Pirtobrutinib versus usual care for patients with richter transformation of chronic lymphocytic leukemia: Inverse probability of treatment weighting-based analysis of BRUIN trial and mayo observational cohort

Abstract Introduction: Pirtobrutinib, a highly selective non-covalent BTK inhibitor, demonstrated encouraging efficacy in Richter transformation (RT) of chronic lymphocytic leukemia (CLL) in the BRUIN trial (Wierda et al, Lancet Haematology, 2024). However, a control arm was not included in this phase 1/2 trial, and how pirtobrutinib compares to usual care is unknown. To address this gap of knowledge, we sought to compare efficacy outcomes in BRUIN to that in a control cohort consisting of RT patients treated with usual care at Mayo Clinic. Methods: The study was approved by the Mayo Clinic IRB. Patient-level data from BRUIN (n=79; investigator-assessed) were obtained from the study sponsor. Patients with histologically confirmed RT (large B-cell lymphoma) who received at least one line of therapy (n=230) were identified from the Mayo Clinic CLL Database. Multivariable logistic regression was employed to calculate propensity scores for baseline covariates (ie, age at RT treatment line, number of prior lines of CLL treatment [truncated at 3], number of prior lines of RT treatment [truncated at 3], and LDH). For each Mayo patient, propensity scores for each line of RT therapy were calculated, and the line with the highest propensity score was chosen as the index RT treatment line. Using the inverse probability treatment weighting (IPTW) methodology, individual weights were computed, and standardized mean differences (SMDs) were examined for each of the unadjusted and weighted baseline covariates to ensure that balance was obtained between BRUIN cases and Mayo controls. Overall survival (OS; the primary endpoint) and progression-free survival (PFS) were analyzed using unweighted and weighted Cox proportional hazards models. Unweighted and weighted overall response rates (ORRs) and complete response (CR) rates were analyzed using logistic regression. Results: The final analysis dataset contained 79 BRUIN cases (median age 67 [range 26-95], 66% male) and 204 Mayo controls (median age 69 [range 30-89], 74% male). The BRUIN cohort had more patients with ECOG PS ≥1 (61% vs 40%, p=0.001) and elevated LDH (81% vs 63%, p=0.003) than the Mayo cohort. The proportion of patients with TP53 aberration was not statistically different in both cohorts (57% vs. 44%, p=0.15). The index line of RT treatment in the Mayo cohort included chemoimmunotherapy (n=167, 80%) and novel agent-based therapy (eg, cBTKi, venetoclax, PI3Ki, immune checkpoint inhibitor, etc; n=42, 20%). Median lines of prior CLL therapy were 2 (IQR 1-4) vs 1 (IQR 0-3) in the BRUIN and Mayo cohorts, respectively; median lines of prior RT therapy were 2 (IQR 1-2) vs 0 (IQR 0-2). The SMDs of the weighted baseline factors met pre-determined criteria (-0.25≤SMD≤0.25), indicating that balance between the two cohorts was achieved. The median follow-up was 18.3 months (range 0.7-32.9) in the BRUIN cohort and 122.8 months (range 0-280.2) in the Mayo cohort. The unweighted median OS was 12.5 months (95% CI 7.0-20.6) in the BRUIN cohort and 5.7 months (95% CI 3.9-10.7) in the Mayo cohort. The unweighted HR was 0.76 (95% CI 0.54-1.07, p=0.12). After IPTW, the weighted HR was 0.63 (95% CI 0.50-0.78, p<0.001), significantly favoring the BRUIN cohort. The unweighted median PFS was 3.6 months (95% CI 2.8-5.1) in the BRUIN cohort and 3.1 months (95% CI 2.5-4.3) in the Mayo cohort. The unweighted HR was 0.98 (95%CI 0.72-1.34, p=0.92). After IPTW, the weighted HR was 0.78 (95% CI 0.64-0.95, p=0.01), again favoring the BRUIN cohort. Response was evaluable/available in 69 patients in BRUIN and 182 patients in Mayo cohort. The unweighted ORR was 58% vs 53% in BRUIN and Mayo cohorts, respectively (OR=0.83, 95% CI 0.47-1.45, p=0.51), and the CR rate was 16% vs 36% (OR=2.94, 95% CI 1.43-5.88, p=0.003). After IPTW, the weighted OR was 0.65 (95% CI 0.45-0.93, p=0.02) for ORR, favoring the BRUIN cohort, and 1.89 (95%CI 1.23-2.86, p=0.02) for CR rate, favoring the Mayo cohort. Conclusions: This individual patient-level IPTW-based analysis demonstrated that single agent pirtobrutinib is associated with improved OS, PFS, and ORR compared to usual care in patients with RT. These results support the choice of pirtobrutinib over traditional therapies for RT. Although these results are encouraging, the durability of response to pirtobrutinib remains suboptimal. Ongoing trials and other future research will evaluate the efficacy of pirtobrutinib in combination with other treatments in this setting.