VENETOCLAX‐OBINUTUZUMAB MODULATES CLONAL GROWTH: RESULTS OF A POPULATION‐BASED MINIMAL RESIDUAL DISEASE MODEL FROM THE RANDOMIZED CLL14 STUDY

Othman Al‐Sawaf(University Hospital Cologne), C Zhang(University Hospital Cologne), Tiewei Lu(Kaiser Permanente San Francisco Medical Center), Minsi Liao(Kaiser Permanente San Francisco Medical Center), Amey C Panchal(Roche (United Kingdom)), Sandra Robrecht(University Hospital Cologne), Travers Ching(Adaptive Biotechnologies (United States)), Maneesh Tandon(Roche (United Kingdom)), Anna‐Maria Fink(University Hospital Cologne), Eugen Tausch(University Hospital Ulm), Matthias Ritgen(University of Lübeck), Sebastian Böttcher(University of Rostock), Karl‐Anton Kreuzer(University Hospital Cologne), S Kim(AbbVie (United States)), David Miles(Gener8 (United States)), Clemens‐Martin Wendtner(München Klinik Schwabing), Stephan Stilgenbauer(University Hospital Ulm), Barbara Eichhorst(University Hospital Cologne), Yan Jiang(Kaiser Permanente San Francisco Medical Center), Michael Hallek(University Hospital Cologne), Kirsten Fischer(University Hospital Cologne)
Hematological Oncology
June 1, 2021
Cited by 3Open Access
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Abstract

Introduction: The CLL14 study has established fixed-duration treatment with the BCL2 inhibitor venetoclax and the CD20 antibody obinutuzumab (Ven-Obi) for patients (pts) with previously untreated chronic lymphocytic leukemia (CLL). The aim of this report is to provide a population-based exploratory analysis of MRD growth dynamics and to compare growth trajectories after stopping Ven-Obi and chlorambucil-Obi (Clb). Methods: Pts were randomized 1:1 to receive 12 cycles (cy) of Ven with 6 cy of Obi or 12 cy of Clb with 6 cy of Obi. MRD was analyzed by NGS (clonoSEQ Assay). Samples from peripheral blood (PB) are collected every 3-6 months. For the longitudinal analyses of MRD growth dynamics, a population-based logistic growth model with nonlinear mixed effects (NLME) approach was developed to estimate population and individual patient parameters. Cases with at least two measurable timepoints were included; data < LLOQ were incorporated by likelihood-based method. Prognostic markers were screened as covariates for impact on key model parameters based on statistical and graphical assessments. Results: Of 432 enrolled pts, 216 were assigned to receive Clb-Obi and 216 to Ven-Obi. At follow-up month 30, 7 (3.2%) pts in the Clb-Obi arm and 58 (26.9%) pts in the Ven-Obi arm had uMRD levels <10-4 (Fig A,B). Based on the inclusion criteria for the population analysis, 154 pts from Clb-Obi and 153 pts from Ven-Obi arm were included. The model was well calibrated, and high concordance between observed and predicted values was confirmed (Fig C). The median MRD level at EoT was significantly lower after Ven-Obi than after Clb-Obi (10-6.00 vs 10-3.26, p < 2e-16). Within the Ven-Obi arm, end of treatment MRD values did not differ between pts with low-risk and high-risk features, such as IGHV status (10-5.79 for mutated IGHV vs 10-6.12 for unmutated IGHV) or TP53 deletion/mutation (10-5.38 for deletion/mutation vs 10-6.03 for non-deleted/mutated). The median MRD doubling time was longer after Ven-Obi than Clb-Obi therapy (median days 84 versus 67 days, p = 3.3e-5)(Fig D). The median time from EoT to MRD level increase to 10-2 was also longer after Ven-Obi therapy compared to Clb-Obi therapy (median 1225 days versus 227 days, p < 2e-16)(Fig D). Based on a covariate screening of 28 biological and clinical features, the final model showed a significant impact on MRD growth dynamics by Ven-Obi treatment, high MRD levels at the start of treatment, high CLL-IPI, del11q, higher disease burden, response to treatment, and IGHV status (Fig E,F). Conclusion: This analysis establishes a robust, population-based model of MRD growth dynamics that allows description of growth trajectories and treatment effects after treatment cessation. In addition to more effective MRD eradication with Ven-Obi, our results demonstrate that MRD growth is modulated more efficiently by BCL2-targeting treatment in contrast to genotoxic chemoimmunotherapy. The research was funded by: Hoffmann-La Roche Ltd.; AbbVie Inc. Keywords: Diagnostic and Prognostic Biomarkers, Chronic Lymphocytic Leukemia (CLL) Conflicts of interests pertinent to the abstract O. Al-Sawaf Consultant or advisory role: Roche, Abbvie Honoraria: Roche, Abbvie Research funding: Roche, Abbvie Educational grants: Roche, Abbvie T. Lu Employment or leadership position: Genentec Inc. M. Z. Liao Employment or leadership position: Genentec Inc. A. Panchal Employment or leadership position: Roche Products Ltd. T. Ching Employment or leadership position: Adaptive Biotechnologies Corp. A.-M. Fink Honoraria: Celgene, Janssen, Hoffmann-LaRoche E. Tausch Honoraria: Roche AG, AbbVie M. Ritgen Honoraria: Hoffmann-LaRoche, AbbVie Research funding: Hoffmann-LaRoche K.-A. Kreuzer Honoraria: Roche, AbbVie Research funding: Roche, AbbVie S. Kim Employment or leadership position: AbbVie Inc. D. Miles Employment or leadership position: Genentec Inc. C. Wendtner Honoraria: Hoffmann-LaRoche, AbbVie, Janssen-Cilag, Gilead, MorphoSys S. Stilgenbauer Honoraria: AbbVie, AstraZeneca, Celgene, Gilead, GSK, Hoffmann-LaRoche, Janssen, Novartis, Pharmacyclics, Sunesis, Verastem Research funding: AbbVie, AstraZeneca, Celgene, Gilead, GSK, Hoffmann-LaRoche, Janssen, Novartis, Pharmacyclics, Sunesis, Verastem B. Eichhorst Honoraria: Hoffmann-LaRoche, AbbVie, Celgene, Novartis, ArQule, BeiGene, Gilead, AstraZeneca, Oxford Biomedica (UK), Adaptive Biotechnologies Research funding: Hoffmann-LaRoche, AbbVie, Janssen Y. Jiang Employment or leadership position: Genentec Inc. M. Hallek Honoraria: Roche, Gilead, Mundipharma, Janssen, Celgene, Pharmacyclics, AbbVie Research funding: Roche, Gilead, Mundipharma, Janssen, Celgene, Pharmacyclics, AbbVie K. Fischer Honoraria: AbbVie, Hoffmann-LaRoche


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