Jan Rekowski1, Andreas Hüttmann2, Christine Schmitz2, Stefan P Müller3, Lars Kurch4, Jörg Kotzerke5, Christiane Franzius6, Matthias Weckesser7, Frank M Bengel8, Martin Freesmeyer9, Andreas Hertel10, Thomas Krohn11, Jens Holzinger12, Ingo Brink13, Uwe Haberkorn14, Fonyuy Nyuyki15, Daniëlle M E van Assema16, Lilli Geworski17, Dirk Hasenclever18, Karl-Heinz Jöckel19, Ulrich Dührsen2. 1. Institut für Medizinische Informatik, Biometrie, und Epidemiologie, Universitätsklinikum, Essen, Germany jan.rekowski@uk-essen.de. 2. Klinik für Hämatologie, Universitätsklinikum, Essen, Germany. 3. Klinik für Nuklearmedizin, Universitätsklinikum, Essen, Germany. 4. Klinik und Poliklinik für Nuklearmedizin, Universitätsklinikum, Leipzig, Germany. 5. Klinik für Nuklearmedizin, Universitätsklinikum Carl Gustav Carus, Dresden, Germany. 6. Zentrum für moderne Diagnostik (Zemodi), Zentrum für Nuklearmedizin und PET/CT, Bremen, Germany. 7. Klinik für Nuklearmedizin, Universitätsklinikum, Münster, Germany. 8. Klinik für Nuklearmedizin, Medizinische Hochschule, Hannover, Germany. 9. Klinik für Nuklearmedizin, Universitätsklinikum, Jena, Germany. 10. Klinik für Diagnostische und Therapeutische Nuklearmedizin, Klinikum, Fulda, Germany. 11. Klinik für Nuklearmedizin, Universitätsklinikum, Aachen, Germany. 12. Institut für Diagnostische Radiologie, Neuroradiologie, und Nuklearmedizin, Johannes Wesling Klinikum, Minden, Germany. 13. Klinik für nuklearmedizinische Diagnostik und Therapie, Ernst von Bergmann Klinikum, Potsdam, Germany. 14. Radiologische Klinik und Poliklinik, Universitätsklinikum, Heidelberg, Germany. 15. Klinik für Nuklearmedizin, Brüderkrankenhaus St. Josef, Paderborn, Germany. 16. Department of Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands. 17. Stabsstelle Strahlenschutz und Abteilung Medizinische Physik, Medizinische Hochschule, Hannover, Germany; and. 18. Institut für Medizinische Informatik, Statistik, und Epidemiologie, Universität Leipzig, Leipzig, Germany. 19. Institut für Medizinische Informatik, Biometrie, und Epidemiologie, Universitätsklinikum, Essen, Germany.
Abstract
The value of interim 18F-FDG PET/CT (iPET)-guided treatment decisions in patients with diffuse large B-cell lymphoma (DLBCL) has been the subject of much debate. This investigation focuses on a comparison of the Deauville score and the change-in-SUVmax (ΔSUVmax) approach-2 methods to assess early metabolic response to standard chemotherapy in DLBCL. Methods: Of 609 DLBCL patients participating in the PET-Guided Therapy of Aggressive Non-Hodgkin Lymphomas trial, iPET scans of 596 patients originally evaluated using the ΔSUVmax method were available for post hoc assessment of the Deauville score. A commonly used definition of an unfavorable iPET result according to the Deauville score is an uptake greater than that of the liver, whereas an unfavorable iPET scan with regard to the ΔSUVmax approach is characterized as a relative reduction of the SUVmax between baseline and iPET staging of less than or equal to 66%. We investigated the 2 methods' correlation and concordance by Spearman rank correlation coefficient and the agreement in classification, respectively. We further used Kaplan-Meier curves and Cox regression to assess differences in survival between patient subgroups defined by the prespecified cutoffs. Time-dependent receiver-operating-characteristic curve analysis provided information on the methods' respective discrimination performance. Results: Deauville score and ΔSUVmax approach differed in their iPET-based prognosis. The ΔSUVmax approach outperformed the Deauville score in terms of discrimination performance-most likely because of a high number of false-positive decisions by the Deauville score. Cutoff-independent discrimination performance remained low for both methods, but cutoff-related analyses showed promising results. Both favored the ΔSUVmax approach, for example, for the segregation by iPET response, where the event-free survival hazard ratio was 3.14 (95% confidence interval, 2.22-4.46) for ΔSUVmax and 1.70 (95% confidence interval, 1.29-2.24) for the Deauville score. Conclusion: When considering treatment intensification, the currently used Deauville score cutoff of an uptake above that of the liver seems to be inappropriate and associated with potential harm for DLBCL patients. The ΔSUVmax criterion of a relative reduction in SUVmax of less than or equal to 66% should be considered as an alternative.
The value of interim 18F-FDG PET/CT (iPET)-guided treatment decisions in patients with diffuse large B-cell lymphoma (DLBCL) has been the subject of much debate. This investigation focuses on a comparison of the Deauville score and the change-in-SUVmax (ΔSUVmax) approach-2 methods to assess early metabolic response to standard chemotherapy in DLBCL. Methods: Of 609 DLBCL patients participating in the PET-Guided Therapy of Aggressive Non-Hodgkin Lymphomas trial, iPET scans of 596 patients originally evaluated using the ΔSUVmax method were available for post hoc assessment of the Deauville score. A commonly used definition of an unfavorable iPET result according to the Deauville score is an uptake greater than that of the liver, whereas an unfavorable iPET scan with regard to the ΔSUVmax approach is characterized as a relative reduction of the SUVmax between baseline and iPET staging of less than or equal to 66%. We investigated the 2 methods' correlation and concordance by Spearman rank correlation coefficient and the agreement in classification, respectively. We further used Kaplan-Meier curves and Cox regression to assess differences in survival between patient subgroups defined by the prespecified cutoffs. Time-dependent receiver-operating-characteristic curve analysis provided information on the methods' respective discrimination performance. Results: Deauville score and ΔSUVmax approach differed in their iPET-based prognosis. The ΔSUVmax approach outperformed the Deauville score in terms of discrimination performance-most likely because of a high number of false-positive decisions by the Deauville score. Cutoff-independent discrimination performance remained low for both methods, but cutoff-related analyses showed promising results. Both favored the ΔSUVmax approach, for example, for the segregation by iPET response, where the event-free survival hazard ratio was 3.14 (95% confidence interval, 2.22-4.46) for ΔSUVmax and 1.70 (95% confidence interval, 1.29-2.24) for the Deauville score. Conclusion: When considering treatment intensification, the currently used Deauville score cutoff of an uptake above that of the liver seems to be inappropriate and associated with potential harm for DLBCL patients. The ΔSUVmax criterion of a relative reduction in SUVmax of less than or equal to 66% should be considered as an alternative.
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: Sally F Barrington; Jakoba J Eertink; Henrika C W de Vet; N George Mikhaeel; Otto S Hoekstra; Josee M Zijlstra Journal: J Nucl Med Date: 2021-04-23 Impact factor: 11.082
Authors: Martina Broecker-Preuss; Nina Becher-Boveleth; Stefan P Müller; Andreas Hüttmann; Christine Hanoun; Hong Grafe; Julia Richter; Wolfram Klapper; Jan Rekowski; Andreas Bockisch; Ulrich Dührsen Journal: J Cancer Res Clin Oncol Date: 2021-10-27 Impact factor: 4.322
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