Christine Schmitz1, Andreas Hüttmann2, Stefan P Müller3, Maher Hanoun2, Ronald Boellaard4, Marcus Brinkmann5, Karl-Heinz Jöckel6, Ulrich Dührsen2, Jan Rekowski6. 1. Department of Hematology, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany. Electronic address: christine.schmitz@uk-essen.de. 2. Department of Hematology, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany. 3. Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany. 4. Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands. 5. Center for Clinical Trials, University Hospital Essen, University of Duisburg-Essen, Essen, Germany. 6. Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Abstract
BACKGROUND: Valid prognostic tools are needed to guide risk-adjusted treatment approaches in patients with diffuse large B-cell lymphoma (DLBCL). METHODS: We assessed total metabolic tumor volume (TMTV) and standardized uptake value (SUV)-based interim positron emission tomography (iPET) response in 510 patients with DLBCL participating in the positron emission tomography-guided therapy of aggressive non-Hodgkin lymphomas (PETAL) trial (NCT00554164). TMTV was analyzed with a relative (SUV41max) and a fixed thresholding method (SUV4), and iPET was evaluated using the ΔSUVmax procedure. We determined associations between TMTV and international prognostic index (IPI) factors using Welch's t-test, investigated effects of TMTV, iPET response, and the IPI factors on time to progression (TTP), progression-free survival (PFS), and overall survival (OS) by Cox regression, and estimated the outcome using Kaplan-Meier curves. FINDINGS: TMTV was associated with all IPI factors except age. Irrespective of the thresholding method used, TMTV and iPET response were correlated with TTP, PFS, and OS, and remained the only independent outcome predictors in Cox regression analysis. By dichotomizing TMTV (cut-off: 328 cm³ by SUV41max) and iPET response (cut-off: 66% SUVmax reduction), we defined three groups at different risk of treatment failure (low [57.1% of patients]: low TMTV/good iPET response; intermediate [37.8%]: high TMTV/good iPET response or low TMTV/poor iPET response; and high [5.1%]: high TMTV/poor iPET response), with corresponding 2-year probabilities of 93.8% vs. 67.3% vs. 38.5% for TTP, 90.9% vs. 62.5% vs. 29.9% for PFS, and 95.5% vs. 77.4% vs. 37.1% for OS. INTERPRETATION: The PET-based risk model proposed may help identify patients who may benefit from treatment modifications or novel approaches.
BACKGROUND: Valid prognostic tools are needed to guide risk-adjusted treatment approaches in patients with diffuse large B-cell lymphoma (DLBCL). METHODS: We assessed total metabolic tumor volume (TMTV) and standardized uptake value (SUV)-based interim positron emission tomography (iPET) response in 510 patients with DLBCL participating in the positron emission tomography-guided therapy of aggressive non-Hodgkin lymphomas (PETAL) trial (NCT00554164). TMTV was analyzed with a relative (SUV41max) and a fixed thresholding method (SUV4), and iPET was evaluated using the ΔSUVmax procedure. We determined associations between TMTV and international prognostic index (IPI) factors using Welch's t-test, investigated effects of TMTV, iPET response, and the IPI factors on time to progression (TTP), progression-free survival (PFS), and overall survival (OS) by Cox regression, and estimated the outcome using Kaplan-Meier curves. FINDINGS: TMTV was associated with all IPI factors except age. Irrespective of the thresholding method used, TMTV and iPET response were correlated with TTP, PFS, and OS, and remained the only independent outcome predictors in Cox regression analysis. By dichotomizing TMTV (cut-off: 328 cm³ by SUV41max) and iPET response (cut-off: 66% SUVmax reduction), we defined three groups at different risk of treatment failure (low [57.1% of patients]: low TMTV/good iPET response; intermediate [37.8%]: high TMTV/good iPET response or low TMTV/poor iPET response; and high [5.1%]: high TMTV/poor iPET response), with corresponding 2-year probabilities of 93.8% vs. 67.3% vs. 38.5% for TTP, 90.9% vs. 62.5% vs. 29.9% for PFS, and 95.5% vs. 77.4% vs. 37.1% for OS. INTERPRETATION: The PET-based risk model proposed may help identify patients who may benefit from treatment modifications or novel approaches.
Authors: J J Eertink; C N Burggraaff; M W Heymans; U Dührsen; A Hüttmann; C Schmitz; S Müller; P J Lugtenburg; S F Barrington; N G Mikhaeel; R Carr; S Czibor; T Györke; L Ceriani; E Zucca; M Hutchings; L Kostakoglu; A Loft; S Fanti; S E Wiegers; S Pieplenbosch; R Boellaard; O S Hoekstra; J M Zijlstra; H C W de Vet Journal: Blood Adv Date: 2021-05-11
Authors: Coreline N Burggraaff; Jakoba J Eertink; Pieternella J Lugtenburg; Otto S Hoekstra; Anne I J Arens; Bart de Keizer; Martijn W Heymans; Bronno van der Holt; Sanne E Wiegers; Simone Pieplenbosch; Ronald Boellaard; Henrica C W de Vet; Josée M Zijlstra Journal: J Nucl Med Date: 2021-10-21 Impact factor: 11.082
Authors: N George Mikhaeel; Martijn W Heymans; Jakoba J Eertink; Henrica C W de Vet; Ronald Boellaard; Ulrich Dührsen; Luca Ceriani; Christine Schmitz; Sanne E Wiegers; Andreas Hüttmann; Pieternella J Lugtenburg; Emanuele Zucca; Gerben J C Zwezerijnen; Otto S Hoekstra; Josée M Zijlstra; Sally F Barrington Journal: J Clin Oncol Date: 2022-03-31 Impact factor: 50.717
Authors: Gerben J C Zwezerijnen; Jakoba J Eertink; Coreline N Burggraaff; Sanne E Wiegers; Ekhlas A I N Shaban; Simone Pieplenbosch; Daniela E Oprea-Lager; Pieternella J Lugtenburg; Otto S Hoekstra; Henrica C W de Vet; Josee M Zijlstra; Ronald Boellaard Journal: J Nucl Med Date: 2021-03-05 Impact factor: 11.082
Authors: Christine Schmitz; Andreas Hüttmann; Stefan P Müller; Maher Hanoun; Ronald Boellaard; Marcus Brinkmann; Karl-Heinz Jöckel; Ulrich Dührsen; Jan Rekowski Journal: Data Brief Date: 2019-12-12
Authors: Christine Schmitz; Jan Rekowski; Stefan P Müller; Navid Farsijani; Bernd Hertenstein; Christiane Franzius; Ulla von Verschuer; Paul La Rosée; Martin Freesmeyer; Stefan Wilop; Thomas Krohn; Aruna Raghavachar; Arnold Ganser; Frank M Bengel; Gabriele Prange-Krex; Frank Kroschinsky; Jörg Kotzerke; Aristoteles Giagounidis; Ulrich Dührsen; Andreas Hüttmann Journal: Cancer Med Date: 2020-09-14 Impact factor: 4.452