Stefan Alig1, Charles W Macaulay1, David M Kurtz1, Ulrich Dührsen2, Andreas Hüttmann2, Christine Schmitz2, Michael C Jin1, Brian J Sworder1, Andrea Garofalo1, Mohammad Shahrokh Esfahani1, Barzin Y Nabet3, Joanne Soo1, Florian Scherer1,4, Alexander F M Craig1, Olivier Casasnovas5, Jason R Westin6, Gianluca Gaidano7, Davide Rossi8, Mark Roschewski9, Wyndham H Wilson9, Michel Meignan10, Maximilian Diehn3,11, Ash A Alizadeh1,11. 1. Department of Medicine, Divisions of Oncology and Hematology, Stanford University, Stanford, CA. 2. Department of Hematology, University Hospital of Essen, Essen, Germany. 3. Department of Radiation Oncology, Stanford University Medical Center, Stanford, CA. 4. Department Medicine I, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. 5. Hematology Department, University Hospital F. Mitterrand and Inserm UMR 1231, Dijon, France. 6. Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX. 7. Division of Hematology, Department of Translational Medicine, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy. 8. Oncology Institute of Southern Switzerland and Institute of Oncology Research, Bellinzona, Switzerland. 9. National Cancer Institute, National Institutes of Health, Bethesda, MD. 10. Hôpitaux Universitaires Henri Mondor, Creteil, France. 11. Stanford Cancer Institute, Institute for Stem Cell Biology & Regenerative Medicine, Stanford, CA.
Abstract
PURPOSE: Patients with Diffuse Large B-cell Lymphoma (DLBCL) in need of immediate therapy are largely under-represented in clinical trials. The diagnosis-to-treatment interval (DTI) has recently been described as a metric to quantify such patient selection bias, with short DTI being associated with adverse risk factors and inferior outcomes. Here, we characterized the relationships between DTI, circulating tumor DNA (ctDNA), conventional risk factors, and clinical outcomes, with the goal of defining objective disease metrics contributing to selection bias. PATIENTS AND METHODS: We evaluated pretreatment ctDNA levels in 267 patients with DLBCL treated across multiple centers in Europe and the United States using Cancer Personalized Profiling by Deep Sequencing. Pretreatment ctDNA levels were correlated with DTI, total metabolic tumor volumes (TMTVs), the International Prognostic Index (IPI), and outcome. RESULTS: Short DTI was associated with advanced-stage disease (P < .001) and higher IPI (P < .001). We also found an inverse correlation between DTI and TMTV (RS = -0.37; P < .001). Similarly, pretreatment ctDNA levels were significantly associated with stage, IPI, and TMTV (all P < .001), demonstrating that both DTI and ctDNA reflect disease burden. Notably, patients with shorter DTI had higher pretreatment ctDNA levels (P < .001). Pretreatment ctDNA levels predicted short DTI independent of the IPI (P < .001). Although each risk factor was significantly associated with event-free survival in univariable analysis, ctDNA level was prognostic of event-free survival independent of DTI and IPI in multivariable Cox regression (ctDNA: hazard ratio, 1.5; 95% CI [1.2 to 2.0]; IPI: 1.1 [0.9 to 1.3]; -DTI: 1.1 [1.0 to 1.2]). CONCLUSION: Short DTI largely reflects baseline tumor burden, which can be objectively measured using pretreatment ctDNA levels. Pretreatment ctDNA levels therefore have utility for quantifying and guarding against selection biases in prospective DLBCL clinical trials.
PURPOSE: Patients with Diffuse Large B-cell Lymphoma (DLBCL) in need of immediate therapy are largely under-represented in clinical trials. The diagnosis-to-treatment interval (DTI) has recently been described as a metric to quantify such patient selection bias, with short DTI being associated with adverse risk factors and inferior outcomes. Here, we characterized the relationships between DTI, circulating tumor DNA (ctDNA), conventional risk factors, and clinical outcomes, with the goal of defining objective disease metrics contributing to selection bias. PATIENTS AND METHODS: We evaluated pretreatment ctDNA levels in 267 patients with DLBCL treated across multiple centers in Europe and the United States using Cancer Personalized Profiling by Deep Sequencing. Pretreatment ctDNA levels were correlated with DTI, total metabolic tumor volumes (TMTVs), the International Prognostic Index (IPI), and outcome. RESULTS: Short DTI was associated with advanced-stage disease (P < .001) and higher IPI (P < .001). We also found an inverse correlation between DTI and TMTV (RS = -0.37; P < .001). Similarly, pretreatment ctDNA levels were significantly associated with stage, IPI, and TMTV (all P < .001), demonstrating that both DTI and ctDNA reflect disease burden. Notably, patients with shorter DTI had higher pretreatment ctDNA levels (P < .001). Pretreatment ctDNA levels predicted short DTI independent of the IPI (P < .001). Although each risk factor was significantly associated with event-free survival in univariable analysis, ctDNA level was prognostic of event-free survival independent of DTI and IPI in multivariable Cox regression (ctDNA: hazard ratio, 1.5; 95% CI [1.2 to 2.0]; IPI: 1.1 [0.9 to 1.3]; -DTI: 1.1 [1.0 to 1.2]). CONCLUSION: Short DTI largely reflects baseline tumor burden, which can be objectively measured using pretreatment ctDNA levels. Pretreatment ctDNA levels therefore have utility for quantifying and guarding against selection biases in prospective DLBCL clinical trials.
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