median follow-up was 15 months (interquartile range [IQR] 8-32). Median age at LBCL diagnosis was 66 years (IQR 56-74); 62% were men; 69 (10%) had double hit lymphoma (DHL); 129 (18%) had underlying low grade lymphoma. Pola was used in the frontline setting in 293 (41%) patients, of whom 139 (47%) had GCB vs 154 (53%) non-GCB COO. Of the 426 patients receiving pola for R/R LBCL (including one patient receiving pola retreatment), 224 (53%) had GCB vs 202 (47%) non-GCB COO. Among patients receiving pola-based regimens in the R/R setting (GCB vs non-GCB: pola monotherapy = 7% vs 4%, pola + R = 26% vs 26%, pola + BR = 55% vs 61%, pola + other = 12% vs 9%; p = 0.44), the ORR in GCB vs non-GCB LBCL was 36% vs 61% (p < 0.001), while CRR in GCB vs non-GCB was 17% vs 36% (p < 0.001). COO remained a significant component of logistic multivariate regression models of ORR (p < 0.001) and CRR (p < 0.001) when incorporating IPI at original LBCL diagnosis, histology, DHL status, and refractory status to frontline therapy. Despite this, no significant PFS or OS differences by COO were seen, potentially due to approximately 1/4 patients being censored due to receiving subsequent cellular therapy (e.g. CAR T) prior to progression. In patients receiving frontline pola-based regimens (of which 275 [94%] included an anthracycline), ORR and CRR were similar in GCB vs non-GCB (ORR 89% vs 88% p > 0.5; CRR 76% vs 77% p > 0.5). While PFS and OS were similar between COO groups in the frontline cohort, follow-up and cohort size were limited. Conclusion: Based on this real-world evidence, COO classification by Hans algorithm is a strong predictor of the activity of pola-containing therapy in R/R LBCL, with significantly higher ORR and CRR in patients with non-GCB compared to GCB COO LBCL. This aligns with the cumulative existing evidence. ORR and CRR to pola-containing therapy in the frontline setting did not differ significantly by COO subtype, but longer follow-up of larger cohorts is needed to clarify the predictive role of COO by Hans algorithm in this setting, especially considering the PFS advantage with polaRCHP in POLARIX was not associated with significant differences in ORR or CRR. Overall, clinicians should consider factoring COO subtype into treatment decisions regarding pola-containing regimens, and studies of pola-based therapies should stratify patients and report outcomes by COO subtype.